diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_fit.json index d16fdd891c..4830f62d0c 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [103497728.0, 113913856.0, 137256960.0, 137777152.0, 254607360.0, 254996480.0, 261459968.0, 261160960.0]], [34115, [103510016.0, 113741824.0, 137211904.0, 137646080.0, 254373888.0, 254570496.0, 261337088.0, 260444160.0]], [34120, [103165952.0, 113451008.0, 137076736.0, 137322496.0, 254459904.0, 254476288.0, 261480448.0, 260411392.0]], [34126, [103739392.0, 114106368.0, 137379840.0, 137945088.0, 254881792.0, 255049728.0, 261562368.0, 261152768.0]], [34139, [103223296.0, 113680384.0, 137277440.0, 137695232.0, 254709760.0, 254763008.0, 261550080.0, 260673536.0]], [34140, [103124992.0, 113422336.0, 136929280.0, 137273344.0, 254320640.0, 254455808.0, 261271552.0, 260407296.0]], [34141, [103649280.0, 114053120.0, 137433088.0, 137940992.0, 254869504.0, 255119360.0, 261599232.0, 260972544.0]], [34155, [103350272.0, 113602560.0, 137392128.0, 137592832.0, 254574592.0, 254656512.0, 261570560.0, 260857856.0]], [34158, [103219200.0, 113692672.0, 137162752.0, 137601024.0, 254353408.0, 254484480.0, 261353472.0, 260530176.0]], [34160, [103059456.0, 113520640.0, 137191424.0, 137527296.0, 254636032.0, 254545920.0, 261484544.0, 260530176.0]], [34162, [103571456.0, 113774592.0, 137142272.0, 137588736.0, 254435328.0, 254562304.0, 261398528.0, 260444160.0]]] \ No newline at end of file +[[34113, [103497728.0, 113913856.0, 137256960.0, 137777152.0, 254607360.0, 254996480.0, 261459968.0, 261160960.0]], [34115, [103510016.0, 113741824.0, 137211904.0, 137646080.0, 254373888.0, 254570496.0, 261337088.0, 260444160.0]], [34120, [103165952.0, 113451008.0, 137076736.0, 137322496.0, 254459904.0, 254476288.0, 261480448.0, 260411392.0]], [34126, [103739392.0, 114106368.0, 137379840.0, 137945088.0, 254881792.0, 255049728.0, 261562368.0, 261152768.0]], [34139, [103223296.0, 113680384.0, 137277440.0, 137695232.0, 254709760.0, 254763008.0, 261550080.0, 260673536.0]], [34140, [103124992.0, 113422336.0, 136929280.0, 137273344.0, 254320640.0, 254455808.0, 261271552.0, 260407296.0]], [34141, [103649280.0, 114053120.0, 137433088.0, 137940992.0, 254869504.0, 255119360.0, 261599232.0, 260972544.0]], [34155, [103350272.0, 113602560.0, 137392128.0, 137592832.0, 254574592.0, 254656512.0, 261570560.0, 260857856.0]], [34158, [103219200.0, 113692672.0, 137162752.0, 137601024.0, 254353408.0, 254484480.0, 261353472.0, 260530176.0]], [34160, [103059456.0, 113520640.0, 137191424.0, 137527296.0, 254636032.0, 254545920.0, 261484544.0, 260530176.0]], [34162, [103571456.0, 113774592.0, 137142272.0, 137588736.0, 254435328.0, 254562304.0, 261398528.0, 260444160.0]], [34164, [103178240.0, 113532928.0, 137244672.0, 137580544.0, 254705664.0, 254619648.0, 261419008.0, 260558848.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_predict.json index 316ccb0af3..66cc69c753 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [90091520.0, 90091520.0, 90087424.0, 90091520.0, 97619968.0, 97624064.0, 97619968.0, 97619968.0]], [34115, [89739264.0, 89739264.0, 89739264.0, 89743360.0, 97288192.0, 97288192.0, 97288192.0, 97288192.0]], [34120, [89460736.0, 89456640.0, 89473024.0, 89464832.0, 97398784.0, 97398784.0, 97398784.0, 97398784.0]], [34126, [90419200.0, 90419200.0, 90415104.0, 90419200.0, 97943552.0, 97943552.0, 97943552.0, 97943552.0]], [34139, [90320896.0, 90247168.0, 90116096.0, 90120192.0, 97558528.0, 97558528.0, 97558528.0, 97558528.0]], [34140, [89653248.0, 89845760.0, 89640960.0, 89710592.0, 97013760.0, 97013760.0, 97013760.0, 97013760.0]], [34141, [89825280.0, 89812992.0, 89821184.0, 89825280.0, 97734656.0, 97734656.0, 97734656.0, 97734656.0]], [34155, [90021888.0, 90005504.0, 90013696.0, 90005504.0, 97525760.0, 97525760.0, 97525760.0, 97525760.0]], [34158, [89481216.0, 89477120.0, 89546752.0, 89481216.0, 97189888.0, 97189888.0, 97189888.0, 97189888.0]], [34160, [89661440.0, 89595904.0, 89595904.0, 89595904.0, 97505280.0, 97505280.0, 97505280.0, 97505280.0]], [34162, [89456640.0, 89391104.0, 89391104.0, 89391104.0, 97312768.0, 97312768.0, 97312768.0, 97312768.0]]] \ No newline at end of file +[[34113, [90091520.0, 90091520.0, 90087424.0, 90091520.0, 97619968.0, 97624064.0, 97619968.0, 97619968.0]], [34115, [89739264.0, 89739264.0, 89739264.0, 89743360.0, 97288192.0, 97288192.0, 97288192.0, 97288192.0]], [34120, [89460736.0, 89456640.0, 89473024.0, 89464832.0, 97398784.0, 97398784.0, 97398784.0, 97398784.0]], [34126, [90419200.0, 90419200.0, 90415104.0, 90419200.0, 97943552.0, 97943552.0, 97943552.0, 97943552.0]], [34139, [90320896.0, 90247168.0, 90116096.0, 90120192.0, 97558528.0, 97558528.0, 97558528.0, 97558528.0]], [34140, [89653248.0, 89845760.0, 89640960.0, 89710592.0, 97013760.0, 97013760.0, 97013760.0, 97013760.0]], [34141, [89825280.0, 89812992.0, 89821184.0, 89825280.0, 97734656.0, 97734656.0, 97734656.0, 97734656.0]], [34155, [90021888.0, 90005504.0, 90013696.0, 90005504.0, 97525760.0, 97525760.0, 97525760.0, 97525760.0]], [34158, [89481216.0, 89477120.0, 89546752.0, 89481216.0, 97189888.0, 97189888.0, 97189888.0, 97189888.0]], [34160, [89661440.0, 89595904.0, 89595904.0, 89595904.0, 97505280.0, 97505280.0, 97505280.0, 97505280.0]], [34162, [89456640.0, 89391104.0, 89391104.0, 89391104.0, 97312768.0, 97312768.0, 97312768.0, 97312768.0]], [34164, [89952256.0, 89886720.0, 89886720.0, 89886720.0, 97382400.0, 97382400.0, 97382400.0, 97382400.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_transform.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_transform.json index 61a428cb0a..035ed5d789 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_transform.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.peakmem_transform.json @@ -1 +1 @@ -[[34113, [121004032.0, 121069568.0, 121004032.0, 121004032.0, 125075456.0, 125075456.0, 125075456.0, 125075456.0]], [34115, [120623104.0, 120623104.0, 120619008.0, 120606720.0, 124657664.0, 124657664.0, 124653568.0, 124653568.0]], [34120, [120635392.0, 120639488.0, 120631296.0, 120635392.0, 124960768.0, 124964864.0, 124960768.0, 124964864.0]], [34126, [121012224.0, 121004032.0, 120979456.0, 120995840.0, 125128704.0, 125128704.0, 125128704.0, 125128704.0]], [34139, [120754176.0, 120745984.0, 120741888.0, 120750080.0, 124993536.0, 124993536.0, 124993536.0, 124993536.0]], [34140, [120213504.0, 120217600.0, 120205312.0, 120209408.0, 124637184.0, 124637184.0, 124637184.0, 124637184.0]], [34141, [120987648.0, 120983552.0, 120979456.0, 120987648.0, 125247488.0, 125247488.0, 125247488.0, 125247488.0]], [34155, [120709120.0, 120700928.0, 120692736.0, 120684544.0, 124948480.0, 124948480.0, 124948480.0, 124948480.0]], [34158, [120717312.0, 120709120.0, 120713216.0, 120700928.0, 124735488.0, 124735488.0, 124735488.0, 124735488.0]], [34160, [120770560.0, 120758272.0, 120770560.0, 120754176.0, 124940288.0, 124940288.0, 124940288.0, 124940288.0]], [34162, [120791040.0, 120786944.0, 120786944.0, 120774656.0, 124837888.0, 124837888.0, 124837888.0, 124837888.0]]] \ No newline at end of file +[[34113, [121004032.0, 121069568.0, 121004032.0, 121004032.0, 125075456.0, 125075456.0, 125075456.0, 125075456.0]], [34115, [120623104.0, 120623104.0, 120619008.0, 120606720.0, 124657664.0, 124657664.0, 124653568.0, 124653568.0]], [34120, [120635392.0, 120639488.0, 120631296.0, 120635392.0, 124960768.0, 124964864.0, 124960768.0, 124964864.0]], [34126, [121012224.0, 121004032.0, 120979456.0, 120995840.0, 125128704.0, 125128704.0, 125128704.0, 125128704.0]], [34139, [120754176.0, 120745984.0, 120741888.0, 120750080.0, 124993536.0, 124993536.0, 124993536.0, 124993536.0]], [34140, [120213504.0, 120217600.0, 120205312.0, 120209408.0, 124637184.0, 124637184.0, 124637184.0, 124637184.0]], [34141, [120987648.0, 120983552.0, 120979456.0, 120987648.0, 125247488.0, 125247488.0, 125247488.0, 125247488.0]], [34155, [120709120.0, 120700928.0, 120692736.0, 120684544.0, 124948480.0, 124948480.0, 124948480.0, 124948480.0]], [34158, [120717312.0, 120709120.0, 120713216.0, 120700928.0, 124735488.0, 124735488.0, 124735488.0, 124735488.0]], [34160, [120770560.0, 120758272.0, 120770560.0, 120754176.0, 124940288.0, 124940288.0, 124940288.0, 124940288.0]], [34162, [120791040.0, 120786944.0, 120786944.0, 120774656.0, 124837888.0, 124837888.0, 124837888.0, 124837888.0]], [34164, [120713216.0, 120709120.0, 120721408.0, 120692736.0, 124895232.0, 124895232.0, 124899328.0, 124895232.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_fit.json index 29f12a09f1..75125ad12c 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [0.3991625919999251, 1.1519106250000277, 2.1956100815000354, 2.025822658500033, 1.7035213440000234, 4.487753880500009, 3.4755872880000425, 5.539475365000044]], [34115, [0.4026635249999799, 1.1873013180000953, 2.216470701999924, 2.0531785540001692, 1.7705761409999923, 4.480288760500002, 3.4902539449999495, 5.273831873000063]], [34120, [0.40211216299996977, 1.1633003755000573, 2.212211158000173, 2.0084279475000812, 1.7233169915000417, 4.488032942000018, 3.469436167500021, 5.2570577399999365]], [34126, [0.40012225800001033, 1.173765830499974, 2.1955101080000077, 2.0139847700002065, 1.6978514429999905, 4.58890453850006, 3.5042248484999163, 5.139550787999951]], [34139, [0.4082977739999478, 1.1557066195000516, 2.2037055660000533, 2.040967331000047, 1.7343460135000441, 4.572316468499935, 3.42960778149984, 5.242985836999878]], [34140, [0.4029847780000182, 1.187454960499963, 2.223766693000016, 2.0451158105000786, 1.744801667499928, 4.481733167000016, 3.4275020919999406, 5.13400181499992]], [34141, [0.3989542449999135, 1.1734618240000145, 2.2403063369999927, 1.63678648899986, 1.6962858340000366, 4.5424000484998714, 3.42729922049989, 5.041594180999937]], [34155, [0.40839658599998074, 1.161156152999979, 2.1917469114999903, 1.9916972369999257, 1.7699823995000088, 4.676281132999861, 3.477417229499906, 5.447648583999808]], [34158, [0.3988204920001408, 1.1412436389998675, 2.2038729180001155, 1.9200255695000124, 1.6938503379999474, 4.4726111840001295, 3.4682473059999666, 5.107280057000025]], [34160, [0.4031725655000855, 1.1766937979999739, 2.188124683000069, 2.059859763499958, 1.6737285480000992, 4.515105040499975, 3.431167462000076, 5.192366988999993]], [34162, [0.4010699124999064, 1.1896462619999966, 2.214189393999959, 2.0446503519999624, 1.7108321509999769, 4.493956586500076, 3.5202055559999508, 5.300774388000036]]] \ No newline at end of file +[[34113, [0.3991625919999251, 1.1519106250000277, 2.1956100815000354, 2.025822658500033, 1.7035213440000234, 4.487753880500009, 3.4755872880000425, 5.539475365000044]], [34115, [0.4026635249999799, 1.1873013180000953, 2.216470701999924, 2.0531785540001692, 1.7705761409999923, 4.480288760500002, 3.4902539449999495, 5.273831873000063]], [34120, [0.40211216299996977, 1.1633003755000573, 2.212211158000173, 2.0084279475000812, 1.7233169915000417, 4.488032942000018, 3.469436167500021, 5.2570577399999365]], [34126, [0.40012225800001033, 1.173765830499974, 2.1955101080000077, 2.0139847700002065, 1.6978514429999905, 4.58890453850006, 3.5042248484999163, 5.139550787999951]], [34139, [0.4082977739999478, 1.1557066195000516, 2.2037055660000533, 2.040967331000047, 1.7343460135000441, 4.572316468499935, 3.42960778149984, 5.242985836999878]], [34140, [0.4029847780000182, 1.187454960499963, 2.223766693000016, 2.0451158105000786, 1.744801667499928, 4.481733167000016, 3.4275020919999406, 5.13400181499992]], [34141, [0.3989542449999135, 1.1734618240000145, 2.2403063369999927, 1.63678648899986, 1.6962858340000366, 4.5424000484998714, 3.42729922049989, 5.041594180999937]], [34155, [0.40839658599998074, 1.161156152999979, 2.1917469114999903, 1.9916972369999257, 1.7699823995000088, 4.676281132999861, 3.477417229499906, 5.447648583999808]], [34158, [0.3988204920001408, 1.1412436389998675, 2.2038729180001155, 1.9200255695000124, 1.6938503379999474, 4.4726111840001295, 3.4682473059999666, 5.107280057000025]], [34160, [0.4031725655000855, 1.1766937979999739, 2.188124683000069, 2.059859763499958, 1.6737285480000992, 4.515105040499975, 3.431167462000076, 5.192366988999993]], [34162, [0.4010699124999064, 1.1896462619999966, 2.214189393999959, 2.0446503519999624, 1.7108321509999769, 4.493956586500076, 3.5202055559999508, 5.300774388000036]], [34164, [0.4047987330000069, 1.1479588420000937, 2.1900761689998944, 2.005692125499877, 1.7454759530000956, 4.5084293780000735, 3.631464396999945, 5.49597428800007]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_predict.json index e9de2878e1..ab94430d2c 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.005341331000010996, 0.005919542500066655, 0.005370030249991942, 0.005351551999979165, 0.027123178999886477, 0.026950404500098557, 0.026958173500020166, 0.02814085149998391]], [34115, [0.005387183750030999, 0.0053054590000556345, 0.0050876790000415895, 0.005530698499967457, 0.027491750000081083, 0.015590554499908649, 0.027173809000032634, 0.025002518500059523]], [34120, [0.006674845499958337, 0.005060527249952429, 0.005274832749989855, 0.005222928999955911, 0.026948187500011045, 0.027001240000004145, 0.026949467000008553, 0.016581200000132412]], [34126, [0.005305630999998812, 0.005277451000040401, 0.005033459499998116, 0.00513947050006891, 0.02746896650000963, 0.017477015499935078, 0.027208277000113412, 0.028963787000066077]], [34139, [0.0060264682499564515, 0.00538019325000505, 0.005295517250033299, 0.005036914499953582, 0.02652675599995291, 0.015451330500013682, 0.027282724499968936, 0.027040538499932154]], [34140, [0.005370134249972125, 0.005274863750003078, 0.004986624750017654, 0.004967474499949276, 0.026702333499883935, 0.015813256000001275, 0.026208953000036672, 0.027147398499892006]], [34141, [0.005369411749995834, 0.005449970000029225, 0.006042239750001954, 0.005443382999942514, 0.02686560750009903, 0.016750389500089113, 0.026783242999954382, 0.0264179430000695]], [34155, [0.005449921500030541, 0.006350195750030707, 0.00536820974997454, 0.005593024250003964, 0.016569097999877158, 0.028520589500089955, 0.016980785999976433, 0.027345636499831016]], [34158, [0.007472061249984563, 0.005257463750012903, 0.005028145499977654, 0.005436988749977445, 0.02681677649991343, 0.018330416499907187, 0.027959162500110324, 0.02855109999995875]], [34160, [0.005278818499959925, 0.005246694499987825, 0.005393841499937935, 0.005246488500006308, 0.02009956599999896, 0.02649547949999942, 0.02688326700001653, 0.027568882499963365]], [34162, [0.005299623999974301, 0.005170923499974833, 0.006296050999992531, 0.005249648250014616, 0.027433640500021284, 0.027831901500007916, 0.026948239500029558, 0.01647337750000588]]] \ No newline at end of file +[[34113, [0.005341331000010996, 0.005919542500066655, 0.005370030249991942, 0.005351551999979165, 0.027123178999886477, 0.026950404500098557, 0.026958173500020166, 0.02814085149998391]], [34115, [0.005387183750030999, 0.0053054590000556345, 0.0050876790000415895, 0.005530698499967457, 0.027491750000081083, 0.015590554499908649, 0.027173809000032634, 0.025002518500059523]], [34120, [0.006674845499958337, 0.005060527249952429, 0.005274832749989855, 0.005222928999955911, 0.026948187500011045, 0.027001240000004145, 0.026949467000008553, 0.016581200000132412]], [34126, [0.005305630999998812, 0.005277451000040401, 0.005033459499998116, 0.00513947050006891, 0.02746896650000963, 0.017477015499935078, 0.027208277000113412, 0.028963787000066077]], [34139, [0.0060264682499564515, 0.00538019325000505, 0.005295517250033299, 0.005036914499953582, 0.02652675599995291, 0.015451330500013682, 0.027282724499968936, 0.027040538499932154]], [34140, [0.005370134249972125, 0.005274863750003078, 0.004986624750017654, 0.004967474499949276, 0.026702333499883935, 0.015813256000001275, 0.026208953000036672, 0.027147398499892006]], [34141, [0.005369411749995834, 0.005449970000029225, 0.006042239750001954, 0.005443382999942514, 0.02686560750009903, 0.016750389500089113, 0.026783242999954382, 0.0264179430000695]], [34155, [0.005449921500030541, 0.006350195750030707, 0.00536820974997454, 0.005593024250003964, 0.016569097999877158, 0.028520589500089955, 0.016980785999976433, 0.027345636499831016]], [34158, [0.007472061249984563, 0.005257463750012903, 0.005028145499977654, 0.005436988749977445, 0.02681677649991343, 0.018330416499907187, 0.027959162500110324, 0.02855109999995875]], [34160, [0.005278818499959925, 0.005246694499987825, 0.005393841499937935, 0.005246488500006308, 0.02009956599999896, 0.02649547949999942, 0.02688326700001653, 0.027568882499963365]], [34162, [0.005299623999974301, 0.005170923499974833, 0.006296050999992531, 0.005249648250014616, 0.027433640500021284, 0.027831901500007916, 0.026948239500029558, 0.01647337750000588]], [34164, [0.005296630750024178, 0.008038998250015084, 0.005319971999995232, 0.005276809999998022, 0.014903719000130877, 0.027215604000048188, 0.027256012499947246, 0.026799617499932538]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_transform.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_transform.json index d77d34cad4..d027e17871 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_transform.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_transform.json @@ -1 +1 @@ -[[34113, [0.0833654594998734, 0.08353508100003637, 0.08356363699999747, 0.08354515899998205, 3.387335070499944, 3.505133060999924, 3.4788784925001437, 3.4913442775000476]], [34115, [0.09455199700005323, 0.09418622550003874, 0.09463288750009724, 0.09520090099988465, 3.570233304000112, 3.5546480730001804, 3.521388963999925, 3.5410637559998577]], [34120, [0.08728195200012578, 0.08757731050002349, 0.08587249099991823, 0.09392003099992507, 3.447838260000026, 3.463302648499962, 3.414089462999982, 3.4645014264999645]], [34126, [0.08805573550000645, 0.09336515249992772, 0.09326614400004019, 0.09338562200002798, 3.8056525639999563, 3.7916022399999747, 3.780921758999966, 3.9462397859999783]], [34139, [0.0910075090000646, 0.09174069599998802, 0.0891819395001221, 0.08995108599992818, 3.846621070999845, 3.5285732675000645, 3.4513283095000133, 3.4487890204999303]], [34140, [0.08655621550008163, 0.08683517250005934, 0.08643948100007037, 0.08634586249991116, 3.4394463404998987, 3.4420722634999947, 3.768378994999921, 3.8005554170001687]], [34141, [0.10042238550011007, 0.10036522099994727, 0.08531690399991021, 0.09737879450005948, 3.8029851090000193, 3.8003822919999948, 3.781139291000045, 3.8138180620001094]], [34155, [0.08425936049991378, 0.08396229050003967, 0.08432738199996948, 0.08393404899993584, 3.417569478000132, 3.4067992325000205, 3.791019874000085, 4.038904399499984]], [34158, [0.08556028300006346, 0.0856344444999877, 0.08539509000013368, 0.0849672819999796, 3.620922735499903, 3.5007576754999263, 3.473892105499999, 3.5567585059999374]], [34160, [0.085943648000125, 0.08548283549998814, 0.0850765479999609, 0.08495039299987184, 3.427754016999984, 3.430599270000016, 3.4279369459999316, 3.9524093110001104]], [34162, [0.08551114950000738, 0.0965105099999164, 0.08989807850002762, 0.08715895400007412, 3.557013690000076, 3.784893330000159, 3.774983223000163, 3.7941743950000273]]] \ No newline at end of file +[[34113, [0.0833654594998734, 0.08353508100003637, 0.08356363699999747, 0.08354515899998205, 3.387335070499944, 3.505133060999924, 3.4788784925001437, 3.4913442775000476]], [34115, [0.09455199700005323, 0.09418622550003874, 0.09463288750009724, 0.09520090099988465, 3.570233304000112, 3.5546480730001804, 3.521388963999925, 3.5410637559998577]], [34120, [0.08728195200012578, 0.08757731050002349, 0.08587249099991823, 0.09392003099992507, 3.447838260000026, 3.463302648499962, 3.414089462999982, 3.4645014264999645]], [34126, [0.08805573550000645, 0.09336515249992772, 0.09326614400004019, 0.09338562200002798, 3.8056525639999563, 3.7916022399999747, 3.780921758999966, 3.9462397859999783]], [34139, [0.0910075090000646, 0.09174069599998802, 0.0891819395001221, 0.08995108599992818, 3.846621070999845, 3.5285732675000645, 3.4513283095000133, 3.4487890204999303]], [34140, [0.08655621550008163, 0.08683517250005934, 0.08643948100007037, 0.08634586249991116, 3.4394463404998987, 3.4420722634999947, 3.768378994999921, 3.8005554170001687]], [34141, [0.10042238550011007, 0.10036522099994727, 0.08531690399991021, 0.09737879450005948, 3.8029851090000193, 3.8003822919999948, 3.781139291000045, 3.8138180620001094]], [34155, [0.08425936049991378, 0.08396229050003967, 0.08432738199996948, 0.08393404899993584, 3.417569478000132, 3.4067992325000205, 3.791019874000085, 4.038904399499984]], [34158, [0.08556028300006346, 0.0856344444999877, 0.08539509000013368, 0.0849672819999796, 3.620922735499903, 3.5007576754999263, 3.473892105499999, 3.5567585059999374]], [34160, [0.085943648000125, 0.08548283549998814, 0.0850765479999609, 0.08495039299987184, 3.427754016999984, 3.430599270000016, 3.4279369459999316, 3.9524093110001104]], [34162, [0.08551114950000738, 0.0965105099999164, 0.08989807850002762, 0.08715895400007412, 3.557013690000076, 3.784893330000159, 3.774983223000163, 3.7941743950000273]], [34164, [0.09294014950000928, 0.09321560700004738, 0.0858323184999108, 0.09338695700000699, 4.762329992999867, 5.3345118304999914, 3.829291792000049, 3.850472555000124]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_test_score.json index 0cabd03721..38e279f4fd 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [-4.109886169433594, -3.0753684043884277, -4.1098856925964355, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34115, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34120, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34126, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34139, [-4.109885215759277, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34140, [-4.109885215759277, -3.0753684043884277, -4.109885215759277, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34141, [-4.109885215759277, -3.0753684043884277, -4.1098856925964355, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34155, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34158, [-4.109885215759277, -3.0753684043884277, -4.109885215759277, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34160, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34162, [-4.109885215759277, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]]] \ No newline at end of file +[[34113, [-4.109886169433594, -3.0753684043884277, -4.1098856925964355, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34115, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34120, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34126, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34139, [-4.109885215759277, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34140, [-4.109885215759277, -3.0753684043884277, -4.109885215759277, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34141, [-4.109885215759277, -3.0753684043884277, -4.1098856925964355, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34155, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34158, [-4.109885215759277, -3.0753684043884277, -4.109885215759277, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34160, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34162, [-4.109885215759277, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]], [34164, [-4.109886169433594, -3.0753684043884277, -4.109886169433594, -3.0753684043884277, -0.9266619682312012, -0.9249227643013, -0.9266619682312012, -0.9249262809753418]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json index ccf12f4b74..1209c9847d 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000671386719]], [34115, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34120, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34126, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34139, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34140, [-4.1075520515441895, -3.0780563354492188, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34141, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34155, [-4.1075520515441895, -3.0780563354492188, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34158, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34160, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34162, [-4.1075520515441895, -3.0780563354492188, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]]] \ No newline at end of file +[[34113, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000671386719]], [34115, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34120, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34126, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34139, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34140, [-4.1075520515441895, -3.0780563354492188, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34141, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34155, [-4.1075520515441895, -3.0780563354492188, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34158, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34160, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34162, [-4.1075520515441895, -3.0780563354492188, -4.1075520515441895, -3.0780563354492188, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]], [34164, [-4.1075520515441895, -3.0780560970306396, -4.1075520515441895, -3.0780560970306396, -0.9227071404457092, -0.922096312046051, -0.9227071404457092, -0.9221000075340271]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json index ce2cfdfb22..1efe7dfc22 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [91324416.0, 91865088.0, 174153728.0, 176168960.0]], [34115, [91107328.0, 91463680.0, 174342144.0, 175394816.0]], [34120, [90939392.0, 91299840.0, 173867008.0, 175509504.0]], [34126, [91213824.0, 92327936.0, 174915584.0, 175804416.0]], [34139, [90464256.0, 91455488.0, 174022656.0, 175779840.0]], [34140, [90611712.0, 91308032.0, 173813760.0, 175583232.0]], [34141, [91144192.0, 92172288.0, 174194688.0, 175988736.0]], [34155, [91074560.0, 91594752.0, 173858816.0, 175554560.0]], [34158, [90861568.0, 91521024.0, 173658112.0, 175136768.0]], [34160, [90771456.0, 91226112.0, 174039040.0, 175333376.0]], [34162, [90836992.0, 91770880.0, 173801472.0, 175472640.0]]] \ No newline at end of file +[[34113, [91324416.0, 91865088.0, 174153728.0, 176168960.0]], [34115, [91107328.0, 91463680.0, 174342144.0, 175394816.0]], [34120, [90939392.0, 91299840.0, 173867008.0, 175509504.0]], [34126, [91213824.0, 92327936.0, 174915584.0, 175804416.0]], [34139, [90464256.0, 91455488.0, 174022656.0, 175779840.0]], [34140, [90611712.0, 91308032.0, 173813760.0, 175583232.0]], [34141, [91144192.0, 92172288.0, 174194688.0, 175988736.0]], [34155, [91074560.0, 91594752.0, 173858816.0, 175554560.0]], [34158, [90861568.0, 91521024.0, 173658112.0, 175136768.0]], [34160, [90771456.0, 91226112.0, 174039040.0, 175333376.0]], [34162, [90836992.0, 91770880.0, 173801472.0, 175472640.0]], [34164, [90583040.0, 91467776.0, 173826048.0, 175595520.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json index 239362da34..3e5b2e5f0e 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [88219648.0, 88223744.0, 103505920.0, 103505920.0]], [34115, [87908352.0, 87912448.0, 103174144.0, 103178240.0]], [34120, [88084480.0, 88076288.0, 103292928.0, 103292928.0]], [34126, [88588288.0, 88588288.0, 103833600.0, 103833600.0]], [34139, [88100864.0, 88100864.0, 103448576.0, 103448576.0]], [34140, [87683072.0, 87683072.0, 102907904.0, 102907904.0]], [34141, [88408064.0, 88395776.0, 103628800.0, 103628800.0]], [34155, [88145920.0, 88145920.0, 103415808.0, 103415808.0]], [34158, [88256512.0, 87408640.0, 103079936.0, 103079936.0]], [34160, [88215552.0, 88211456.0, 103399424.0, 103399424.0]], [34162, [87990272.0, 87990272.0, 103206912.0, 103206912.0]]] \ No newline at end of file +[[34113, [88219648.0, 88223744.0, 103505920.0, 103505920.0]], [34115, [87908352.0, 87912448.0, 103174144.0, 103178240.0]], [34120, [88084480.0, 88076288.0, 103292928.0, 103292928.0]], [34126, [88588288.0, 88588288.0, 103833600.0, 103833600.0]], [34139, [88100864.0, 88100864.0, 103448576.0, 103448576.0]], [34140, [87683072.0, 87683072.0, 102907904.0, 102907904.0]], [34141, [88408064.0, 88395776.0, 103628800.0, 103628800.0]], [34155, [88145920.0, 88145920.0, 103415808.0, 103415808.0]], [34158, [88256512.0, 87408640.0, 103079936.0, 103079936.0]], [34160, [88215552.0, 88211456.0, 103399424.0, 103399424.0]], [34162, [87990272.0, 87990272.0, 103206912.0, 103206912.0]], [34164, [87965696.0, 87965696.0, 103280640.0, 103280640.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json index 67c6300622..3541733fc8 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json @@ -1 +1 @@ -[[34113, [119123968.0, 119123968.0, 124329984.0, 124329984.0]], [34115, [118992896.0, 118980608.0, 123908096.0, 123973632.0]], [34120, [118992896.0, 119058432.0, 124153856.0, 124149760.0]], [34126, [119345152.0, 119353344.0, 124170240.0, 124166144.0]], [34139, [119091200.0, 119095296.0, 124256256.0, 124256256.0]], [34140, [118571008.0, 118591488.0, 123826176.0, 123826176.0]], [34141, [119373824.0, 119373824.0, 124502016.0, 124502016.0]], [34155, [119070720.0, 119050240.0, 124137472.0, 124133376.0]], [34158, [118812672.0, 118829056.0, 123985920.0, 123985920.0]], [34160, [118865920.0, 118853632.0, 123957248.0, 123961344.0]], [34162, [119115776.0, 119115776.0, 124026880.0, 124030976.0]]] \ No newline at end of file +[[34113, [119123968.0, 119123968.0, 124329984.0, 124329984.0]], [34115, [118992896.0, 118980608.0, 123908096.0, 123973632.0]], [34120, [118992896.0, 119058432.0, 124153856.0, 124149760.0]], [34126, [119345152.0, 119353344.0, 124170240.0, 124166144.0]], [34139, [119091200.0, 119095296.0, 124256256.0, 124256256.0]], [34140, [118571008.0, 118591488.0, 123826176.0, 123826176.0]], [34141, [119373824.0, 119373824.0, 124502016.0, 124502016.0]], [34155, [119070720.0, 119050240.0, 124137472.0, 124133376.0]], [34158, [118812672.0, 118829056.0, 123985920.0, 123985920.0]], [34160, [118865920.0, 118853632.0, 123957248.0, 123961344.0]], [34162, [119115776.0, 119115776.0, 124026880.0, 124030976.0]], [34164, [118808576.0, 118792192.0, 124051456.0, 124071936.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_fit.json index 5b6d7301f7..86777464aa 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [0.46602164799969614, 0.49536073599983865, 0.5846232459998646, 1.663407598000049]], [34115, [0.4856757799999514, 0.49751224899989666, 0.6201266324999324, 1.5863794399999733]], [34120, [0.47880918050009313, 0.4762677090000125, 0.6025239899998951, 1.6294973684999832]], [34126, [0.4785985524999887, 0.4876799360001769, 0.6209414644999924, 1.7354764649999197]], [34139, [0.482226503999982, 0.49163170099996023, 0.5264462005000041, 1.6905401430001348]], [34140, [0.47225738999998157, 0.47993858600011663, 0.5229153830000541, 1.6444899804999977]], [34141, [0.4828302959999746, 0.4968368579999378, 0.6216662439999254, 1.9575393630001372]], [34155, [0.46637852000003477, 0.47735968499989667, 0.6256276409999373, 1.676478144000157]], [34158, [0.47048185999983616, 0.4604938970001058, 0.5981123765001257, 1.6373085924999486]], [34160, [0.4834566404999805, 0.48150149399998554, 0.5257019330000503, 1.61000256549994]], [34162, [0.4649942179999016, 0.49264625699993303, 0.6225619635000612, 1.6860210610000195]]] \ No newline at end of file +[[34113, [0.46602164799969614, 0.49536073599983865, 0.5846232459998646, 1.663407598000049]], [34115, [0.4856757799999514, 0.49751224899989666, 0.6201266324999324, 1.5863794399999733]], [34120, [0.47880918050009313, 0.4762677090000125, 0.6025239899998951, 1.6294973684999832]], [34126, [0.4785985524999887, 0.4876799360001769, 0.6209414644999924, 1.7354764649999197]], [34139, [0.482226503999982, 0.49163170099996023, 0.5264462005000041, 1.6905401430001348]], [34140, [0.47225738999998157, 0.47993858600011663, 0.5229153830000541, 1.6444899804999977]], [34141, [0.4828302959999746, 0.4968368579999378, 0.6216662439999254, 1.9575393630001372]], [34155, [0.46637852000003477, 0.47735968499989667, 0.6256276409999373, 1.676478144000157]], [34158, [0.47048185999983616, 0.4604938970001058, 0.5981123765001257, 1.6373085924999486]], [34160, [0.4834566404999805, 0.48150149399998554, 0.5257019330000503, 1.61000256549994]], [34162, [0.4649942179999016, 0.49264625699993303, 0.6225619635000612, 1.6860210610000195]], [34164, [0.47748156400007247, 0.4643983199999866, 0.6232942630001617, 1.5916668449999634]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_predict.json index 2760198564..7cdd846c4c 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.006257542499952251, 0.008202626499951293, 0.02397731949986337, 0.036613891500110185]], [34115, [0.00604414600002201, 0.005378256999961195, 0.029767887000048177, 0.026969365000013568]], [34120, [0.005156626500024686, 0.005332433999967634, 0.03916341450008076, 0.03923153450000427]], [34126, [0.005320993749990066, 0.0064018754999892735, 0.0351604634998921, 0.037514384500013875]], [34139, [0.005413440500035449, 0.005349425000019892, 0.037052692999964165, 0.029411965500003134]], [34140, [0.005424535750023551, 0.005641895250050766, 0.0334678785000051, 0.037357234500063896]], [34141, [0.005128722000051766, 0.005341644000054657, 0.030278876500005936, 0.030793920500059357]], [34155, [0.0064357035000739415, 0.005208551250007076, 0.03596673099991676, 0.01998188050004046]], [34158, [0.0053397412500544306, 0.0077771875000394175, 0.03675511300002654, 0.036925888000041596]], [34160, [0.00507963075006046, 0.005033587000013995, 0.036238207999986116, 0.03650498549995973]], [34162, [0.0059974229999966155, 0.005518245000018851, 0.03770441950007353, 0.03585086149996641]]] \ No newline at end of file +[[34113, [0.006257542499952251, 0.008202626499951293, 0.02397731949986337, 0.036613891500110185]], [34115, [0.00604414600002201, 0.005378256999961195, 0.029767887000048177, 0.026969365000013568]], [34120, [0.005156626500024686, 0.005332433999967634, 0.03916341450008076, 0.03923153450000427]], [34126, [0.005320993749990066, 0.0064018754999892735, 0.0351604634998921, 0.037514384500013875]], [34139, [0.005413440500035449, 0.005349425000019892, 0.037052692999964165, 0.029411965500003134]], [34140, [0.005424535750023551, 0.005641895250050766, 0.0334678785000051, 0.037357234500063896]], [34141, [0.005128722000051766, 0.005341644000054657, 0.030278876500005936, 0.030793920500059357]], [34155, [0.0064357035000739415, 0.005208551250007076, 0.03596673099991676, 0.01998188050004046]], [34158, [0.0053397412500544306, 0.0077771875000394175, 0.03675511300002654, 0.036925888000041596]], [34160, [0.00507963075006046, 0.005033587000013995, 0.036238207999986116, 0.03650498549995973]], [34162, [0.0059974229999966155, 0.005518245000018851, 0.03770441950007353, 0.03585086149996641]], [34164, [0.006194317000051797, 0.0053344940000101815, 0.03659826950001843, 0.02401418049998938]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_transform.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_transform.json index 5da9151a61..2b32124b96 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_transform.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_transform.json @@ -1 +1 @@ -[[34113, [0.09475355399990804, 0.09467651600016325, 7.646174094000116, 6.7097862314999475]], [34115, [0.08590339700003824, 0.08543589600003543, 6.912945717499952, 7.094753633499863]], [34120, [0.09267282700000123, 0.09311965299991698, 7.182846978000043, 7.153372103500033]], [34126, [0.0842455519999703, 0.09256515350011796, 7.421811582999908, 7.44758948149979]], [34139, [0.09212016650008081, 0.09232283249991724, 7.005081073999918, 7.448560831500117]], [34140, [0.08541891400000168, 0.08538058950000504, 6.711045524500037, 6.743529992999925]], [34141, [0.09621716000003744, 0.09997491449996687, 7.37141050799994, 6.927716622000048]], [34155, [0.08349271749989384, 0.09257775150001635, 7.423973920500089, 7.383673761000068]], [34158, [0.09090647549999176, 0.08325666249970709, 6.932016940999802, 6.927716938000003]], [34160, [0.09432868950011652, 0.08690997500002595, 7.120454630999916, 7.048526888499964]], [34162, [0.0931850659999327, 0.0942202725000243, 7.044919052999944, 7.475961620000135]]] \ No newline at end of file +[[34113, [0.09475355399990804, 0.09467651600016325, 7.646174094000116, 6.7097862314999475]], [34115, [0.08590339700003824, 0.08543589600003543, 6.912945717499952, 7.094753633499863]], [34120, [0.09267282700000123, 0.09311965299991698, 7.182846978000043, 7.153372103500033]], [34126, [0.0842455519999703, 0.09256515350011796, 7.421811582999908, 7.44758948149979]], [34139, [0.09212016650008081, 0.09232283249991724, 7.005081073999918, 7.448560831500117]], [34140, [0.08541891400000168, 0.08538058950000504, 6.711045524500037, 6.743529992999925]], [34141, [0.09621716000003744, 0.09997491449996687, 7.37141050799994, 6.927716622000048]], [34155, [0.08349271749989384, 0.09257775150001635, 7.423973920500089, 7.383673761000068]], [34158, [0.09090647549999176, 0.08325666249970709, 6.932016940999802, 6.927716938000003]], [34160, [0.09432868950011652, 0.08690997500002595, 7.120454630999916, 7.048526888499964]], [34162, [0.0931850659999327, 0.0942202725000243, 7.044919052999944, 7.475961620000135]], [34164, [0.09233130500001607, 0.08363951249998536, 6.745201981500031, 7.482104948499909]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.track_test_score.json index c9d97b4c2d..2fd1fa025d 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34115, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34120, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34126, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34139, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34140, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34141, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34155, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34158, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34160, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34162, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]]] \ No newline at end of file +[[34113, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34115, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34120, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34126, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34139, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34140, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34141, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34155, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34158, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34160, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34162, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]], [34164, [-4.596621036529541, -3.1085314750671387, -0.9366871118545532, -0.9386959075927734]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.track_train_score.json index 5ac1a6aac0..125b7aa6e7 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34115, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34120, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34126, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34139, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34140, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34141, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34155, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34158, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34160, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34162, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]]] \ No newline at end of file +[[34113, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34115, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34120, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34126, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34139, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34140, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34141, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34155, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34158, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34160, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34162, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]], [34164, [-4.584851264953613, -3.115997314453125, -0.9323447346687317, -0.934399425983429]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.peakmem_fit.json index ba36311b91..ce7a242ec3 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [109555712.0, 130371584.0, 103464960.0, 130412544.0]], [34115, [109285376.0, 130056192.0, 103432192.0, 130240512.0]], [34120, [109006848.0, 129531904.0, 103002112.0, 129896448.0]], [34126, [109572096.0, 130752512.0, 103526400.0, 130842624.0]], [34139, [109101056.0, 130101248.0, 102735872.0, 130125824.0]], [34140, [109133824.0, 129994752.0, 102748160.0, 129536000.0]], [34141, [109625344.0, 130482176.0, 103653376.0, 130408448.0]], [34155, [109166592.0, 129953792.0, 103333888.0, 129978368.0]], [34158, [109260800.0, 130424832.0, 102899712.0, 130285568.0]], [34160, [109158400.0, 130080768.0, 102727680.0, 129904640.0]], [34162, [109486080.0, 130555904.0, 103579648.0, 130580480.0]]] \ No newline at end of file +[[34113, [109555712.0, 130371584.0, 103464960.0, 130412544.0]], [34115, [109285376.0, 130056192.0, 103432192.0, 130240512.0]], [34120, [109006848.0, 129531904.0, 103002112.0, 129896448.0]], [34126, [109572096.0, 130752512.0, 103526400.0, 130842624.0]], [34139, [109101056.0, 130101248.0, 102735872.0, 130125824.0]], [34140, [109133824.0, 129994752.0, 102748160.0, 129536000.0]], [34141, [109625344.0, 130482176.0, 103653376.0, 130408448.0]], [34155, [109166592.0, 129953792.0, 103333888.0, 129978368.0]], [34158, [109260800.0, 130424832.0, 102899712.0, 130285568.0]], [34160, [109158400.0, 130080768.0, 102727680.0, 129904640.0]], [34162, [109486080.0, 130555904.0, 103579648.0, 130580480.0]], [34164, [108994560.0, 129916928.0, 103235584.0, 129921024.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.peakmem_transform.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.peakmem_transform.json index a0ff7b4bf5..64720cd65d 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.peakmem_transform.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.peakmem_transform.json @@ -1 +1 @@ -[[34113, [85090304.0, 87506944.0, 85024768.0, 87506944.0]], [34115, [84971520.0, 87187456.0, 84971520.0, 87187456.0]], [34120, [84971520.0, 86990848.0, 84971520.0, 86990848.0]], [34126, [85250048.0, 87711744.0, 85250048.0, 87711744.0]], [34139, [85176320.0, 87232512.0, 85176320.0, 87220224.0]], [34140, [85016576.0, 86892544.0, 85016576.0, 86904832.0]], [34141, [85295104.0, 87580672.0, 85295104.0, 87584768.0]], [34155, [85159936.0, 87158784.0, 85159936.0, 87158784.0]], [34158, [85037056.0, 87187456.0, 85037056.0, 87187456.0]], [34160, [85078016.0, 87138304.0, 85078016.0, 87138304.0]], [34162, [85172224.0, 87298048.0, 85172224.0, 87298048.0]]] \ No newline at end of file +[[34113, [85090304.0, 87506944.0, 85024768.0, 87506944.0]], [34115, [84971520.0, 87187456.0, 84971520.0, 87187456.0]], [34120, [84971520.0, 86990848.0, 84971520.0, 86990848.0]], [34126, [85250048.0, 87711744.0, 85250048.0, 87711744.0]], [34139, [85176320.0, 87232512.0, 85176320.0, 87220224.0]], [34140, [85016576.0, 86892544.0, 85016576.0, 86904832.0]], [34141, [85295104.0, 87580672.0, 85295104.0, 87584768.0]], [34155, [85159936.0, 87158784.0, 85159936.0, 87158784.0]], [34158, [85037056.0, 87187456.0, 85037056.0, 87187456.0]], [34160, [85078016.0, 87138304.0, 85078016.0, 87138304.0]], [34162, [85172224.0, 87298048.0, 85172224.0, 87298048.0]], [34164, [85037056.0, 87035904.0, 85037056.0, 87035904.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.time_fit.json index 4706849bf3..e0c7b03098 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [16.863959108000017, 9.957476413999757, 0.7593660990000899, 3.1370855995000966]], [34115, [17.88825365699995, 10.355877707999753, 0.7239531720001651, 3.384461490000376]], [34120, [16.708609389999765, 10.029194895999808, 0.760148511999887, 3.4141655670000546]], [34126, [18.255309286999818, 10.113518836999901, 0.8210320800003501, 3.321303674000319]], [34139, [15.510095168000134, 10.399534428999686, 0.7538921509999454, 3.020865740500085]], [34140, [16.264981127000283, 9.891337809000106, 0.7630291519999446, 3.148526891000074]], [34141, [17.26241022999966, 10.611413686000105, 0.7668966350001938, 3.4432743560000745]], [34155, [17.93767726799979, 10.128927592999844, 0.7505443525001283, 3.2455338955001025]], [34158, [18.02690227899984, 11.015035568999792, 0.738772784000048, 3.033447564500193]], [34160, [17.641949392000242, 10.478162156000053, 0.7856478969999898, 3.258001757999864]], [34162, [15.914419851000275, 10.39640817199961, 0.7879794479999873, 3.3552148610001495]]] \ No newline at end of file +[[34113, [16.863959108000017, 9.957476413999757, 0.7593660990000899, 3.1370855995000966]], [34115, [17.88825365699995, 10.355877707999753, 0.7239531720001651, 3.384461490000376]], [34120, [16.708609389999765, 10.029194895999808, 0.760148511999887, 3.4141655670000546]], [34126, [18.255309286999818, 10.113518836999901, 0.8210320800003501, 3.321303674000319]], [34139, [15.510095168000134, 10.399534428999686, 0.7538921509999454, 3.020865740500085]], [34140, [16.264981127000283, 9.891337809000106, 0.7630291519999446, 3.148526891000074]], [34141, [17.26241022999966, 10.611413686000105, 0.7668966350001938, 3.4432743560000745]], [34155, [17.93767726799979, 10.128927592999844, 0.7505443525001283, 3.2455338955001025]], [34158, [18.02690227899984, 11.015035568999792, 0.738772784000048, 3.033447564500193]], [34160, [17.641949392000242, 10.478162156000053, 0.7856478969999898, 3.258001757999864]], [34162, [15.914419851000275, 10.39640817199961, 0.7879794479999873, 3.3552148610001495]], [34164, [18.021907939000357, 9.796838495999964, 0.788294067499919, 3.3651072499999373]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.time_transform.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.time_transform.json index 4e7a9d3c2d..4962fae91d 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.time_transform.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.time_transform.json @@ -1 +1 @@ -[[34113, [0.22562722699990445, 0.3017920620000041, 0.22166306949998216, 0.2915662965001502]], [34115, [0.23449252249997699, 0.2810909615000128, 0.28288762649981436, 0.2845918794998852]], [34120, [0.24836698500030252, 0.28395613500015315, 0.25088606700001037, 0.29159356600007413]], [34126, [0.24351250899985644, 0.27302701100006743, 0.29670905849980045, 0.2932129599998916]], [34139, [0.23603969350006082, 0.2880728459999773, 0.23366790449995278, 0.29205190199991193]], [34140, [0.22448783999993793, 0.29691259550031646, 0.24091829799999687, 0.2920550354999705]], [34141, [0.2988799019999533, 0.3020082090001779, 0.24220178549990123, 0.28489212900012717]], [34155, [0.28859611350003433, 0.3016308150001805, 0.24738869749990045, 0.2906861760002357]], [34158, [0.24741669900004126, 0.29006182349985465, 0.25078159450004023, 0.29904749500019534]], [34160, [0.22578374299973802, 0.29876851600010923, 0.23780536549998033, 0.302154542000153]], [34162, [0.24118274450006538, 0.31003582499988624, 0.26214826050022566, 0.2961199559999841]]] \ No newline at end of file +[[34113, [0.22562722699990445, 0.3017920620000041, 0.22166306949998216, 0.2915662965001502]], [34115, [0.23449252249997699, 0.2810909615000128, 0.28288762649981436, 0.2845918794998852]], [34120, [0.24836698500030252, 0.28395613500015315, 0.25088606700001037, 0.29159356600007413]], [34126, [0.24351250899985644, 0.27302701100006743, 0.29670905849980045, 0.2932129599998916]], [34139, [0.23603969350006082, 0.2880728459999773, 0.23366790449995278, 0.29205190199991193]], [34140, [0.22448783999993793, 0.29691259550031646, 0.24091829799999687, 0.2920550354999705]], [34141, [0.2988799019999533, 0.3020082090001779, 0.24220178549990123, 0.28489212900012717]], [34155, [0.28859611350003433, 0.3016308150001805, 0.24738869749990045, 0.2906861760002357]], [34158, [0.24741669900004126, 0.29006182349985465, 0.25078159450004023, 0.29904749500019534]], [34160, [0.22578374299973802, 0.29876851600010923, 0.23780536549998033, 0.302154542000153]], [34162, [0.24118274450006538, 0.31003582499988624, 0.26214826050022566, 0.2961199559999841]], [34164, [0.23485662950020014, 0.30083740499981104, 0.22825700749990574, 0.2998249140000553]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.track_test_score.json index b4f1cc8284..cf4b131847 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34115, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34120, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34126, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34139, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34140, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34141, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34155, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34158, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34160, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34162, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]]] \ No newline at end of file +[[34113, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34115, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34120, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34126, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34139, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34140, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34141, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34155, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34158, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34160, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34162, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]], [34164, [-0.07475553452968597, -0.07475553452713135, -0.07475554198026657, -0.07475553814463735]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.track_train_score.json index 8ebef5b1b5..0ccec7b14e 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.DictionaryLearningBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34115, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34120, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34126, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34139, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34140, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34141, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34155, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34158, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34160, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34162, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]]] \ No newline at end of file +[[34113, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34115, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34120, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34126, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34139, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34140, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34141, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34155, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34158, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34160, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34162, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]], [34164, [-0.07231885939836502, -0.07231886142463793, -0.07231885939836502, -0.07231886151447059]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json index 1b34206c7f..45d11d2fc9 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [97640448.0, 108470272.0, 97509376.0, 108183552.0]], [34115, [98037760.0, 107118592.0, 97099776.0, 108032000.0]], [34120, [97648640.0, 107876352.0, 97202176.0, 107606016.0]], [34126, [97673216.0, 107184128.0, 97636352.0, 108310528.0]], [34139, [97144832.0, 107974656.0, 97046528.0, 107708416.0]], [34140, [97308672.0, 106622976.0, 97595392.0, 107667456.0]], [34141, [97697792.0, 108441600.0, 97640448.0, 108220416.0]], [34155, [97517568.0, 107982848.0, 97705984.0, 107732992.0]], [34158, [97435648.0, 108294144.0, 97366016.0, 107094016.0]], [34160, [97382400.0, 108032000.0, 97415168.0, 106844160.0]], [34162, [97906688.0, 107245568.0, 97710080.0, 108138496.0]]] \ No newline at end of file +[[34113, [97640448.0, 108470272.0, 97509376.0, 108183552.0]], [34115, [98037760.0, 107118592.0, 97099776.0, 108032000.0]], [34120, [97648640.0, 107876352.0, 97202176.0, 107606016.0]], [34126, [97673216.0, 107184128.0, 97636352.0, 108310528.0]], [34139, [97144832.0, 107974656.0, 97046528.0, 107708416.0]], [34140, [97308672.0, 106622976.0, 97595392.0, 107667456.0]], [34141, [97697792.0, 108441600.0, 97640448.0, 108220416.0]], [34155, [97517568.0, 107982848.0, 97705984.0, 107732992.0]], [34158, [97435648.0, 108294144.0, 97366016.0, 107094016.0]], [34160, [97382400.0, 108032000.0, 97415168.0, 106844160.0]], [34162, [97906688.0, 107245568.0, 97710080.0, 108138496.0]], [34164, [97595392.0, 107827200.0, 97509376.0, 107610112.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json index 2c24d19b8d..66ef4729e4 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json @@ -1 +1 @@ -[[34113, [86306816.0, 88281088.0, 86192128.0, 88281088.0]], [34115, [86179840.0, 88018944.0, 86073344.0, 88018944.0]], [34120, [86085632.0, 87744512.0, 85979136.0, 87744512.0]], [34126, [86462464.0, 88567808.0, 86351872.0, 88551424.0]], [34139, [86315008.0, 87965696.0, 86126592.0, 87961600.0]], [34140, [85897216.0, 87650304.0, 85958656.0, 87650304.0]], [34141, [86454272.0, 88358912.0, 86335488.0, 88358912.0]], [34155, [86335488.0, 87908352.0, 86175744.0, 87908352.0]], [34158, [86224896.0, 88027136.0, 86011904.0, 88027136.0]], [34160, [86159360.0, 87887872.0, 85958656.0, 87887872.0]], [34162, [86327296.0, 88129536.0, 86147072.0, 88129536.0]]] \ No newline at end of file +[[34113, [86306816.0, 88281088.0, 86192128.0, 88281088.0]], [34115, [86179840.0, 88018944.0, 86073344.0, 88018944.0]], [34120, [86085632.0, 87744512.0, 85979136.0, 87744512.0]], [34126, [86462464.0, 88567808.0, 86351872.0, 88551424.0]], [34139, [86315008.0, 87965696.0, 86126592.0, 87961600.0]], [34140, [85897216.0, 87650304.0, 85958656.0, 87650304.0]], [34141, [86454272.0, 88358912.0, 86335488.0, 88358912.0]], [34155, [86335488.0, 87908352.0, 86175744.0, 87908352.0]], [34158, [86224896.0, 88027136.0, 86011904.0, 88027136.0]], [34160, [86159360.0, 87887872.0, 85958656.0, 87887872.0]], [34162, [86327296.0, 88129536.0, 86147072.0, 88129536.0]], [34164, [86188032.0, 87785472.0, 85987328.0, 87781376.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json index fb39eccb1e..540b5dfeae 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [10.278902363999805, 17.81125016099986, 3.0049109685000985, 20.003798924999955]], [34115, [10.942894361000072, 20.521345728999677, 3.0408156544999656, 18.662708792000103]], [34120, [11.643599353999889, 21.848660600999665, 3.0803943260002598, 19.35254050200001]], [34126, [11.759634247000122, 21.117197495000255, 3.1037892630001807, 17.82164057099999]], [34139, [11.192596227000195, 19.055224494999948, 3.21538228899999, 19.679745584000102]], [34140, [10.678223337999952, 22.562457605000418, 3.048900023999977, 18.712739478999993]], [34141, [10.985714807000022, 21.288947729999563, 3.21961655899986, 20.471603603999938]], [34155, [10.603525870999874, 20.457598145000247, 3.0303118039998935, 17.674937408999995]], [34158, [10.3805415060001, 18.30381863499997, 3.1605699839997214, 20.248392609999883]], [34160, [10.544752687000255, 17.782455906999985, 3.030441095499782, 16.70915287700018]], [34162, [10.524889747000088, 18.625950976999775, 3.080503712499876, 17.60100341799989]]] \ No newline at end of file +[[34113, [10.278902363999805, 17.81125016099986, 3.0049109685000985, 20.003798924999955]], [34115, [10.942894361000072, 20.521345728999677, 3.0408156544999656, 18.662708792000103]], [34120, [11.643599353999889, 21.848660600999665, 3.0803943260002598, 19.35254050200001]], [34126, [11.759634247000122, 21.117197495000255, 3.1037892630001807, 17.82164057099999]], [34139, [11.192596227000195, 19.055224494999948, 3.21538228899999, 19.679745584000102]], [34140, [10.678223337999952, 22.562457605000418, 3.048900023999977, 18.712739478999993]], [34141, [10.985714807000022, 21.288947729999563, 3.21961655899986, 20.471603603999938]], [34155, [10.603525870999874, 20.457598145000247, 3.0303118039998935, 17.674937408999995]], [34158, [10.3805415060001, 18.30381863499997, 3.1605699839997214, 20.248392609999883]], [34160, [10.544752687000255, 17.782455906999985, 3.030441095499782, 16.70915287700018]], [34162, [10.524889747000088, 18.625950976999775, 3.080503712499876, 17.60100341799989]], [34164, [11.195334200000161, 21.436233222000283, 3.033676102500067, 19.641946082999766]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json index 024e862254..8d3fede1d3 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json @@ -1 +1 @@ -[[34113, [0.21936002150005152, 0.30340672600004837, 0.22705053549975673, 0.2967285885001729]], [34115, [0.25488355449988376, 0.2980023559998699, 0.244140449500037, 0.3020705970000108]], [34120, [0.24916579450018617, 0.27482116699979997, 0.23907773949986222, 0.302260558999933]], [34126, [0.24539044099969942, 0.3009983940000893, 0.2505660945000727, 0.300423385999693]], [34139, [0.22393840299992007, 0.30034285399960936, 0.22955045300000165, 0.301076135500125]], [34140, [0.2204806089998783, 0.28774454950007566, 0.22025028250004652, 0.28289440349999495]], [34141, [0.24431915399986792, 0.3037751249999019, 0.254274256500139, 0.3025140120000742]], [34155, [0.2508273045000351, 0.3044691619998048, 0.25143443899992235, 0.29593346600017867]], [34158, [0.2381800010000461, 0.2950735529998383, 0.26532198499990045, 0.2987929509999958]], [34160, [0.22599147749997428, 0.2905798220003817, 0.2251219269996909, 0.29219981800019923]], [34162, [0.22999483400008103, 0.3070665509999344, 0.2236103264999656, 0.30262822500003494]]] \ No newline at end of file +[[34113, [0.21936002150005152, 0.30340672600004837, 0.22705053549975673, 0.2967285885001729]], [34115, [0.25488355449988376, 0.2980023559998699, 0.244140449500037, 0.3020705970000108]], [34120, [0.24916579450018617, 0.27482116699979997, 0.23907773949986222, 0.302260558999933]], [34126, [0.24539044099969942, 0.3009983940000893, 0.2505660945000727, 0.300423385999693]], [34139, [0.22393840299992007, 0.30034285399960936, 0.22955045300000165, 0.301076135500125]], [34140, [0.2204806089998783, 0.28774454950007566, 0.22025028250004652, 0.28289440349999495]], [34141, [0.24431915399986792, 0.3037751249999019, 0.254274256500139, 0.3025140120000742]], [34155, [0.2508273045000351, 0.3044691619998048, 0.25143443899992235, 0.29593346600017867]], [34158, [0.2381800010000461, 0.2950735529998383, 0.26532198499990045, 0.2987929509999958]], [34160, [0.22599147749997428, 0.2905798220003817, 0.2251219269996909, 0.29219981800019923]], [34162, [0.22999483400008103, 0.3070665509999344, 0.2236103264999656, 0.30262822500003494]], [34164, [0.23348975750036516, 0.3011397499999475, 0.23203592250001748, 0.30503979800005254]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json index 015b50c522..2a68b6a085 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34115, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34120, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34126, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34139, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34140, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34141, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34155, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34158, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34160, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34162, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]]] \ No newline at end of file +[[34113, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34115, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34120, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34126, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34139, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34140, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34141, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34155, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34158, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34160, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34162, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]], [34164, [-0.07506909221410751, -0.0750688759007175, -0.0750984251499176, -0.07509369093642158]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json index c507c584fc..bce2c56ea9 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34115, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34120, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34126, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34139, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34140, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34141, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34155, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34158, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34160, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34162, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]]] \ No newline at end of file +[[34113, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34115, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34120, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34126, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34139, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34140, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34141, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34155, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34158, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34160, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34162, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]], [34164, [-0.07244396954774857, -0.072444055250929, -0.07244586199522018, -0.07244519704497496]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.peakmem_fit.json index 759546ffc2..af953831c7 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [907702272.0, 605138944.0, 622297088.0]], [34115, [908111872.0, 605319168.0, 631824384.0]], [34120, [906477568.0, 604946432.0, 632209408.0]], [34126, [906641408.0, 605171712.0, 632680448.0]], [34139, [908226560.0, 604737536.0, 631857152.0]], [34140, [907751424.0, 604979200.0, 631795712.0]], [34141, [907132928.0, 605249536.0, 632393728.0]], [34155, [907649024.0, 604856320.0, 631967744.0]], [34158, [906563584.0, 605171712.0, 632221696.0]], [34160, [906682368.0, 604790784.0, 631975936.0]], [34162, [907452416.0, 605298688.0, 632299520.0]]] \ No newline at end of file +[[34113, [907702272.0, 605138944.0, 622297088.0]], [34115, [908111872.0, 605319168.0, 631824384.0]], [34120, [906477568.0, 604946432.0, 632209408.0]], [34126, [906641408.0, 605171712.0, 632680448.0]], [34139, [908226560.0, 604737536.0, 631857152.0]], [34140, [907751424.0, 604979200.0, 631795712.0]], [34141, [907132928.0, 605249536.0, 632393728.0]], [34155, [907649024.0, 604856320.0, 631967744.0]], [34158, [906563584.0, 605171712.0, 632221696.0]], [34160, [906682368.0, 604790784.0, 631975936.0]], [34162, [907452416.0, 605298688.0, 632299520.0]], [34164, [907489280.0, 604741632.0, 631640064.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.peakmem_transform.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.peakmem_transform.json index bf9b319131..8eced4c875 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.peakmem_transform.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.peakmem_transform.json @@ -1 +1 @@ -[[34113, [583139328.0, 582873088.0, 582852608.0]], [34115, [582893568.0, 582742016.0, 583057408.0]], [34120, [582430720.0, 582905856.0, 582639616.0]], [34126, [582782976.0, 582938624.0, 582836224.0]], [34139, [582631424.0, 582778880.0, 582979584.0]], [34140, [582496256.0, 582647808.0, 582254592.0]], [34141, [582959104.0, 583049216.0, 583307264.0]], [34155, [582324224.0, 582705152.0, 582647808.0]], [34158, [582627328.0, 582541312.0, 582692864.0]], [34160, [583077888.0, 582778880.0, 582606848.0]], [34162, [582991872.0, 582762496.0, 582823936.0]]] \ No newline at end of file +[[34113, [583139328.0, 582873088.0, 582852608.0]], [34115, [582893568.0, 582742016.0, 583057408.0]], [34120, [582430720.0, 582905856.0, 582639616.0]], [34126, [582782976.0, 582938624.0, 582836224.0]], [34139, [582631424.0, 582778880.0, 582979584.0]], [34140, [582496256.0, 582647808.0, 582254592.0]], [34141, [582959104.0, 583049216.0, 583307264.0]], [34155, [582324224.0, 582705152.0, 582647808.0]], [34158, [582627328.0, 582541312.0, 582692864.0]], [34160, [583077888.0, 582778880.0, 582606848.0]], [34162, [582991872.0, 582762496.0, 582823936.0]], [34164, [582590464.0, 582508544.0, 582238208.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.time_fit.json index 49043cf4b1..9d67b7c826 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [2.5344614550003826, 1.1216455670000869, 1.1282506094996734]], [34115, [2.549508699999933, 1.1206456965001053, 1.1301036924999153]], [34120, [2.521436789999825, 1.1083389884997814, 1.0749521859997913]], [34126, [2.4590610279997236, 1.1125587534997976, 1.096222490000173]], [34139, [2.4785882310002307, 1.1233270845000334, 1.1123904684998251]], [34140, [2.456096704999709, 1.116302130000122, 1.0941048849999788]], [34141, [2.5385982340003466, 1.0867538900001819, 1.1184209424998244]], [34155, [2.445017814000039, 1.0961094839999532, 1.0825815540001713]], [34158, [2.5478048320001108, 1.1210688845001187, 1.0953287855002145]], [34160, [2.4602960540000822, 1.0975781189999907, 1.075519708000229]], [34162, [2.480745754000054, 1.100578485999904, 1.0813159080000787]]] \ No newline at end of file +[[34113, [2.5344614550003826, 1.1216455670000869, 1.1282506094996734]], [34115, [2.549508699999933, 1.1206456965001053, 1.1301036924999153]], [34120, [2.521436789999825, 1.1083389884997814, 1.0749521859997913]], [34126, [2.4590610279997236, 1.1125587534997976, 1.096222490000173]], [34139, [2.4785882310002307, 1.1233270845000334, 1.1123904684998251]], [34140, [2.456096704999709, 1.116302130000122, 1.0941048849999788]], [34141, [2.5385982340003466, 1.0867538900001819, 1.1184209424998244]], [34155, [2.445017814000039, 1.0961094839999532, 1.0825815540001713]], [34158, [2.5478048320001108, 1.1210688845001187, 1.0953287855002145]], [34160, [2.4602960540000822, 1.0975781189999907, 1.075519708000229]], [34162, [2.480745754000054, 1.100578485999904, 1.0813159080000787]], [34164, [2.4394728550000764, 1.0926944279999589, 1.121318427499773]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.time_transform.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.time_transform.json index 57c745ef3f..2e7244c54a 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.time_transform.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.time_transform.json @@ -1 +1 @@ -[[34113, [0.16096080550005354, 0.1604534914999931, 0.16147806050003055]], [34115, [0.1561906199999612, 0.15565533700009837, 0.15863474200000383]], [34120, [0.1564785610000854, 0.15827015149989165, 0.1576623619998827]], [34126, [0.163766948500097, 0.16377916100009315, 0.1583692549997977]], [34139, [0.15564640950015018, 0.15749349199995777, 0.16059154299978218]], [34140, [0.15601904100003594, 0.16050076099986654, 0.16023792500004674]], [34141, [0.16193340999984684, 0.15678125099998397, 0.15918615350005894]], [34155, [0.16250465799998892, 0.15675171450016023, 0.1565621579998151]], [34158, [0.1595982515000287, 0.1612489784997706, 0.1600804515001073]], [34160, [0.15832245249998778, 0.15858034300003965, 0.1647011064999333]], [34162, [0.15654644300002474, 0.15872943849990406, 0.16309884099996452]]] \ No newline at end of file +[[34113, [0.16096080550005354, 0.1604534914999931, 0.16147806050003055]], [34115, [0.1561906199999612, 0.15565533700009837, 0.15863474200000383]], [34120, [0.1564785610000854, 0.15827015149989165, 0.1576623619998827]], [34126, [0.163766948500097, 0.16377916100009315, 0.1583692549997977]], [34139, [0.15564640950015018, 0.15749349199995777, 0.16059154299978218]], [34140, [0.15601904100003594, 0.16050076099986654, 0.16023792500004674]], [34141, [0.16193340999984684, 0.15678125099998397, 0.15918615350005894]], [34155, [0.16250465799998892, 0.15675171450016023, 0.1565621579998151]], [34158, [0.1595982515000287, 0.1612489784997706, 0.1600804515001073]], [34160, [0.15832245249998778, 0.15858034300003965, 0.1647011064999333]], [34162, [0.15654644300002474, 0.15872943849990406, 0.16309884099996452]], [34164, [0.16068778799990469, 0.15615487000013673, 0.16022983500010923]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.track_test_score.json index e77bac6b11..1bce7d87bd 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34115, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34120, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34126, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34139, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34140, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34141, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34155, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34158, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34160, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34162, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]]] \ No newline at end of file +[[34113, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34115, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34120, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34126, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34139, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34140, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34141, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34155, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34158, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34160, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34162, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]], [34164, [0.7449418902397156, 0.7449416518211365, 0.7449308037757874]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.track_train_score.json index 9ce4cd10bd..421550448c 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34115, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34120, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34126, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34139, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34140, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34141, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34155, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34158, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34160, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34162, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]]] \ No newline at end of file +[[34113, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34115, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34120, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34126, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34139, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34140, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34141, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34155, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34158, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34160, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34162, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]], [34164, [0.7445708513259888, 0.7445658445358276, 0.7445555329322815]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json index 3820db71d3..c91748fd8a 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [92717056.0, 116801536.0]], [34115, [92385280.0, 116486144.0]], [34120, [92549120.0, 116740096.0]], [34126, [92704768.0, 116854784.0]], [34139, [92753920.0, 116846592.0]], [34140, [92364800.0, 116436992.0]], [34141, [92782592.0, 116924416.0]], [34155, [92762112.0, 116838400.0]], [34158, [92569600.0, 116572160.0]], [34160, [91000832.0, 116596736.0]], [34162, [91279360.0, 116699136.0]]] \ No newline at end of file +[[34113, [92717056.0, 116801536.0]], [34115, [92385280.0, 116486144.0]], [34120, [92549120.0, 116740096.0]], [34126, [92704768.0, 116854784.0]], [34139, [92753920.0, 116846592.0]], [34140, [92364800.0, 116436992.0]], [34141, [92782592.0, 116924416.0]], [34155, [92762112.0, 116838400.0]], [34158, [92569600.0, 116572160.0]], [34160, [91000832.0, 116596736.0]], [34162, [91279360.0, 116699136.0]], [34164, [91164672.0, 116969472.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json index 7d8b6ab7f2..e19074079b 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [88731648.0, 98676736.0]], [34115, [88768512.0, 98406400.0]], [34120, [88788992.0, 98451456.0]], [34126, [89047040.0, 98693120.0]], [34139, [88825856.0, 98451456.0]], [34140, [88547328.0, 98181120.0]], [34141, [89116672.0, 98762752.0]], [34155, [88870912.0, 98504704.0]], [34158, [88735744.0, 98369536.0]], [34160, [88735744.0, 98365440.0]], [34162, [88780800.0, 98435072.0]]] \ No newline at end of file +[[34113, [88731648.0, 98676736.0]], [34115, [88768512.0, 98406400.0]], [34120, [88788992.0, 98451456.0]], [34126, [89047040.0, 98693120.0]], [34139, [88825856.0, 98451456.0]], [34140, [88547328.0, 98181120.0]], [34141, [89116672.0, 98762752.0]], [34155, [88870912.0, 98504704.0]], [34158, [88735744.0, 98369536.0]], [34160, [88735744.0, 98365440.0]], [34162, [88780800.0, 98435072.0]], [34164, [88793088.0, 98426880.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.time_fit.json index 6304b9c3c7..2341dd755a 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [2.7723530729999766, 2.4561092534997897]], [34115, [2.7972221055001683, 2.236694880000414]], [34120, [2.8581781809998574, 2.3060040135001145]], [34126, [2.781807273500135, 2.318331097499822]], [34139, [3.094916280000234, 2.2614375369998925]], [34140, [2.7866730430000644, 2.477774012500049]], [34141, [2.7623300440000094, 2.3173976569999013]], [34155, [2.8655262935001247, 2.2923448010001266]], [34158, [2.8014932509997834, 2.2305168039997625]], [34160, [2.7702543259997583, 2.463514964000069]], [34162, [3.1671906420001505, 2.3063645810000253]]] \ No newline at end of file +[[34113, [2.7723530729999766, 2.4561092534997897]], [34115, [2.7972221055001683, 2.236694880000414]], [34120, [2.8581781809998574, 2.3060040135001145]], [34126, [2.781807273500135, 2.318331097499822]], [34139, [3.094916280000234, 2.2614375369998925]], [34140, [2.7866730430000644, 2.477774012500049]], [34141, [2.7623300440000094, 2.3173976569999013]], [34155, [2.8655262935001247, 2.2923448010001266]], [34158, [2.8014932509997834, 2.2305168039997625]], [34160, [2.7702543259997583, 2.463514964000069]], [34162, [3.1671906420001505, 2.3063645810000253]], [34164, [2.8024476734999553, 2.230259036999996]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.time_predict.json index 7e3c9ab0a5..ddc62b1780 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.04323960950000583, 0.04730742950005151]], [34115, [0.04957913949988324, 0.04525440849988627]], [34120, [0.046732778999967195, 0.04620476750005764]], [34126, [0.0440122084999075, 0.04498867249981231]], [34139, [0.049097066000058476, 0.0466856689999986]], [34140, [0.04552267949998168, 0.0475306719999935]], [34141, [0.04966457399996216, 0.04219663099979698]], [34155, [0.04544437250001465, 0.042533135499979835]], [34158, [0.04541657699996904, 0.04231454750015473]], [34160, [0.04969014049993348, 0.046675294499891606]], [34162, [0.05024331749996236, 0.04161820550007178]]] \ No newline at end of file +[[34113, [0.04323960950000583, 0.04730742950005151]], [34115, [0.04957913949988324, 0.04525440849988627]], [34120, [0.046732778999967195, 0.04620476750005764]], [34126, [0.0440122084999075, 0.04498867249981231]], [34139, [0.049097066000058476, 0.0466856689999986]], [34140, [0.04552267949998168, 0.0475306719999935]], [34141, [0.04966457399996216, 0.04219663099979698]], [34155, [0.04544437250001465, 0.042533135499979835]], [34158, [0.04541657699996904, 0.04231454750015473]], [34160, [0.04969014049993348, 0.046675294499891606]], [34162, [0.05024331749996236, 0.04161820550007178]], [34164, [0.04937785099991743, 0.04594007900004726]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.track_test_score.json index 450da54e7a..ebc0f8a2a8 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.550023128549654, 0.10409974329281042]], [34115, [0.5379757333329528, 0.10409974329281042]], [34120, [0.5451685329292877, 0.10409974329281042]], [34126, [0.5487050558621032, 0.10409974329281042]], [34139, [0.5413671702284087, 0.10409974329281042]], [34140, [0.5505971636610227, 0.10409974329281042]], [34141, [0.5404085822588184, 0.10409974329281042]], [34155, [0.5540723644183304, 0.10409974329281042]], [34158, [0.5478068325552989, 0.10409974329281042]], [34160, [0.5575723057121493, 0.10409974329281042]], [34162, [0.5388832280278022, 0.10409974329281042]]] \ No newline at end of file +[[34113, [0.550023128549654, 0.10409974329281042]], [34115, [0.5379757333329528, 0.10409974329281042]], [34120, [0.5451685329292877, 0.10409974329281042]], [34126, [0.5487050558621032, 0.10409974329281042]], [34139, [0.5413671702284087, 0.10409974329281042]], [34140, [0.5505971636610227, 0.10409974329281042]], [34141, [0.5404085822588184, 0.10409974329281042]], [34155, [0.5540723644183304, 0.10409974329281042]], [34158, [0.5478068325552989, 0.10409974329281042]], [34160, [0.5575723057121493, 0.10409974329281042]], [34162, [0.5388832280278022, 0.10409974329281042]], [34164, [0.5542371517925532, 0.10409974329281042]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.track_train_score.json index 645ad63295..d5e339d59c 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.6304699471453126, 0.15180008167538628]], [34115, [0.6257717335717553, 0.15180008167538628]], [34120, [0.6217883740208758, 0.15180008167538628]], [34126, [0.6250799297386578, 0.15180008167538628]], [34139, [0.6343881833417756, 0.15180008167538628]], [34140, [0.6296514176013915, 0.15180008167538628]], [34141, [0.6312666388096332, 0.15180008167538628]], [34155, [0.6230917284231469, 0.15180008167538628]], [34158, [0.6296236099833925, 0.15180008167538628]], [34160, [0.6307096759081057, 0.15180008167538628]], [34162, [0.6305939680167932, 0.15180008167538628]]] \ No newline at end of file +[[34113, [0.6304699471453126, 0.15180008167538628]], [34115, [0.6257717335717553, 0.15180008167538628]], [34120, [0.6217883740208758, 0.15180008167538628]], [34126, [0.6250799297386578, 0.15180008167538628]], [34139, [0.6343881833417756, 0.15180008167538628]], [34140, [0.6296514176013915, 0.15180008167538628]], [34141, [0.6312666388096332, 0.15180008167538628]], [34155, [0.6230917284231469, 0.15180008167538628]], [34158, [0.6296236099833925, 0.15180008167538628]], [34160, [0.6307096759081057, 0.15180008167538628]], [34162, [0.6305939680167932, 0.15180008167538628]], [34164, [0.6330727844153277, 0.15180008167538628]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit.json index fd9ec7f8db..0a0dde5bc8 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, 103030784.0], [34115, 102924288.0], [34120, 102899712.0], [34126, 103399424.0], [34139, 102875136.0], [34140, 102612992.0], [34141, 102993920.0], [34155, 102854656.0], [34158, 102883328.0], [34160, 102764544.0], [34162, 103010304.0]] \ No newline at end of file +[[34113, 103030784.0], [34115, 102924288.0], [34120, 102899712.0], [34126, 103399424.0], [34139, 102875136.0], [34140, 102612992.0], [34141, 102993920.0], [34155, 102854656.0], [34158, 102883328.0], [34160, 102764544.0], [34162, 103010304.0], [34164, 103084032.0]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json index 9f456c272a..27afb8857a 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, 91521024.0], [34115, 90980352.0], [34120, 90525696.0], [34126, 91549696.0], [34139, 91324416.0], [34140, 90341376.0], [34141, 91381760.0], [34155, 91303936.0], [34158, 91103232.0], [34160, 91013120.0], [34162, 91062272.0]] \ No newline at end of file +[[34113, 91521024.0], [34115, 90980352.0], [34120, 90525696.0], [34126, 91549696.0], [34139, 91324416.0], [34140, 90341376.0], [34141, 91381760.0], [34155, 91303936.0], [34158, 91103232.0], [34160, 91013120.0], [34162, 91062272.0], [34164, 91148288.0]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json index d1615b1869..b3bdf774e7 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, 2.457242207499803], [34115, 2.4975013709999985], [34120, 2.3545510505000493], [34126, 2.401516767999965], [34139, 2.44353313900001], [34140, 2.4544404060000033], [34141, 2.3755439290000595], [34155, 2.4368824595001115], [34158, 2.343000346500048], [34160, 2.3359379720000106], [34162, 2.4711404590000257]] \ No newline at end of file +[[34113, 2.457242207499803], [34115, 2.4975013709999985], [34120, 2.3545510505000493], [34126, 2.401516767999965], [34139, 2.44353313900001], [34140, 2.4544404060000033], [34141, 2.3755439290000595], [34155, 2.4368824595001115], [34158, 2.343000346500048], [34160, 2.3359379720000106], [34162, 2.4711404590000257], [34164, 2.4061413559998073]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.time_predict.json index 0dfb182ddd..95c0b8e36b 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, 0.08456578100003753], [34115, 0.08634114549977312], [34120, 0.09060399500003768], [34126, 0.08663618550008323], [34139, 0.08268839199990907], [34140, 0.08462493000001814], [34141, 0.0855075530000704], [34155, 0.08763014299984206], [34158, 0.08412637700007508], [34160, 0.08247170899994671], [34162, 0.08514108499980466]] \ No newline at end of file +[[34113, 0.08456578100003753], [34115, 0.08634114549977312], [34120, 0.09060399500003768], [34126, 0.08663618550008323], [34139, 0.08268839199990907], [34140, 0.08462493000001814], [34141, 0.0855075530000704], [34155, 0.08763014299984206], [34158, 0.08412637700007508], [34160, 0.08247170899994671], [34162, 0.08514108499980466], [34164, 0.08461356699990574]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.track_test_score.json index 2fec6a942a..20f0c7cdba 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, 0.7230709112942986], [34115, 0.7230709112942986], [34120, 0.7230709112942986], [34126, 0.7230709112942986], [34139, 0.7230709112942986], [34140, 0.7230709112942986], [34141, 0.7230709112942986], [34155, 0.7230709112942986], [34158, 0.7230709112942986], [34160, 0.7230709112942986], [34162, 0.7230709112942986]] \ No newline at end of file +[[34113, 0.7230709112942986], [34115, 0.7230709112942986], [34120, 0.7230709112942986], [34126, 0.7230709112942986], [34139, 0.7230709112942986], [34140, 0.7230709112942986], [34141, 0.7230709112942986], [34155, 0.7230709112942986], [34158, 0.7230709112942986], [34160, 0.7230709112942986], [34162, 0.7230709112942986], [34164, 0.7230709112942986]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.track_train_score.json index 567b087d99..d1ef66e8a9 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.HistGradientBoostingClassifierBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, 0.9812160155622751], [34115, 0.9812160155622751], [34120, 0.9812160155622751], [34126, 0.9812160155622751], [34139, 0.9812160155622751], [34140, 0.9812160155622751], [34141, 0.9812160155622751], [34155, 0.9812160155622751], [34158, 0.9812160155622751], [34160, 0.9812160155622751], [34162, 0.9812160155622751]] \ No newline at end of file +[[34113, 0.9812160155622751], [34115, 0.9812160155622751], [34120, 0.9812160155622751], [34126, 0.9812160155622751], [34139, 0.9812160155622751], [34140, 0.9812160155622751], [34141, 0.9812160155622751], [34155, 0.9812160155622751], [34158, 0.9812160155622751], [34160, 0.9812160155622751], [34162, 0.9812160155622751], [34164, 0.9812160155622751]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json index a8aa2511c5..f5546707bd 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [179490816.0, 178929664.0, 402763776.0, 402767872.0]], [34115, [179122176.0, 179122176.0, 402472960.0, 402464768.0]], [34120, [179347456.0, 179347456.0, 402436096.0, 402432000.0]], [34126, [179798016.0, 179171328.0, 402997248.0, 402993152.0]], [34139, [178782208.0, 178782208.0, 402427904.0, 402681856.0]], [34140, [179052544.0, 179093504.0, 402333696.0, 402329600.0]], [34141, [178814976.0, 178814976.0, 402751488.0, 402722816.0]], [34155, [178802688.0, 178802688.0, 402464768.0, 402714624.0]], [34158, [179322880.0, 179322880.0, 402587648.0, 402563072.0]], [34160, [178872320.0, 178806784.0, 402530304.0, 402501632.0]], [34162, [179343360.0, 179343360.0, 402644992.0, 402624512.0]]] \ No newline at end of file +[[34113, [179490816.0, 178929664.0, 402763776.0, 402767872.0]], [34115, [179122176.0, 179122176.0, 402472960.0, 402464768.0]], [34120, [179347456.0, 179347456.0, 402436096.0, 402432000.0]], [34126, [179798016.0, 179171328.0, 402997248.0, 402993152.0]], [34139, [178782208.0, 178782208.0, 402427904.0, 402681856.0]], [34140, [179052544.0, 179093504.0, 402333696.0, 402329600.0]], [34141, [178814976.0, 178814976.0, 402751488.0, 402722816.0]], [34155, [178802688.0, 178802688.0, 402464768.0, 402714624.0]], [34158, [179322880.0, 179322880.0, 402587648.0, 402563072.0]], [34160, [178872320.0, 178806784.0, 402530304.0, 402501632.0]], [34162, [179343360.0, 179343360.0, 402644992.0, 402624512.0]], [34164, [178688000.0, 178647040.0, 402300928.0, 402538496.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json index 252b0efbd1..84fa009eae 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [182308864.0, 188870656.0, 402747392.0, 402755584.0]], [34115, [182005760.0, 188579840.0, 402460672.0, 402714624.0]], [34120, [182173696.0, 188592128.0, 402427904.0, 402681856.0]], [34126, [182484992.0, 188997632.0, 402976768.0, 403001344.0]], [34139, [181776384.0, 188231680.0, 402669568.0, 402677760.0]], [34140, [181878784.0, 188493824.0, 402329600.0, 402337792.0]], [34141, [182181888.0, 188727296.0, 402726912.0, 402718720.0]], [34155, [182091776.0, 188461056.0, 402452480.0, 402456576.0]], [34158, [182054912.0, 188620800.0, 402567168.0, 402567168.0]], [34160, [182001664.0, 188448768.0, 402509824.0, 402493440.0]], [34162, [182075392.0, 188628992.0, 402612224.0, 402620416.0]]] \ No newline at end of file +[[34113, [182308864.0, 188870656.0, 402747392.0, 402755584.0]], [34115, [182005760.0, 188579840.0, 402460672.0, 402714624.0]], [34120, [182173696.0, 188592128.0, 402427904.0, 402681856.0]], [34126, [182484992.0, 188997632.0, 402976768.0, 403001344.0]], [34139, [181776384.0, 188231680.0, 402669568.0, 402677760.0]], [34140, [181878784.0, 188493824.0, 402329600.0, 402337792.0]], [34141, [182181888.0, 188727296.0, 402726912.0, 402718720.0]], [34155, [182091776.0, 188461056.0, 402452480.0, 402456576.0]], [34158, [182054912.0, 188620800.0, 402567168.0, 402567168.0]], [34160, [182001664.0, 188448768.0, 402509824.0, 402493440.0]], [34162, [182075392.0, 188628992.0, 402612224.0, 402620416.0]], [34164, [181596160.0, 188043264.0, 402296832.0, 402522112.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_fit.json index 48b2e3eb41..f764894b2a 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [7.813662172000022, 2.631280527999934, 13.10751998800015, 3.710660526999618]], [34115, [7.890770659999816, 2.6541829950001556, 11.86105055600001, 3.8145785550000255]], [34120, [7.987968695999825, 2.585337749000246, 12.80511913600003, 3.8722442140001476]], [34126, [7.752072297999803, 2.639289982000264, 13.011203486999875, 3.8892102569998315]], [34139, [7.88686423099989, 2.720284802999913, 12.506980561000091, 3.3476920774999144]], [34140, [8.175071625000328, 2.6887398814999415, 12.425730679000026, 4.01721900099983]], [34141, [7.710956264000288, 2.5998024409996106, 11.318275010000434, 3.8583944370002428]], [34155, [9.042567922000217, 2.6205434250000508, 11.327867981000054, 3.9026235350002025]], [34158, [7.800100429000395, 2.54144083600022, 11.44762519699998, 3.95882699699996]], [34160, [7.763412393999715, 2.690199855499941, 11.599635012000363, 4.0297477200001595]], [34162, [8.052950703999613, 2.5815270469997813, 12.913747177000005, 3.766678955000316]]] \ No newline at end of file +[[34113, [7.813662172000022, 2.631280527999934, 13.10751998800015, 3.710660526999618]], [34115, [7.890770659999816, 2.6541829950001556, 11.86105055600001, 3.8145785550000255]], [34120, [7.987968695999825, 2.585337749000246, 12.80511913600003, 3.8722442140001476]], [34126, [7.752072297999803, 2.639289982000264, 13.011203486999875, 3.8892102569998315]], [34139, [7.88686423099989, 2.720284802999913, 12.506980561000091, 3.3476920774999144]], [34140, [8.175071625000328, 2.6887398814999415, 12.425730679000026, 4.01721900099983]], [34141, [7.710956264000288, 2.5998024409996106, 11.318275010000434, 3.8583944370002428]], [34155, [9.042567922000217, 2.6205434250000508, 11.327867981000054, 3.9026235350002025]], [34158, [7.800100429000395, 2.54144083600022, 11.44762519699998, 3.95882699699996]], [34160, [7.763412393999715, 2.690199855499941, 11.599635012000363, 4.0297477200001595]], [34162, [8.052950703999613, 2.5815270469997813, 12.913747177000005, 3.766678955000316]], [34164, [9.085547088999647, 2.6027938379997977, 12.921292811000058, 3.9211711170000854]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_predict.json index da620fb9f9..592d4c0f69 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.22913243850030085, 0.16478286599976855, 1.991937617999838, 0.7731947814997966]], [34115, [0.26504841399969337, 0.16383611399987785, 2.0814112130001376, 0.7831545280000682]], [34120, [0.24261155849990246, 0.15926719699996283, 2.1483221379999122, 0.7804793590003101]], [34126, [0.2670710910001617, 0.15454414700002417, 1.9866251339999508, 0.7630215624999437]], [34139, [0.2664149769998403, 0.16428017149996776, 2.3061396654998134, 0.7840486780000901]], [34140, [0.23997445400027573, 0.16390845749992877, 2.154497423000066, 0.7836551760001385]], [34141, [0.26705912650004393, 0.16311937750015204, 2.0884010529998704, 0.7730670294999982]], [34155, [0.23425654049992772, 0.164310564500056, 2.281735604000005, 0.7737549180001224]], [34158, [0.26201189899984456, 0.16252918500003943, 2.184382443999766, 0.7811598415000844]], [34160, [0.23783584699981475, 0.1642423409998628, 2.229272642000069, 0.7731388650001918]], [34162, [0.24140098200018656, 0.15914731900011247, 2.1570284999997966, 0.7931396809999569]]] \ No newline at end of file +[[34113, [0.22913243850030085, 0.16478286599976855, 1.991937617999838, 0.7731947814997966]], [34115, [0.26504841399969337, 0.16383611399987785, 2.0814112130001376, 0.7831545280000682]], [34120, [0.24261155849990246, 0.15926719699996283, 2.1483221379999122, 0.7804793590003101]], [34126, [0.2670710910001617, 0.15454414700002417, 1.9866251339999508, 0.7630215624999437]], [34139, [0.2664149769998403, 0.16428017149996776, 2.3061396654998134, 0.7840486780000901]], [34140, [0.23997445400027573, 0.16390845749992877, 2.154497423000066, 0.7836551760001385]], [34141, [0.26705912650004393, 0.16311937750015204, 2.0884010529998704, 0.7730670294999982]], [34155, [0.23425654049992772, 0.164310564500056, 2.281735604000005, 0.7737549180001224]], [34158, [0.26201189899984456, 0.16252918500003943, 2.184382443999766, 0.7811598415000844]], [34160, [0.23783584699981475, 0.1642423409998628, 2.229272642000069, 0.7731388650001918]], [34162, [0.24140098200018656, 0.15914731900011247, 2.1570284999997966, 0.7931396809999569]], [34164, [0.2336071004999667, 0.16390110649967937, 2.256482493500016, 0.7739589839998189]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.track_test_score.json index f1e6ee2e68..aaad00f285 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.7452087689026669, 0.7452087689026669, 0.8656423941766682, 0.8656423941766682]], [34115, [0.7428708480147509, 0.7428708480147509, 0.8656423941766682, 0.8656423941766682]], [34120, [0.7488528575232659, 0.7488528575232659, 0.8656423941766682, 0.8656423941766682]], [34126, [0.7625079204188426, 0.7625079204188426, 0.8656423941766682, 0.8656423941766682]], [34139, [0.7509938759610261, 0.7509938759610261, 0.8656423941766682, 0.8656423941766682]], [34140, [0.7404731129108142, 0.7404731129108142, 0.8656423941766682, 0.8656423941766682]], [34141, [0.7572054211067915, 0.7572054211067915, 0.8656423941766682, 0.8656423941766682]], [34155, [0.751560151161111, 0.751560151161111, 0.8656423941766682, 0.8656423941766682]], [34158, [0.7451817654542843, 0.7451817654542843, 0.8656423941766682, 0.8656423941766682]], [34160, [0.7418582809705169, 0.7418582809705169, 0.8656423941766682, 0.8656423941766682]], [34162, [0.7499083474088095, 0.7499083474088095, 0.8656423941766682, 0.8656423941766682]]] \ No newline at end of file +[[34113, [0.7452087689026669, 0.7452087689026669, 0.8656423941766682, 0.8656423941766682]], [34115, [0.7428708480147509, 0.7428708480147509, 0.8656423941766682, 0.8656423941766682]], [34120, [0.7488528575232659, 0.7488528575232659, 0.8656423941766682, 0.8656423941766682]], [34126, [0.7625079204188426, 0.7625079204188426, 0.8656423941766682, 0.8656423941766682]], [34139, [0.7509938759610261, 0.7509938759610261, 0.8656423941766682, 0.8656423941766682]], [34140, [0.7404731129108142, 0.7404731129108142, 0.8656423941766682, 0.8656423941766682]], [34141, [0.7572054211067915, 0.7572054211067915, 0.8656423941766682, 0.8656423941766682]], [34155, [0.751560151161111, 0.751560151161111, 0.8656423941766682, 0.8656423941766682]], [34158, [0.7451817654542843, 0.7451817654542843, 0.8656423941766682, 0.8656423941766682]], [34160, [0.7418582809705169, 0.7418582809705169, 0.8656423941766682, 0.8656423941766682]], [34162, [0.7499083474088095, 0.7499083474088095, 0.8656423941766682, 0.8656423941766682]], [34164, [0.7514125134095717, 0.7514125134095717, 0.8656423941766682, 0.8656423941766682]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.track_train_score.json index 359fcf6a4c..0da13356d9 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.997144213244914, 0.997144213244914, 0.9996123288718864, 0.9996123288718864]], [34115, [0.9966205676979023, 0.9966205676979023, 0.9996123288718864, 0.9996123288718864]], [34120, [0.9964776279865033, 0.9964776279865033, 0.9996123288718864, 0.9996123288718864]], [34126, [0.996908203929455, 0.996908203929455, 0.9996123288718864, 0.9996123288718864]], [34139, [0.9964145298929145, 0.9964145298929145, 0.9996123288718864, 0.9996123288718864]], [34140, [0.9966586401285239, 0.9966586401285239, 0.9996123288718864, 0.9996123288718864]], [34141, [0.997571208059097, 0.997571208059097, 0.9996123288718864, 0.9996123288718864]], [34155, [0.9970748704681233, 0.9970748704681233, 0.9996123288718864, 0.9996123288718864]], [34158, [0.9971436671182348, 0.9971436671182348, 0.9996123288718864, 0.9996123288718864]], [34160, [0.9968332593859823, 0.9968332593859823, 0.9996123288718864, 0.9996123288718864]], [34162, [0.9971490450302072, 0.9971490450302072, 0.9996123288718864, 0.9996123288718864]]] \ No newline at end of file +[[34113, [0.997144213244914, 0.997144213244914, 0.9996123288718864, 0.9996123288718864]], [34115, [0.9966205676979023, 0.9966205676979023, 0.9996123288718864, 0.9996123288718864]], [34120, [0.9964776279865033, 0.9964776279865033, 0.9996123288718864, 0.9996123288718864]], [34126, [0.996908203929455, 0.996908203929455, 0.9996123288718864, 0.9996123288718864]], [34139, [0.9964145298929145, 0.9964145298929145, 0.9996123288718864, 0.9996123288718864]], [34140, [0.9966586401285239, 0.9966586401285239, 0.9996123288718864, 0.9996123288718864]], [34141, [0.997571208059097, 0.997571208059097, 0.9996123288718864, 0.9996123288718864]], [34155, [0.9970748704681233, 0.9970748704681233, 0.9996123288718864, 0.9996123288718864]], [34158, [0.9971436671182348, 0.9971436671182348, 0.9996123288718864, 0.9996123288718864]], [34160, [0.9968332593859823, 0.9968332593859823, 0.9996123288718864, 0.9996123288718864]], [34162, [0.9971490450302072, 0.9971490450302072, 0.9996123288718864, 0.9996123288718864]], [34164, [0.9976925608991845, 0.9976925608991845, 0.9996123288718864, 0.9996123288718864]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.peakmem_fit.json index 9dc4b4a882..671313297a 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [852660224.0, 1208893440.0, 123805696.0, null]], [34115, [852480000.0, 1208991744.0, 123572224.0, null]], [34120, [852602880.0, 1208692736.0, 123682816.0, null]], [34126, [852758528.0, 1208999936.0, 123842560.0, null]], [34139, [852553728.0, 1208664064.0, 123641856.0, null]], [34140, [852291584.0, 1208487936.0, 123547648.0, null]], [34141, [852819968.0, 1208971264.0, 123748352.0, null]], [34155, [852738048.0, 1208832000.0, 123797504.0, null]], [34158, [852488192.0, 1208963072.0, 123551744.0, null]], [34160, [852664320.0, 1208930304.0, 123584512.0, null]], [34162, [852660224.0, 1208922112.0, 123863040.0, null]]] \ No newline at end of file +[[34113, [852660224.0, 1208893440.0, 123805696.0, null]], [34115, [852480000.0, 1208991744.0, 123572224.0, null]], [34120, [852602880.0, 1208692736.0, 123682816.0, null]], [34126, [852758528.0, 1208999936.0, 123842560.0, null]], [34139, [852553728.0, 1208664064.0, 123641856.0, null]], [34140, [852291584.0, 1208487936.0, 123547648.0, null]], [34141, [852819968.0, 1208971264.0, 123748352.0, null]], [34155, [852738048.0, 1208832000.0, 123797504.0, null]], [34158, [852488192.0, 1208963072.0, 123551744.0, null]], [34160, [852664320.0, 1208930304.0, 123584512.0, null]], [34162, [852660224.0, 1208922112.0, 123863040.0, null]], [34164, [852422656.0, 1208594432.0, 123518976.0, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.peakmem_predict.json index 1768a29b8c..01417d7e5b 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [489689088.0, 488415232.0, 96985088.0, null]], [34115, [488427520.0, 488308736.0, 96681984.0, null]], [34120, [488407040.0, 488423424.0, 96821248.0, null]], [34126, [488579072.0, 488574976.0, 96825344.0, null]], [34139, [488456192.0, 488460288.0, 96677888.0, null]], [34140, [487886848.0, 487829504.0, 96653312.0, null]], [34141, [488599552.0, 488480768.0, 96944128.0, null]], [34155, [489119744.0, 489054208.0, 96403456.0, null]], [34158, [488312832.0, 488304640.0, 96731136.0, null]], [34160, [488333312.0, 488415232.0, 96825344.0, null]], [34162, [488431616.0, 488435712.0, 96739328.0, null]]] \ No newline at end of file +[[34113, [489689088.0, 488415232.0, 96985088.0, null]], [34115, [488427520.0, 488308736.0, 96681984.0, null]], [34120, [488407040.0, 488423424.0, 96821248.0, null]], [34126, [488579072.0, 488574976.0, 96825344.0, null]], [34139, [488456192.0, 488460288.0, 96677888.0, null]], [34140, [487886848.0, 487829504.0, 96653312.0, null]], [34141, [488599552.0, 488480768.0, 96944128.0, null]], [34155, [489119744.0, 489054208.0, 96403456.0, null]], [34158, [488312832.0, 488304640.0, 96731136.0, null]], [34160, [488333312.0, 488415232.0, 96825344.0, null]], [34162, [488431616.0, 488435712.0, 96739328.0, null]], [34164, [488521728.0, 488583168.0, 96755712.0, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.time_fit.json index e517cf56db..d28115c568 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [1.503077243000007, 1.846700294500124, 2.9672953879999113, null]], [34115, [1.4873651390003033, 1.8177908520001438, 2.59364191900022, null]], [34120, [1.531378032000248, 1.8468832720000137, 2.7112892300001477, null]], [34126, [1.533449082999823, 1.8606683004998104, 2.942428560000053, null]], [34139, [1.5193447579999884, 1.8595000084997082, 2.835243714999933, null]], [34140, [1.5126034819995766, 1.8216339539999353, 2.6061559649997434, null]], [34141, [1.4932458210000732, 1.8395198165001148, 2.566649231000156, null]], [34155, [1.4946025629997166, 1.828222786499964, 2.9713149649999195, null]], [34158, [1.5216081809999196, 1.8668405230002918, 2.6438975539999774, null]], [34160, [1.5257385820000309, 1.81849905450008, 2.6026626269999724, null]], [34162, [1.518916893000096, 1.864188352499923, 2.973103538000032, null]]] \ No newline at end of file +[[34113, [1.503077243000007, 1.846700294500124, 2.9672953879999113, null]], [34115, [1.4873651390003033, 1.8177908520001438, 2.59364191900022, null]], [34120, [1.531378032000248, 1.8468832720000137, 2.7112892300001477, null]], [34126, [1.533449082999823, 1.8606683004998104, 2.942428560000053, null]], [34139, [1.5193447579999884, 1.8595000084997082, 2.835243714999933, null]], [34140, [1.5126034819995766, 1.8216339539999353, 2.6061559649997434, null]], [34141, [1.4932458210000732, 1.8395198165001148, 2.566649231000156, null]], [34155, [1.4946025629997166, 1.828222786499964, 2.9713149649999195, null]], [34158, [1.5216081809999196, 1.8668405230002918, 2.6438975539999774, null]], [34160, [1.5257385820000309, 1.81849905450008, 2.6026626269999724, null]], [34162, [1.518916893000096, 1.864188352499923, 2.973103538000032, null]], [34164, [1.4877357710001888, 1.8094093889999385, 3.000940709000133, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.time_predict.json index 77393f6737..bc4917102d 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.05389516099990033, 0.05423411900028441, 0.003108844000053068, null]], [34115, [0.04891691400007403, 0.051755285499893944, 0.0026089054999829386, null]], [34120, [0.04905522549984198, 0.049049809499820185, 0.0023140689000229033, null]], [34126, [0.051988829000038095, 0.05033106250016317, 0.003116641499976443, null]], [34139, [0.048820078000062495, 0.0489583205001054, 0.0031004231666429405, null]], [34140, [0.053175156500174126, 0.05017690699969535, 0.0030782541665909475, null]], [34141, [0.050365806499939936, 0.05113379999988865, 0.0026252118999764203, null]], [34155, [0.04857381100009661, 0.0489027785001781, 0.0030937553334145678, null]], [34158, [0.052264668499901745, 0.052171042500049225, 0.0030675015000269923, null]], [34160, [0.051866391000203294, 0.05166774699978305, 0.0030837281666814915, null]], [34162, [0.04860671050005294, 0.04861176700001124, 0.0022938249999697293, null]]] \ No newline at end of file +[[34113, [0.05389516099990033, 0.05423411900028441, 0.003108844000053068, null]], [34115, [0.04891691400007403, 0.051755285499893944, 0.0026089054999829386, null]], [34120, [0.04905522549984198, 0.049049809499820185, 0.0023140689000229033, null]], [34126, [0.051988829000038095, 0.05033106250016317, 0.003116641499976443, null]], [34139, [0.048820078000062495, 0.0489583205001054, 0.0031004231666429405, null]], [34140, [0.053175156500174126, 0.05017690699969535, 0.0030782541665909475, null]], [34141, [0.050365806499939936, 0.05113379999988865, 0.0026252118999764203, null]], [34155, [0.04857381100009661, 0.0489027785001781, 0.0030937553334145678, null]], [34158, [0.052264668499901745, 0.052171042500049225, 0.0030675015000269923, null]], [34160, [0.051866391000203294, 0.05166774699978305, 0.0030837281666814915, null]], [34162, [0.04860671050005294, 0.04861176700001124, 0.0022938249999697293, null]], [34164, [0.050347782499784444, 0.05032561400003033, 0.0026102439999704076, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.track_test_score.json index 907b97ead4..366984d64b 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.9274010856209145, 0.9274010850953214, 0.9507063990451832, null]], [34115, [0.9274010856209145, 0.9274010850953214, 0.9497652084082335, null]], [34120, [0.9274010856209145, 0.9274010850953214, 0.9497792096137744, null]], [34126, [0.9274010856209145, 0.9274010850953214, 0.9496576613619748, null]], [34139, [0.9274010856209145, 0.9274010850953214, 0.9503996252926831, null]], [34140, [0.9274010856209145, 0.9274010850953214, 0.9496787377825079, null]], [34141, [0.9274010856209145, 0.9274010850953214, 0.9511661874618516, null]], [34155, [0.9274010856209145, 0.9274010850953214, 0.9503229902646675, null]], [34158, [0.9274010856209145, 0.9274010850953214, 0.9503336487711286, null]], [34160, [0.9274010856209145, 0.9274010850953214, 0.9492574849383765, null]], [34162, [0.9274010856209145, 0.9274010850953214, 0.9484256932560814, null]]] \ No newline at end of file +[[34113, [0.9274010856209145, 0.9274010850953214, 0.9507063990451832, null]], [34115, [0.9274010856209145, 0.9274010850953214, 0.9497652084082335, null]], [34120, [0.9274010856209145, 0.9274010850953214, 0.9497792096137744, null]], [34126, [0.9274010856209145, 0.9274010850953214, 0.9496576613619748, null]], [34139, [0.9274010856209145, 0.9274010850953214, 0.9503996252926831, null]], [34140, [0.9274010856209145, 0.9274010850953214, 0.9496787377825079, null]], [34141, [0.9274010856209145, 0.9274010850953214, 0.9511661874618516, null]], [34155, [0.9274010856209145, 0.9274010850953214, 0.9503229902646675, null]], [34158, [0.9274010856209145, 0.9274010850953214, 0.9503336487711286, null]], [34160, [0.9274010856209145, 0.9274010850953214, 0.9492574849383765, null]], [34162, [0.9274010856209145, 0.9274010850953214, 0.9484256932560814, null]], [34164, [0.9274010856209145, 0.9274010850953214, 0.9503669656848922, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.track_train_score.json index 9faa097d3e..ff11503246 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.9276022550495941, 0.9276022552325599, 0.9559910307755232, null]], [34115, [0.9276022550495941, 0.9276022552325599, 0.955965578016296, null]], [34120, [0.9276022550495941, 0.9276022552325599, 0.9556130917473258, null]], [34126, [0.9276022550495941, 0.9276022552325599, 0.9562419028808282, null]], [34139, [0.9276022550495941, 0.9276022552325599, 0.9561033907206925, null]], [34140, [0.9276022550495941, 0.9276022552325599, 0.9563885342377361, null]], [34141, [0.9276022550495941, 0.9276022552325599, 0.9562091104795359, null]], [34155, [0.9276022550495941, 0.9276022552325599, 0.9565811213008745, null]], [34158, [0.9276022550495941, 0.9276022552325599, 0.9563373466233949, null]], [34160, [0.9276022550495941, 0.9276022552325599, 0.956281705949938, null]], [34162, [0.9276022550495941, 0.9276022552325599, 0.9556867859652732, null]]] \ No newline at end of file +[[34113, [0.9276022550495941, 0.9276022552325599, 0.9559910307755232, null]], [34115, [0.9276022550495941, 0.9276022552325599, 0.955965578016296, null]], [34120, [0.9276022550495941, 0.9276022552325599, 0.9556130917473258, null]], [34126, [0.9276022550495941, 0.9276022552325599, 0.9562419028808282, null]], [34139, [0.9276022550495941, 0.9276022552325599, 0.9561033907206925, null]], [34140, [0.9276022550495941, 0.9276022552325599, 0.9563885342377361, null]], [34141, [0.9276022550495941, 0.9276022552325599, 0.9562091104795359, null]], [34155, [0.9276022550495941, 0.9276022552325599, 0.9565811213008745, null]], [34158, [0.9276022550495941, 0.9276022552325599, 0.9563373466233949, null]], [34160, [0.9276022550495941, 0.9276022552325599, 0.956281705949938, null]], [34162, [0.9276022550495941, 0.9276022552325599, 0.9556867859652732, null]], [34164, [0.9276022550495941, 0.9276022552325599, 0.9557095101976094, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.peakmem_fit.json index 2596100f32..ef4898a7ec 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [852594688.0, 1208889344.0, 123805696.0, null]], [34115, [852611072.0, 1208999936.0, 123604992.0, null]], [34120, [852676608.0, 1208688640.0, 123674624.0, null]], [34126, [852758528.0, 1208995840.0, 123854848.0, null]], [34139, [852492288.0, 1208659968.0, 123645952.0, null]], [34140, [852295680.0, 1208483840.0, 123289600.0, null]], [34141, [852885504.0, 1208979456.0, 123752448.0, null]], [34155, [852672512.0, 1208848384.0, 123817984.0, null]], [34158, [852557824.0, 1208967168.0, 123568128.0, null]], [34160, [852672512.0, 1208922112.0, 123588608.0, null]], [34162, [852664320.0, 1208913920.0, 123867136.0, null]]] \ No newline at end of file +[[34113, [852594688.0, 1208889344.0, 123805696.0, null]], [34115, [852611072.0, 1208999936.0, 123604992.0, null]], [34120, [852676608.0, 1208688640.0, 123674624.0, null]], [34126, [852758528.0, 1208995840.0, 123854848.0, null]], [34139, [852492288.0, 1208659968.0, 123645952.0, null]], [34140, [852295680.0, 1208483840.0, 123289600.0, null]], [34141, [852885504.0, 1208979456.0, 123752448.0, null]], [34155, [852672512.0, 1208848384.0, 123817984.0, null]], [34158, [852557824.0, 1208967168.0, 123568128.0, null]], [34160, [852672512.0, 1208922112.0, 123588608.0, null]], [34162, [852664320.0, 1208913920.0, 123867136.0, null]], [34164, [852422656.0, 1208590336.0, 123547648.0, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.peakmem_predict.json index 7a34483650..2e49953831 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [489857024.0, 488349696.0, 96997376.0, null]], [34115, [488427520.0, 488427520.0, 96530432.0, null]], [34120, [488411136.0, 488402944.0, 96821248.0, null]], [34126, [488652800.0, 488656896.0, 96890880.0, null]], [34139, [488468480.0, 488538112.0, 96751616.0, null]], [34140, [487903232.0, 487907328.0, 96657408.0, null]], [34141, [488554496.0, 488615936.0, 96968704.0, null]], [34155, [489328640.0, 489394176.0, 96403456.0, null]], [34158, [488312832.0, 488316928.0, 96755712.0, null]], [34160, [488378368.0, 488284160.0, 96821248.0, null]], [34162, [488431616.0, 488546304.0, 96735232.0, null]]] \ No newline at end of file +[[34113, [489857024.0, 488349696.0, 96997376.0, null]], [34115, [488427520.0, 488427520.0, 96530432.0, null]], [34120, [488411136.0, 488402944.0, 96821248.0, null]], [34126, [488652800.0, 488656896.0, 96890880.0, null]], [34139, [488468480.0, 488538112.0, 96751616.0, null]], [34140, [487903232.0, 487907328.0, 96657408.0, null]], [34141, [488554496.0, 488615936.0, 96968704.0, null]], [34155, [489328640.0, 489394176.0, 96403456.0, null]], [34158, [488312832.0, 488316928.0, 96755712.0, null]], [34160, [488378368.0, 488284160.0, 96821248.0, null]], [34162, [488431616.0, 488546304.0, 96735232.0, null]], [34164, [488673280.0, 488677376.0, 96768000.0, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_fit.json index 99c39e6da6..86d481e31e 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [1.5239953260006587, 1.8497955205002654, 2.7018208590006907, null]], [34115, [1.5279928590002783, 1.8691245400000298, 2.4240076305000002, null]], [34120, [1.5262647925001147, 1.881840656500117, 2.4087156180000875, null]], [34126, [1.5164873310000075, 1.8395980235000025, 2.6776082740002494, null]], [34139, [1.485033693999867, 1.800661921000028, 2.3943103279998468, null]], [34140, [1.535684588499862, 1.8550358274999326, 2.4545799929996974, null]], [34141, [1.5099309950001043, 1.8337169439998888, 2.690711140000076, null]], [34155, [1.4839816409999003, 1.8104580019999048, 2.7141099630002827, null]], [34158, [1.5131060970002181, 1.8375568494998333, 2.727330099000028, null]], [34160, [1.5230309040002794, 1.8519302365000385, 2.373872123499723, null]], [34162, [1.5111102109999592, 1.8382507880000958, 2.3619796595000935, null]]] \ No newline at end of file +[[34113, [1.5239953260006587, 1.8497955205002654, 2.7018208590006907, null]], [34115, [1.5279928590002783, 1.8691245400000298, 2.4240076305000002, null]], [34120, [1.5262647925001147, 1.881840656500117, 2.4087156180000875, null]], [34126, [1.5164873310000075, 1.8395980235000025, 2.6776082740002494, null]], [34139, [1.485033693999867, 1.800661921000028, 2.3943103279998468, null]], [34140, [1.535684588499862, 1.8550358274999326, 2.4545799929996974, null]], [34141, [1.5099309950001043, 1.8337169439998888, 2.690711140000076, null]], [34155, [1.4839816409999003, 1.8104580019999048, 2.7141099630002827, null]], [34158, [1.5131060970002181, 1.8375568494998333, 2.727330099000028, null]], [34160, [1.5230309040002794, 1.8519302365000385, 2.373872123499723, null]], [34162, [1.5111102109999592, 1.8382507880000958, 2.3619796595000935, null]], [34164, [1.4888062420000097, 1.8079061550001825, 2.5100165049998395, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_predict.json index 7fd41318dc..2b92c1ba57 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.05104908500015881, 0.05391180350034119, 0.0026218439000331275, null]], [34115, [0.04950163350008552, 0.049300229500204296, 0.0024172451000140428, null]], [34120, [0.05256559050008036, 0.05266997450007693, 0.002604424599985578, null]], [34126, [0.052009156500162135, 0.04877835449997292, 0.003069596624982296, null]], [34139, [0.0469083384998612, 0.04811633900021661, 0.0026101646999904917, null]], [34140, [0.053887745999873005, 0.051782497999965926, 0.0030985074999989592, null]], [34141, [0.04865654550008003, 0.05019419649988777, 0.00305248462501595, null]], [34155, [0.04920758749995002, 0.04857772850004949, 0.002283395899985408, null]], [34158, [0.0538293165000141, 0.05035330300006535, 0.003087816833309868, null]], [34160, [0.05168738199972722, 0.04868466550010453, 0.0030951064999650653, null]], [34162, [0.048717755000097895, 0.04874280100011674, 0.0030709731250340155, null]]] \ No newline at end of file +[[34113, [0.05104908500015881, 0.05391180350034119, 0.0026218439000331275, null]], [34115, [0.04950163350008552, 0.049300229500204296, 0.0024172451000140428, null]], [34120, [0.05256559050008036, 0.05266997450007693, 0.002604424599985578, null]], [34126, [0.052009156500162135, 0.04877835449997292, 0.003069596624982296, null]], [34139, [0.0469083384998612, 0.04811633900021661, 0.0026101646999904917, null]], [34140, [0.053887745999873005, 0.051782497999965926, 0.0030985074999989592, null]], [34141, [0.04865654550008003, 0.05019419649988777, 0.00305248462501595, null]], [34155, [0.04920758749995002, 0.04857772850004949, 0.002283395899985408, null]], [34158, [0.0538293165000141, 0.05035330300006535, 0.003087816833309868, null]], [34160, [0.05168738199972722, 0.04868466550010453, 0.0030951064999650653, null]], [34162, [0.048717755000097895, 0.04874280100011674, 0.0030709731250340155, null]], [34164, [0.04686548949985081, 0.04995990999987043, 0.0031124310000905098, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.track_test_score.json index 03df3c61c0..b93574e814 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.9274015024583205, 0.9274015028138817, 0.9494692478356281, null]], [34115, [0.9274015024583205, 0.9274015028138817, 0.9484680415057948, null]], [34120, [0.9274015024583205, 0.9274015028138817, 0.9482918280589865, null]], [34126, [0.9274015024583205, 0.9274015028138817, 0.9482855114502713, null]], [34139, [0.9274015024583205, 0.9274015028138817, 0.9490583964576568, null]], [34140, [0.9274015024583205, 0.9274015028138817, 0.9487190858734746, null]], [34141, [0.9274015024583205, 0.9274015028138817, 0.9497868600089711, null]], [34155, [0.9274015024583205, 0.9274015028138817, 0.949039799117987, null]], [34158, [0.9274015024583205, 0.9274015028138817, 0.949232685260236, null]], [34160, [0.9274015024583205, 0.9274015028138817, 0.9475150361322258, null]], [34162, [0.9274015024583205, 0.9274015028138817, 0.9468968169861525, null]]] \ No newline at end of file +[[34113, [0.9274015024583205, 0.9274015028138817, 0.9494692478356281, null]], [34115, [0.9274015024583205, 0.9274015028138817, 0.9484680415057948, null]], [34120, [0.9274015024583205, 0.9274015028138817, 0.9482918280589865, null]], [34126, [0.9274015024583205, 0.9274015028138817, 0.9482855114502713, null]], [34139, [0.9274015024583205, 0.9274015028138817, 0.9490583964576568, null]], [34140, [0.9274015024583205, 0.9274015028138817, 0.9487190858734746, null]], [34141, [0.9274015024583205, 0.9274015028138817, 0.9497868600089711, null]], [34155, [0.9274015024583205, 0.9274015028138817, 0.949039799117987, null]], [34158, [0.9274015024583205, 0.9274015028138817, 0.949232685260236, null]], [34160, [0.9274015024583205, 0.9274015028138817, 0.9475150361322258, null]], [34162, [0.9274015024583205, 0.9274015028138817, 0.9468968169861525, null]], [34164, [0.9274015024583205, 0.9274015028138817, 0.9490962488661691, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.track_train_score.json index f06209af4d..6eaa26d25f 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.92760249197518, 0.9276024919395177, 0.9535520060174222, null]], [34115, [0.92760249197518, 0.9276024919395177, 0.9535011268768218, null]], [34120, [0.92760249197518, 0.9276024919395177, 0.9531765235157791, null]], [34126, [0.92760249197518, 0.9276024919395177, 0.9538195148081864, null]], [34139, [0.92760249197518, 0.9276024919395177, 0.9535898656773749, null]], [34140, [0.92760249197518, 0.9276024919395177, 0.9539501614002056, null]], [34141, [0.92760249197518, 0.9276024919395177, 0.9538726986116016, null]], [34155, [0.92760249197518, 0.9276024919395177, 0.9541328402116976, null]], [34158, [0.92760249197518, 0.9276024919395177, 0.9538945724032855, null]], [34160, [0.92760249197518, 0.9276024919395177, 0.9538589113779388, null]], [34162, [0.92760249197518, 0.9276024919395177, 0.9532118542977651, null]]] \ No newline at end of file +[[34113, [0.92760249197518, 0.9276024919395177, 0.9535520060174222, null]], [34115, [0.92760249197518, 0.9276024919395177, 0.9535011268768218, null]], [34120, [0.92760249197518, 0.9276024919395177, 0.9531765235157791, null]], [34126, [0.92760249197518, 0.9276024919395177, 0.9538195148081864, null]], [34139, [0.92760249197518, 0.9276024919395177, 0.9535898656773749, null]], [34140, [0.92760249197518, 0.9276024919395177, 0.9539501614002056, null]], [34141, [0.92760249197518, 0.9276024919395177, 0.9538726986116016, null]], [34155, [0.92760249197518, 0.9276024919395177, 0.9541328402116976, null]], [34158, [0.92760249197518, 0.9276024919395177, 0.9538945724032855, null]], [34160, [0.92760249197518, 0.9276024919395177, 0.9538589113779388, null]], [34162, [0.92760249197518, 0.9276024919395177, 0.9532118542977651, null]], [34164, [0.92760249197518, 0.9276024919395177, 0.9533432474207427, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.peakmem_fit.json index 7f8b03936a..4d363db822 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [1214894080.0, 236261376.0]], [34115, [1214914560.0, 236216320.0]], [34120, [1215016960.0, 236060672.0]], [34126, [1215062016.0, 236138496.0]], [34139, [1214832640.0, 235917312.0]], [34140, [1214726144.0, 235749376.0]], [34141, [1215094784.0, 236449792.0]], [34155, [1214951424.0, 236081152.0]], [34158, [1214930944.0, 235782144.0]], [34160, [1215074304.0, 236163072.0]], [34162, [1215070208.0, 236310528.0]]] \ No newline at end of file +[[34113, [1214894080.0, 236261376.0]], [34115, [1214914560.0, 236216320.0]], [34120, [1215016960.0, 236060672.0]], [34126, [1215062016.0, 236138496.0]], [34139, [1214832640.0, 235917312.0]], [34140, [1214726144.0, 235749376.0]], [34141, [1215094784.0, 236449792.0]], [34155, [1214951424.0, 236081152.0]], [34158, [1214930944.0, 235782144.0]], [34160, [1215074304.0, 236163072.0]], [34162, [1215070208.0, 236310528.0]], [34164, [1214713856.0, 235802624.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.peakmem_predict.json index db13749be2..c4d5365367 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [489857024.0, 156368896.0]], [34115, [488448000.0, 156499968.0]], [34120, [488456192.0, 156385280.0]], [34126, [488652800.0, 156790784.0]], [34139, [488460288.0, 156585984.0]], [34140, [488046592.0, 155860992.0]], [34141, [488615936.0, 156741632.0]], [34155, [489185280.0, 156241920.0]], [34158, [488325120.0, 156180480.0]], [34160, [488419328.0, 156594176.0]], [34162, [488439808.0, 156549120.0]]] \ No newline at end of file +[[34113, [489857024.0, 156368896.0]], [34115, [488448000.0, 156499968.0]], [34120, [488456192.0, 156385280.0]], [34126, [488652800.0, 156790784.0]], [34139, [488460288.0, 156585984.0]], [34140, [488046592.0, 155860992.0]], [34141, [488615936.0, 156741632.0]], [34155, [489185280.0, 156241920.0]], [34158, [488325120.0, 156180480.0]], [34160, [488419328.0, 156594176.0]], [34162, [488439808.0, 156549120.0]], [34164, [488714240.0, 156061696.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.time_fit.json index d4ee684529..f03d2741e8 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [3.1477707140002167, 1.119999438999912]], [34115, [3.0982080889998542, 1.1249297180002031]], [34120, [3.072171095000158, 1.1003675929996461]], [34126, [3.107850808999501, 1.1242004460000317]], [34139, [3.104394320999745, 1.130350608000299]], [34140, [3.1200300549999156, 1.123712613000862]], [34141, [3.0841696369998317, 1.1130340089994206]], [34155, [3.12040750199958, 1.105185679999522]], [34158, [3.089356376000069, 1.1447208930003399]], [34160, [3.1335604019996026, 1.1193904910005585]], [34162, [3.128602781999689, 1.1407109069996295]]] \ No newline at end of file +[[34113, [3.1477707140002167, 1.119999438999912]], [34115, [3.0982080889998542, 1.1249297180002031]], [34120, [3.072171095000158, 1.1003675929996461]], [34126, [3.107850808999501, 1.1242004460000317]], [34139, [3.104394320999745, 1.130350608000299]], [34140, [3.1200300549999156, 1.123712613000862]], [34141, [3.0841696369998317, 1.1130340089994206]], [34155, [3.12040750199958, 1.105185679999522]], [34158, [3.089356376000069, 1.1447208930003399]], [34160, [3.1335604019996026, 1.1193904910005585]], [34162, [3.128602781999689, 1.1407109069996295]], [34164, [3.1859428859997934, 1.1083194440002444]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.time_predict.json index f80b7f8014..511614b8ac 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.051000174000364495, 0.033584025999971345]], [34115, [0.051702005499919323, 0.0338211845000842]], [34120, [0.05160755400038397, 0.03339269250000143]], [34126, [0.05394243650016506, 0.03452845399988291]], [34139, [0.04983659199979229, 0.033139438000034716]], [34140, [0.053761811000185844, 0.034447631500370335]], [34141, [0.05150740699991729, 0.033556216500528535]], [34155, [0.04948936299979323, 0.03268535500001235]], [34158, [0.05060100200034867, 0.03364304449951305]], [34160, [0.05377105150000716, 0.033953873500195186]], [34162, [0.04882281399977728, 0.03391453199992611]]] \ No newline at end of file +[[34113, [0.051000174000364495, 0.033584025999971345]], [34115, [0.051702005499919323, 0.0338211845000842]], [34120, [0.05160755400038397, 0.03339269250000143]], [34126, [0.05394243650016506, 0.03452845399988291]], [34139, [0.04983659199979229, 0.033139438000034716]], [34140, [0.053761811000185844, 0.034447631500370335]], [34141, [0.05150740699991729, 0.033556216500528535]], [34155, [0.04948936299979323, 0.03268535500001235]], [34158, [0.05060100200034867, 0.03364304449951305]], [34160, [0.05377105150000716, 0.033953873500195186]], [34162, [0.04882281399977728, 0.03391453199992611]], [34164, [0.04958680599975196, 0.03305380149959092]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.track_test_score.json index b67cffb3a9..62f5d50509 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.9274012651798128, 0.10537455395166118]], [34115, [0.9274012651798128, 0.10734502113119426]], [34120, [0.9274012651798128, 0.1019393703664494]], [34126, [0.9274012651798128, 0.09683538400762892]], [34139, [0.9274012651798128, 0.1003338831837407]], [34140, [0.9274012651798128, 0.10510856216849207]], [34141, [0.9274012651798128, 0.10185575897445409]], [34155, [0.9274012651798128, 0.10346956272382513]], [34158, [0.9274012651798128, 0.1055346531725826]], [34160, [0.9274012651798128, 0.10426357226983463]], [34162, [0.9274012651798128, 0.1031687231040086]]] \ No newline at end of file +[[34113, [0.9274012651798128, 0.10537455395166118]], [34115, [0.9274012651798128, 0.10734502113119426]], [34120, [0.9274012651798128, 0.1019393703664494]], [34126, [0.9274012651798128, 0.09683538400762892]], [34139, [0.9274012651798128, 0.1003338831837407]], [34140, [0.9274012651798128, 0.10510856216849207]], [34141, [0.9274012651798128, 0.10185575897445409]], [34155, [0.9274012651798128, 0.10346956272382513]], [34158, [0.9274012651798128, 0.1055346531725826]], [34160, [0.9274012651798128, 0.10426357226983463]], [34162, [0.9274012651798128, 0.1031687231040086]], [34164, [0.9274012651798128, 0.10550304492260665]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.track_train_score.json index 51a0573946..63127fc954 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LinearRegressionBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.927602494829764, 0.9999999999962048]], [34115, [0.927602494829764, 0.9999999999963745]], [34120, [0.927602494829764, 0.999999999996311]], [34126, [0.927602494829764, 0.9999999999962734]], [34139, [0.927602494829764, 0.9999999999964163]], [34140, [0.927602494829764, 0.9999999999962066]], [34141, [0.927602494829764, 0.9999999999963289]], [34155, [0.927602494829764, 0.9999999999962674]], [34158, [0.927602494829764, 0.9999999999962469]], [34160, [0.927602494829764, 0.9999999999962648]], [34162, [0.927602494829764, 0.9999999999963929]]] \ No newline at end of file +[[34113, [0.927602494829764, 0.9999999999962048]], [34115, [0.927602494829764, 0.9999999999963745]], [34120, [0.927602494829764, 0.999999999996311]], [34126, [0.927602494829764, 0.9999999999962734]], [34139, [0.927602494829764, 0.9999999999964163]], [34140, [0.927602494829764, 0.9999999999962066]], [34141, [0.927602494829764, 0.9999999999963289]], [34155, [0.927602494829764, 0.9999999999962674]], [34158, [0.927602494829764, 0.9999999999962469]], [34160, [0.927602494829764, 0.9999999999962648]], [34162, [0.927602494829764, 0.9999999999963929]], [34164, [0.927602494829764, 0.9999999999962889]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.peakmem_fit.json index 591aca7a80..7cf568095a 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [105746432.0, 99024896.0, 83361792.0, 84545536.0, 382517248.0, 125247488.0, 103944192.0, 104714240.0]], [34115, [105762816.0, 98791424.0, 83259392.0, 84430848.0, 381276160.0, 124780544.0, 103759872.0, 104538112.0]], [34120, [105373696.0, 98664448.0, 83279872.0, 84324352.0, 382087168.0, 124932096.0, 104017920.0, 104525824.0]], [34126, [105512960.0, 99225600.0, 83546112.0, 84701184.0, 382337024.0, 125313024.0, 104050688.0, 104771584.0]], [34139, [105369600.0, 98783232.0, 83296256.0, 84361216.0, 381861888.0, 124952576.0, 103677952.0, 104435712.0]], [34140, [105127936.0, 98521088.0, 83210240.0, 84344832.0, 381894656.0, 124768256.0, 103612416.0, 104419328.0]], [34141, [105873408.0, 99123200.0, 83492864.0, 84656128.0, 382210048.0, 125251584.0, 104050688.0, 104841216.0]], [34155, [105402368.0, 98807808.0, 83410944.0, 84385792.0, 381222912.0, 124960768.0, 104108032.0, 104632320.0]], [34158, [105259008.0, 98840576.0, 83279872.0, 84459520.0, 381874176.0, 124923904.0, 103718912.0, 104493056.0]], [34160, [105332736.0, 98742272.0, 83243008.0, 84332544.0, 381329408.0, 124882944.0, 103817216.0, 104534016.0]], [34162, [105226240.0, 98942976.0, 83390464.0, 84557824.0, 381112320.0, 124956672.0, 103993344.0, 104570880.0]]] \ No newline at end of file +[[34113, [105746432.0, 99024896.0, 83361792.0, 84545536.0, 382517248.0, 125247488.0, 103944192.0, 104714240.0]], [34115, [105762816.0, 98791424.0, 83259392.0, 84430848.0, 381276160.0, 124780544.0, 103759872.0, 104538112.0]], [34120, [105373696.0, 98664448.0, 83279872.0, 84324352.0, 382087168.0, 124932096.0, 104017920.0, 104525824.0]], [34126, [105512960.0, 99225600.0, 83546112.0, 84701184.0, 382337024.0, 125313024.0, 104050688.0, 104771584.0]], [34139, [105369600.0, 98783232.0, 83296256.0, 84361216.0, 381861888.0, 124952576.0, 103677952.0, 104435712.0]], [34140, [105127936.0, 98521088.0, 83210240.0, 84344832.0, 381894656.0, 124768256.0, 103612416.0, 104419328.0]], [34141, [105873408.0, 99123200.0, 83492864.0, 84656128.0, 382210048.0, 125251584.0, 104050688.0, 104841216.0]], [34155, [105402368.0, 98807808.0, 83410944.0, 84385792.0, 381222912.0, 124960768.0, 104108032.0, 104632320.0]], [34158, [105259008.0, 98840576.0, 83279872.0, 84459520.0, 381874176.0, 124923904.0, 103718912.0, 104493056.0]], [34160, [105332736.0, 98742272.0, 83243008.0, 84332544.0, 381329408.0, 124882944.0, 103817216.0, 104534016.0]], [34162, [105226240.0, 98942976.0, 83390464.0, 84557824.0, 381112320.0, 124956672.0, 103993344.0, 104570880.0]], [34164, [105193472.0, 98627584.0, 83476480.0, 84377600.0, 381157376.0, 124772352.0, 103841792.0, 104566784.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.peakmem_predict.json index a373e5e6ab..2e2a5d97bc 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [99295232.0, 99217408.0, 86175744.0, 86065152.0, 100352000.0, 100487168.0, 88195072.0, 88182784.0]], [34115, [98861056.0, 98844672.0, 85803008.0, 85970944.0, 100286464.0, 100294656.0, 88223744.0, 88158208.0]], [34120, [99127296.0, 98799616.0, 85897216.0, 85995520.0, 100220928.0, 100196352.0, 88256512.0, 88047616.0]], [34126, [99278848.0, 99438592.0, 86085632.0, 86216704.0, 100626432.0, 100634624.0, 88096768.0, 88100864.0]], [34139, [98811904.0, 98992128.0, 86069248.0, 86200320.0, 100433920.0, 100429824.0, 87830528.0, 87801856.0]], [34140, [98603008.0, 98471936.0, 85663744.0, 85827584.0, 99807232.0, 99815424.0, 87638016.0, 87625728.0]], [34141, [99246080.0, 98963456.0, 86376448.0, 86212608.0, 100425728.0, 100442112.0, 88477696.0, 88412160.0]], [34155, [99053568.0, 99278848.0, 86114304.0, 86204416.0, 100450304.0, 100450304.0, 88076288.0, 88080384.0]], [34158, [98910208.0, 98799616.0, 86056960.0, 85803008.0, 100212736.0, 100147200.0, 87805952.0, 87781376.0]], [34160, [99246080.0, 99061760.0, 86097920.0, 85778432.0, 100294656.0, 100294656.0, 87867392.0, 87838720.0]], [34162, [99045376.0, 98852864.0, 86044672.0, 85966848.0, 100339712.0, 100343808.0, 88199168.0, 88129536.0]]] \ No newline at end of file +[[34113, [99295232.0, 99217408.0, 86175744.0, 86065152.0, 100352000.0, 100487168.0, 88195072.0, 88182784.0]], [34115, [98861056.0, 98844672.0, 85803008.0, 85970944.0, 100286464.0, 100294656.0, 88223744.0, 88158208.0]], [34120, [99127296.0, 98799616.0, 85897216.0, 85995520.0, 100220928.0, 100196352.0, 88256512.0, 88047616.0]], [34126, [99278848.0, 99438592.0, 86085632.0, 86216704.0, 100626432.0, 100634624.0, 88096768.0, 88100864.0]], [34139, [98811904.0, 98992128.0, 86069248.0, 86200320.0, 100433920.0, 100429824.0, 87830528.0, 87801856.0]], [34140, [98603008.0, 98471936.0, 85663744.0, 85827584.0, 99807232.0, 99815424.0, 87638016.0, 87625728.0]], [34141, [99246080.0, 98963456.0, 86376448.0, 86212608.0, 100425728.0, 100442112.0, 88477696.0, 88412160.0]], [34155, [99053568.0, 99278848.0, 86114304.0, 86204416.0, 100450304.0, 100450304.0, 88076288.0, 88080384.0]], [34158, [98910208.0, 98799616.0, 86056960.0, 85803008.0, 100212736.0, 100147200.0, 87805952.0, 87781376.0]], [34160, [99246080.0, 99061760.0, 86097920.0, 85778432.0, 100294656.0, 100294656.0, 87867392.0, 87838720.0]], [34162, [99045376.0, 98852864.0, 86044672.0, 85966848.0, 100339712.0, 100343808.0, 88199168.0, 88129536.0]], [34164, [98729984.0, 98672640.0, 86056960.0, 85983232.0, 100130816.0, 100102144.0, 87883776.0, 87871488.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.time_fit.json index 7a11c8907b..679aaabf36 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [0.02052857299986499, 0.18869883800016396, 4.506277077499817, 4.441826818000209, 1.0322624400000677, 2.892911722000008, 4.052634612000475, 3.5975131530003637]], [34115, [0.021150513000065985, 0.18992112549995, 4.963376912499825, 4.693534734999957, 1.1507344829997237, 2.9954944780001824, 3.664626369999496, 4.6395898655000565]], [34120, [0.022663903999728063, 0.1900928495001608, 4.431748399000298, 4.920255185000315, 1.0958088899997165, 2.9875566620003156, 3.5799573885001337, 4.6472271430002365]], [34126, [0.021789737500512274, 0.18951674400022966, 4.890083466499618, 5.203183940000599, 1.119830186999934, 2.9758953789996667, 3.9982250169996405, 4.055279547000282]], [34139, [0.021585251999567845, 0.18923547800022789, 6.737588544499886, 6.535931969999638, 1.1426961119996122, 2.927481376999822, 4.084116218000418, 4.796345232500244]], [34140, [0.02288981599986073, 0.18946403300014936, 4.901977846500358, 4.9086812650002685, 1.0369827390004502, 2.9462964719996307, 3.8842646690000038, 4.125112634999823]], [34141, [0.02283817999978055, 0.18943942300029448, 4.227935298000375, 5.250737195499823, 1.1300016149998555, 2.9527129660000355, 3.9079445209999903, 4.206512706000012]], [34155, [0.02250768349995269, 0.18915184700017562, 5.085128879999502, 5.106547033000425, 1.1202172154999062, 3.0916373119998752, 3.7006019565001225, 4.176256558000205]], [34158, [0.022577468500003306, 0.18936516099984146, 4.897060346999751, 5.548095727000145, 1.092709123000077, 2.970390075000523, 4.1461177379997025, 3.6277260030001344]], [34160, [0.022829148000255373, 0.1803743355003462, 4.996524258000136, 4.95579465100036, 1.0305067530002816, 2.9800310109994825, 3.572270988499895, 4.155317227000523]], [34162, [0.023230360499837843, 0.18967650499962474, 4.277101779000077, 4.935574182499749, 1.0229312695000772, 3.00213876899943, 3.6338864714998635, 4.147057948500333]]] \ No newline at end of file +[[34113, [0.02052857299986499, 0.18869883800016396, 4.506277077499817, 4.441826818000209, 1.0322624400000677, 2.892911722000008, 4.052634612000475, 3.5975131530003637]], [34115, [0.021150513000065985, 0.18992112549995, 4.963376912499825, 4.693534734999957, 1.1507344829997237, 2.9954944780001824, 3.664626369999496, 4.6395898655000565]], [34120, [0.022663903999728063, 0.1900928495001608, 4.431748399000298, 4.920255185000315, 1.0958088899997165, 2.9875566620003156, 3.5799573885001337, 4.6472271430002365]], [34126, [0.021789737500512274, 0.18951674400022966, 4.890083466499618, 5.203183940000599, 1.119830186999934, 2.9758953789996667, 3.9982250169996405, 4.055279547000282]], [34139, [0.021585251999567845, 0.18923547800022789, 6.737588544499886, 6.535931969999638, 1.1426961119996122, 2.927481376999822, 4.084116218000418, 4.796345232500244]], [34140, [0.02288981599986073, 0.18946403300014936, 4.901977846500358, 4.9086812650002685, 1.0369827390004502, 2.9462964719996307, 3.8842646690000038, 4.125112634999823]], [34141, [0.02283817999978055, 0.18943942300029448, 4.227935298000375, 5.250737195499823, 1.1300016149998555, 2.9527129660000355, 3.9079445209999903, 4.206512706000012]], [34155, [0.02250768349995269, 0.18915184700017562, 5.085128879999502, 5.106547033000425, 1.1202172154999062, 3.0916373119998752, 3.7006019565001225, 4.176256558000205]], [34158, [0.022577468500003306, 0.18936516099984146, 4.897060346999751, 5.548095727000145, 1.092709123000077, 2.970390075000523, 4.1461177379997025, 3.6277260030001344]], [34160, [0.022829148000255373, 0.1803743355003462, 4.996524258000136, 4.95579465100036, 1.0305067530002816, 2.9800310109994825, 3.572270988499895, 4.155317227000523]], [34162, [0.023230360499837843, 0.18967650499962474, 4.277101779000077, 4.935574182499749, 1.0229312695000772, 3.00213876899943, 3.6338864714998635, 4.147057948500333]], [34164, [0.02202568299981067, 0.1899807609997879, 5.437485297999956, 5.821437818999584, 1.1260430444999656, 2.8871156069999415, 4.132045049000226, 3.531279477499538]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.time_predict.json index b8ccdda67f..298eac0da2 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.0030169748749813152, 0.0030997149999620888, 0.001925429333368811, 0.002128827900105534, 0.007595465750000585, 0.007624496000062209, 0.005059357999925851, 0.0050641541668786285]], [34115, [0.0034455609999592225, 0.0030973771250728532, 0.0019135443333955966, 0.001959551333281221, 0.0077340845000435365, 0.007776695250186094, 0.005069868333369717, 0.00626804124976843]], [34120, [0.003087647374968583, 0.0030104119998668466, 0.0019054025000665813, 0.00191010391661924, 0.007001277250083149, 0.00700198649997219, 0.0063410637499146105, 0.006132296000032511]], [34126, [0.0032651608333556697, 0.0030447791251617673, 0.0018959520833353358, 0.0018729491666817921, 0.007418960750101178, 0.010146493500087672, 0.005074696249948829, 0.005076008333314045]], [34139, [0.0032878298334253486, 0.0029951763750659666, 0.0019051904166644817, 0.0018981729998965116, 0.006960681249665868, 0.00913858274998347, 0.006311489750032706, 0.006220015249937205]], [34140, [0.003280371333251727, 0.0030387254998913704, 0.0018779903333173327, 0.0019208724166522493, 0.007021301500117261, 0.007012418000158505, 0.004617041499993016, 0.004606026999984655]], [34141, [0.0030451823333047896, 0.003141248874953817, 0.0019741656666762233, 0.0019412794999880134, 0.007860078749899913, 0.00786672300000646, 0.005096859833429335, 0.00509592174989848]], [34155, [0.0033058421666585973, 0.003137772124887306, 0.0018953181666650685, 0.0019295214166656176, 0.007062973249958304, 0.007086437499992826, 0.0046423243332659085, 0.004628394333394681]], [34158, [0.003230687166554465, 0.0031203945001152533, 0.001920489499980249, 0.0019658238332643423, 0.00791751475003366, 0.007908693750096063, 0.005171990000008009, 0.005171911750039726]], [34160, [0.0032651716666502275, 0.0031353644999398966, 0.001967150333333241, 0.0019417085833689876, 0.0076188405000721104, 0.007673486000157936, 0.005045570333398549, 0.006150585500108718]], [34162, [0.003247009166746769, 0.003149160375073734, 0.001882533583360176, 0.0019023586667117343, 0.007221017749998282, 0.010103955000431597, 0.006551339250108867, 0.006409718499980954]]] \ No newline at end of file +[[34113, [0.0030169748749813152, 0.0030997149999620888, 0.001925429333368811, 0.002128827900105534, 0.007595465750000585, 0.007624496000062209, 0.005059357999925851, 0.0050641541668786285]], [34115, [0.0034455609999592225, 0.0030973771250728532, 0.0019135443333955966, 0.001959551333281221, 0.0077340845000435365, 0.007776695250186094, 0.005069868333369717, 0.00626804124976843]], [34120, [0.003087647374968583, 0.0030104119998668466, 0.0019054025000665813, 0.00191010391661924, 0.007001277250083149, 0.00700198649997219, 0.0063410637499146105, 0.006132296000032511]], [34126, [0.0032651608333556697, 0.0030447791251617673, 0.0018959520833353358, 0.0018729491666817921, 0.007418960750101178, 0.010146493500087672, 0.005074696249948829, 0.005076008333314045]], [34139, [0.0032878298334253486, 0.0029951763750659666, 0.0019051904166644817, 0.0018981729998965116, 0.006960681249665868, 0.00913858274998347, 0.006311489750032706, 0.006220015249937205]], [34140, [0.003280371333251727, 0.0030387254998913704, 0.0018779903333173327, 0.0019208724166522493, 0.007021301500117261, 0.007012418000158505, 0.004617041499993016, 0.004606026999984655]], [34141, [0.0030451823333047896, 0.003141248874953817, 0.0019741656666762233, 0.0019412794999880134, 0.007860078749899913, 0.00786672300000646, 0.005096859833429335, 0.00509592174989848]], [34155, [0.0033058421666585973, 0.003137772124887306, 0.0018953181666650685, 0.0019295214166656176, 0.007062973249958304, 0.007086437499992826, 0.0046423243332659085, 0.004628394333394681]], [34158, [0.003230687166554465, 0.0031203945001152533, 0.001920489499980249, 0.0019658238332643423, 0.00791751475003366, 0.007908693750096063, 0.005171990000008009, 0.005171911750039726]], [34160, [0.0032651716666502275, 0.0031353644999398966, 0.001967150333333241, 0.0019417085833689876, 0.0076188405000721104, 0.007673486000157936, 0.005045570333398549, 0.006150585500108718]], [34162, [0.003247009166746769, 0.003149160375073734, 0.001882533583360176, 0.0019023586667117343, 0.007221017749998282, 0.010103955000431597, 0.006551339250108867, 0.006409718499980954]], [34164, [0.0032742393333743776, 0.003068732999963686, 0.0019151165833288055, 0.0019205019166292914, 0.007063327249852591, 0.007030069500160607, 0.004619126499922762, 0.00612575324998943]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.track_test_score.json index 900f0a7bb9..81a55a6377 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.17424444924904262, 0.17424444924904262, 0.7839260955492333, 0.7839260955492333, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34115, [0.1725673885723084, 0.1725673885723084, 0.7826281819158617, 0.7826281819158617, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34120, [0.17421305525041922, 0.17421305525041922, 0.7782283339160001, 0.7782283339160001, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34126, [0.17518087150125433, 0.17518087150125433, 0.7790245490509625, 0.7790245490509625, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34139, [0.17168436462627806, 0.17168436462627806, 0.7793331027990112, 0.7793331027990112, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34140, [0.17586317751193295, 0.17586317751193295, 0.7711664672278389, 0.7711664672278389, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34141, [0.1722671648834762, 0.1722671648834762, 0.7715538523675664, 0.7715538523675664, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34155, [0.1730781546219734, 0.1730781546219734, 0.7764414429199678, 0.7764414429199678, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34158, [0.17280838299138498, 0.17280838299138498, 0.7633507225162636, 0.7633507225162636, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34160, [0.17531390370710556, 0.17531390370710556, 0.7851940045969401, 0.7851940045969401, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34162, [0.17421318660606197, 0.17421318660606197, 0.7751237470519855, 0.7751237470519855, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]]] \ No newline at end of file +[[34113, [0.17424444924904262, 0.17424444924904262, 0.7839260955492333, 0.7839260955492333, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34115, [0.1725673885723084, 0.1725673885723084, 0.7826281819158617, 0.7826281819158617, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34120, [0.17421305525041922, 0.17421305525041922, 0.7782283339160001, 0.7782283339160001, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34126, [0.17518087150125433, 0.17518087150125433, 0.7790245490509625, 0.7790245490509625, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34139, [0.17168436462627806, 0.17168436462627806, 0.7793331027990112, 0.7793331027990112, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34140, [0.17586317751193295, 0.17586317751193295, 0.7711664672278389, 0.7711664672278389, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34141, [0.1722671648834762, 0.1722671648834762, 0.7715538523675664, 0.7715538523675664, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34155, [0.1730781546219734, 0.1730781546219734, 0.7764414429199678, 0.7764414429199678, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34158, [0.17280838299138498, 0.17280838299138498, 0.7633507225162636, 0.7633507225162636, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34160, [0.17531390370710556, 0.17531390370710556, 0.7851940045969401, 0.7851940045969401, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34162, [0.17421318660606197, 0.17421318660606197, 0.7751237470519855, 0.7751237470519855, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]], [34164, [0.17421675376024606, 0.17421675376024606, 0.7813306063625303, 0.7813306063625303, 0.06538461538461539, 0.06538461538461539, 0.5765140080078162, 0.5765140080078162]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.track_train_score.json index 186c35d32c..b42a72eb3f 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.1799443704819773, 0.1799443704819773, 0.8028301804376747, 0.8028301804376747, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34115, [0.17854810855256653, 0.17854810855256653, 0.7944815400224952, 0.7944815400224952, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34120, [0.17846267704756377, 0.17846267704756377, 0.7959053245282692, 0.7959053245282692, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34126, [0.18040602937700362, 0.18040602937700362, 0.8000414973329711, 0.8000414973329711, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34139, [0.17873924713291384, 0.17873924713291384, 0.8006044291158562, 0.8006044291158562, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34140, [0.1804109052605111, 0.1804109052605111, 0.79979023767034, 0.79979023767034, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34141, [0.17929053664035507, 0.17929053664035507, 0.7999207089718164, 0.7999207089718164, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34155, [0.17918916423043427, 0.17918916423043427, 0.7974778501715544, 0.7974778501715544, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34158, [0.17900956836321424, 0.17900956836321424, 0.7950849178989723, 0.7950849178989723, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34160, [0.17761102700236397, 0.17761102700236397, 0.8002572686597246, 0.8002572686597246, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34162, [0.18059127186352428, 0.18059127186352428, 0.7987268755720667, 0.7987268755720667, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]]] \ No newline at end of file +[[34113, [0.1799443704819773, 0.1799443704819773, 0.8028301804376747, 0.8028301804376747, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34115, [0.17854810855256653, 0.17854810855256653, 0.7944815400224952, 0.7944815400224952, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34120, [0.17846267704756377, 0.17846267704756377, 0.7959053245282692, 0.7959053245282692, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34126, [0.18040602937700362, 0.18040602937700362, 0.8000414973329711, 0.8000414973329711, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34139, [0.17873924713291384, 0.17873924713291384, 0.8006044291158562, 0.8006044291158562, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34140, [0.1804109052605111, 0.1804109052605111, 0.79979023767034, 0.79979023767034, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34141, [0.17929053664035507, 0.17929053664035507, 0.7999207089718164, 0.7999207089718164, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34155, [0.17918916423043427, 0.17918916423043427, 0.7974778501715544, 0.7974778501715544, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34158, [0.17900956836321424, 0.17900956836321424, 0.7950849178989723, 0.7950849178989723, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34160, [0.17761102700236397, 0.17761102700236397, 0.8002572686597246, 0.8002572686597246, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34162, [0.18059127186352428, 0.18059127186352428, 0.7987268755720667, 0.7987268755720667, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]], [34164, [0.17947291893890438, 0.17947291893890438, 0.7992028148325083, 0.7992028148325083, 0.0681998556998557, 0.0681998556998557, 0.6908414295256007, 0.6908414295256007]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.peakmem_fit.json index c19324d3a3..d77055e538 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [463446016.0, 825294848.0, 463634432.0, 472313856.0, 466915328.0, 472276992.0, 472289280.0, 192696320.0, null, 1270927360.0, 193785856.0, 192696320.0, 158105600.0, 158093312.0]], [34115, [463544320.0, 824979456.0, 463609856.0, 472305664.0, 466735104.0, 472260608.0, 472252416.0, 192327680.0, null, 1270599680.0, 193761280.0, 192311296.0, 157974528.0, 157995008.0]], [34120, [463491072.0, 824897536.0, 463495168.0, 472338432.0, 466767872.0, 472252416.0, 472252416.0, 192385024.0, null, 1270849536.0, 193720320.0, 192389120.0, 158019584.0, 158003200.0]], [34126, [463728640.0, 825389056.0, 463724544.0, 472510464.0, 467001344.0, 472449024.0, 472453120.0, 192503808.0, null, 1270857728.0, 193781760.0, 192688128.0, 157933568.0, 157929472.0]], [34139, [463466496.0, 824946688.0, 463470592.0, 472424448.0, 466796544.0, 472236032.0, 472236032.0, 192438272.0, null, 1270767616.0, 193822720.0, 192454656.0, 157659136.0, 157659136.0]], [34140, [463138816.0, 824672256.0, 463269888.0, 472223744.0, 466681856.0, 472080384.0, 472076288.0, 192503808.0, null, 1270616064.0, 193658880.0, 192495616.0, 157782016.0, 157761536.0]], [34141, [463581184.0, 825430016.0, 463773696.0, 472616960.0, 467050496.0, 472371200.0, 472375296.0, 192626688.0, null, 1271029760.0, 193929216.0, 192634880.0, 158007296.0, 157999104.0]], [34155, [463597568.0, 825061376.0, 463593472.0, 472326144.0, 466923520.0, 472326144.0, 472330240.0, 192663552.0, null, 1270870016.0, 193785856.0, 192663552.0, 157974528.0, 157945856.0]], [34158, [463478784.0, 824987648.0, 463486976.0, 472338432.0, 466735104.0, 472281088.0, 472281088.0, 192278528.0, null, 1270673408.0, 193568768.0, 192278528.0, 157974528.0, 157966336.0]], [34160, [463572992.0, 825110528.0, 463593472.0, 472485888.0, 466853888.0, 472178688.0, 472178688.0, 192450560.0, null, 1270865920.0, 193798144.0, 192475136.0, 157962240.0, 157949952.0]], [34162, [463560704.0, 825126912.0, 463560704.0, 472301568.0, 466862080.0, 472354816.0, 472354816.0, 192528384.0, null, 1270771712.0, 193634304.0, 192344064.0, 157937664.0, 157958144.0]]] \ No newline at end of file +[[34113, [463446016.0, 825294848.0, 463634432.0, 472313856.0, 466915328.0, 472276992.0, 472289280.0, 192696320.0, null, 1270927360.0, 193785856.0, 192696320.0, 158105600.0, 158093312.0]], [34115, [463544320.0, 824979456.0, 463609856.0, 472305664.0, 466735104.0, 472260608.0, 472252416.0, 192327680.0, null, 1270599680.0, 193761280.0, 192311296.0, 157974528.0, 157995008.0]], [34120, [463491072.0, 824897536.0, 463495168.0, 472338432.0, 466767872.0, 472252416.0, 472252416.0, 192385024.0, null, 1270849536.0, 193720320.0, 192389120.0, 158019584.0, 158003200.0]], [34126, [463728640.0, 825389056.0, 463724544.0, 472510464.0, 467001344.0, 472449024.0, 472453120.0, 192503808.0, null, 1270857728.0, 193781760.0, 192688128.0, 157933568.0, 157929472.0]], [34139, [463466496.0, 824946688.0, 463470592.0, 472424448.0, 466796544.0, 472236032.0, 472236032.0, 192438272.0, null, 1270767616.0, 193822720.0, 192454656.0, 157659136.0, 157659136.0]], [34140, [463138816.0, 824672256.0, 463269888.0, 472223744.0, 466681856.0, 472080384.0, 472076288.0, 192503808.0, null, 1270616064.0, 193658880.0, 192495616.0, 157782016.0, 157761536.0]], [34141, [463581184.0, 825430016.0, 463773696.0, 472616960.0, 467050496.0, 472371200.0, 472375296.0, 192626688.0, null, 1271029760.0, 193929216.0, 192634880.0, 158007296.0, 157999104.0]], [34155, [463597568.0, 825061376.0, 463593472.0, 472326144.0, 466923520.0, 472326144.0, 472330240.0, 192663552.0, null, 1270870016.0, 193785856.0, 192663552.0, 157974528.0, 157945856.0]], [34158, [463478784.0, 824987648.0, 463486976.0, 472338432.0, 466735104.0, 472281088.0, 472281088.0, 192278528.0, null, 1270673408.0, 193568768.0, 192278528.0, 157974528.0, 157966336.0]], [34160, [463572992.0, 825110528.0, 463593472.0, 472485888.0, 466853888.0, 472178688.0, 472178688.0, 192450560.0, null, 1270865920.0, 193798144.0, 192475136.0, 157962240.0, 157949952.0]], [34162, [463560704.0, 825126912.0, 463560704.0, 472301568.0, 466862080.0, 472354816.0, 472354816.0, 192528384.0, null, 1270771712.0, 193634304.0, 192344064.0, 157937664.0, 157958144.0]], [34164, [463417344.0, 824877056.0, 463417344.0, 472137728.0, 466743296.0, 472195072.0, 472190976.0, 192499712.0, null, 1270681600.0, 193835008.0, 192512000.0, 157773824.0, 157745152.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.peakmem_predict.json index 8717ed59d1..c82be8bddb 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [282771456.0, 282693632.0, 282763264.0, 282763264.0, 282767360.0, 282697728.0, 282746880.0, 118349824.0, null, 118349824.0, 118349824.0, 118325248.0, 118349824.0, 118308864.0]], [34115, [283021312.0, 282931200.0, 283037696.0, 282947584.0, 282947584.0, 282947584.0, 283021312.0, 118804480.0, null, 119230464.0, 118870016.0, 118804480.0, 118661120.0, 118661120.0]], [34120, [282963968.0, 282980352.0, 282988544.0, 282988544.0, 282963968.0, 282935296.0, 282963968.0, 117731328.0, null, 117731328.0, 117665792.0, 117837824.0, 117665792.0, 117657600.0]], [34126, [283385856.0, 283361280.0, 283369472.0, 283365376.0, 283344896.0, 283283456.0, 283385856.0, 119676928.0, null, 119562240.0, 119443456.0, 119676928.0, 119611392.0, 119377920.0]], [34139, [283009024.0, 283021312.0, 283082752.0, 283009024.0, 282963968.0, 283009024.0, 283013120.0, 119332864.0, null, 119377920.0, 119377920.0, 119328768.0, 119377920.0, 119197696.0]], [34140, [282558464.0, 282451968.0, 282546176.0, 282451968.0, 282558464.0, 282320896.0, 282468352.0, 118124544.0, null, 118149120.0, 118099968.0, 118165504.0, 118099968.0, 118124544.0]], [34141, [283312128.0, 283287552.0, 283324416.0, 283287552.0, 283299840.0, 283209728.0, 283283456.0, 117821440.0, null, 117821440.0, 117952512.0, 117952512.0, 117886976.0, 117817344.0]], [34155, [282705920.0, 282636288.0, 282693632.0, 282632192.0, 282624000.0, 282624000.0, 282701824.0, 118509568.0, null, 118419456.0, 118353920.0, 118353920.0, 118427648.0, 118194176.0]], [34158, [282906624.0, 282943488.0, 282955776.0, 282918912.0, 282918912.0, 282972160.0, 282906624.0, 117788672.0, null, 117760000.0, 117760000.0, 117854208.0, 117854208.0, 117854208.0]], [34160, [282947584.0, 282685440.0, 282898432.0, 282972160.0, 282927104.0, 282816512.0, 282972160.0, 117735424.0, null, 117841920.0, 117669888.0, 117862400.0, 117862400.0, 117665792.0]], [34162, [282918912.0, 282763264.0, 282918912.0, 282935296.0, 282918912.0, 282763264.0, 282935296.0, 118640640.0, null, 118616064.0, 118525952.0, 118616064.0, 118624256.0, 118501376.0]]] \ No newline at end of file +[[34113, [282771456.0, 282693632.0, 282763264.0, 282763264.0, 282767360.0, 282697728.0, 282746880.0, 118349824.0, null, 118349824.0, 118349824.0, 118325248.0, 118349824.0, 118308864.0]], [34115, [283021312.0, 282931200.0, 283037696.0, 282947584.0, 282947584.0, 282947584.0, 283021312.0, 118804480.0, null, 119230464.0, 118870016.0, 118804480.0, 118661120.0, 118661120.0]], [34120, [282963968.0, 282980352.0, 282988544.0, 282988544.0, 282963968.0, 282935296.0, 282963968.0, 117731328.0, null, 117731328.0, 117665792.0, 117837824.0, 117665792.0, 117657600.0]], [34126, [283385856.0, 283361280.0, 283369472.0, 283365376.0, 283344896.0, 283283456.0, 283385856.0, 119676928.0, null, 119562240.0, 119443456.0, 119676928.0, 119611392.0, 119377920.0]], [34139, [283009024.0, 283021312.0, 283082752.0, 283009024.0, 282963968.0, 283009024.0, 283013120.0, 119332864.0, null, 119377920.0, 119377920.0, 119328768.0, 119377920.0, 119197696.0]], [34140, [282558464.0, 282451968.0, 282546176.0, 282451968.0, 282558464.0, 282320896.0, 282468352.0, 118124544.0, null, 118149120.0, 118099968.0, 118165504.0, 118099968.0, 118124544.0]], [34141, [283312128.0, 283287552.0, 283324416.0, 283287552.0, 283299840.0, 283209728.0, 283283456.0, 117821440.0, null, 117821440.0, 117952512.0, 117952512.0, 117886976.0, 117817344.0]], [34155, [282705920.0, 282636288.0, 282693632.0, 282632192.0, 282624000.0, 282624000.0, 282701824.0, 118509568.0, null, 118419456.0, 118353920.0, 118353920.0, 118427648.0, 118194176.0]], [34158, [282906624.0, 282943488.0, 282955776.0, 282918912.0, 282918912.0, 282972160.0, 282906624.0, 117788672.0, null, 117760000.0, 117760000.0, 117854208.0, 117854208.0, 117854208.0]], [34160, [282947584.0, 282685440.0, 282898432.0, 282972160.0, 282927104.0, 282816512.0, 282972160.0, 117735424.0, null, 117841920.0, 117669888.0, 117862400.0, 117862400.0, 117665792.0]], [34162, [282918912.0, 282763264.0, 282918912.0, 282935296.0, 282918912.0, 282763264.0, 282935296.0, 118640640.0, null, 118616064.0, 118525952.0, 118616064.0, 118624256.0, 118501376.0]], [34164, [283750400.0, 283410432.0, 283758592.0, 283541504.0, 282234880.0, 283410432.0, 282296320.0, 118022144.0, null, 117989376.0, 118153216.0, 117911552.0, 118022144.0, 118001664.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.time_fit.json index 6f3badd53e..88f18b740c 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [0.21185313449950627, 1.6796053879997999, 0.21279462999973475, 0.21486669499972777, 0.26787650749975, 30.418165931000658, 12.331982362999952, 0.16864914549978494, null, 5.503050796000025, 0.13556127299989384, 0.15476013050010806, 2.485522879999735, 2.1107342299992524]], [34115, [0.20943603800014898, 1.7008452365007543, 0.210531179499867, 0.2241566029997557, 0.2573270369994134, 27.79707271100051, 12.418715319000512, 0.1503713360002621, null, 5.401703473999987, 0.13236097999970298, 0.15077996499985602, 2.8592231420002463, 2.1074420749996534]], [34120, [0.21205779000001712, 1.739370547999897, 0.2088864580000518, 0.208901920000244, 0.25529594299950986, 28.340167938000377, 12.253944037999645, 0.15257755550010188, null, 5.353326000999914, 0.14484916049968888, 0.1653717669996695, 2.846489500500411, 2.102737858999717]], [34126, [0.21133133199964504, 1.6925767049997376, 0.21603624499948637, 0.2250377089999347, 0.25073622099989734, 28.233321622999938, 15.433453081000152, 0.1607515794999017, null, 5.45057535199976, 0.13863539800013314, 0.15998630949979997, 2.4907335749994672, 1.8563188389998686]], [34139, [0.21206282099956297, 1.669457125000008, 0.21078016699993896, 0.22253330200055643, 0.24378798299994742, 27.900293618999967, 12.297222299000168, 0.14997508550004568, null, 5.355670191000172, 0.1440651720004098, 0.16451315049971527, 2.4887197480002214, 2.1645896929994706]], [34140, [0.21205807649994313, 1.6865210849996402, 0.21435880999979418, 0.21786358000008477, 0.25312051350010734, 30.08396841800004, 14.008259172999715, 0.15510172350013818, null, 5.48533466400022, 0.13657450000027893, 0.1547802979998778, 2.827463781500228, 2.039725209000153]], [34141, [0.21309923950002485, 1.7053674980002143, 0.2089557754998168, 0.22759025449977344, 0.24965063700028622, 29.58076247899953, 13.966115232999982, 0.1519405519998145, null, 5.732561372999953, 0.14305818450020524, 0.16314652200026103, 2.8058143919997747, 2.0900424494998333]], [34155, [0.2124147519998587, 1.681041230000119, 0.20614241600014793, 0.21276441600002727, 0.2617466974998024, 29.879230076000567, 13.717861131000063, 0.16102431750050528, null, 5.63939210099943, 0.14124156999969273, 0.16086448650048624, 2.7046296130001792, 1.8710523590007142]], [34158, [0.21471719100009068, 1.7325437054996655, 0.2121094770000127, 0.2188873679997414, 0.2596492419997958, 29.974799196000276, 13.622493873999701, 0.1654095359999701, null, 5.661291766000431, 0.14596009749993755, 0.16542069300021467, 2.556482787999812, 2.0562051320002865]], [34160, [0.21724708699957773, 1.7101248240001041, 0.2130004420005207, 0.23086905099989963, 0.2629579569997986, 28.29990544500015, 13.991099267999743, 0.15769116749970635, null, 5.646227860999716, 0.1464644729999236, 0.1570656554999914, 2.8458652989997972, 2.123320797999895]], [34162, [0.22064827050007807, 1.7345931064996876, 0.2106260020004811, 0.22766223800044827, 0.26226041599966265, 27.906169908000265, 13.950564458999906, 0.16593966949994865, null, 5.612195816000167, 0.13576185200008695, 0.15465401300025405, 2.55703478399937, 1.8539671059998]]] \ No newline at end of file +[[34113, [0.21185313449950627, 1.6796053879997999, 0.21279462999973475, 0.21486669499972777, 0.26787650749975, 30.418165931000658, 12.331982362999952, 0.16864914549978494, null, 5.503050796000025, 0.13556127299989384, 0.15476013050010806, 2.485522879999735, 2.1107342299992524]], [34115, [0.20943603800014898, 1.7008452365007543, 0.210531179499867, 0.2241566029997557, 0.2573270369994134, 27.79707271100051, 12.418715319000512, 0.1503713360002621, null, 5.401703473999987, 0.13236097999970298, 0.15077996499985602, 2.8592231420002463, 2.1074420749996534]], [34120, [0.21205779000001712, 1.739370547999897, 0.2088864580000518, 0.208901920000244, 0.25529594299950986, 28.340167938000377, 12.253944037999645, 0.15257755550010188, null, 5.353326000999914, 0.14484916049968888, 0.1653717669996695, 2.846489500500411, 2.102737858999717]], [34126, [0.21133133199964504, 1.6925767049997376, 0.21603624499948637, 0.2250377089999347, 0.25073622099989734, 28.233321622999938, 15.433453081000152, 0.1607515794999017, null, 5.45057535199976, 0.13863539800013314, 0.15998630949979997, 2.4907335749994672, 1.8563188389998686]], [34139, [0.21206282099956297, 1.669457125000008, 0.21078016699993896, 0.22253330200055643, 0.24378798299994742, 27.900293618999967, 12.297222299000168, 0.14997508550004568, null, 5.355670191000172, 0.1440651720004098, 0.16451315049971527, 2.4887197480002214, 2.1645896929994706]], [34140, [0.21205807649994313, 1.6865210849996402, 0.21435880999979418, 0.21786358000008477, 0.25312051350010734, 30.08396841800004, 14.008259172999715, 0.15510172350013818, null, 5.48533466400022, 0.13657450000027893, 0.1547802979998778, 2.827463781500228, 2.039725209000153]], [34141, [0.21309923950002485, 1.7053674980002143, 0.2089557754998168, 0.22759025449977344, 0.24965063700028622, 29.58076247899953, 13.966115232999982, 0.1519405519998145, null, 5.732561372999953, 0.14305818450020524, 0.16314652200026103, 2.8058143919997747, 2.0900424494998333]], [34155, [0.2124147519998587, 1.681041230000119, 0.20614241600014793, 0.21276441600002727, 0.2617466974998024, 29.879230076000567, 13.717861131000063, 0.16102431750050528, null, 5.63939210099943, 0.14124156999969273, 0.16086448650048624, 2.7046296130001792, 1.8710523590007142]], [34158, [0.21471719100009068, 1.7325437054996655, 0.2121094770000127, 0.2188873679997414, 0.2596492419997958, 29.974799196000276, 13.622493873999701, 0.1654095359999701, null, 5.661291766000431, 0.14596009749993755, 0.16542069300021467, 2.556482787999812, 2.0562051320002865]], [34160, [0.21724708699957773, 1.7101248240001041, 0.2130004420005207, 0.23086905099989963, 0.2629579569997986, 28.29990544500015, 13.991099267999743, 0.15769116749970635, null, 5.646227860999716, 0.1464644729999236, 0.1570656554999914, 2.8458652989997972, 2.123320797999895]], [34162, [0.22064827050007807, 1.7345931064996876, 0.2106260020004811, 0.22766223800044827, 0.26226041599966265, 27.906169908000265, 13.950564458999906, 0.16593966949994865, null, 5.612195816000167, 0.13576185200008695, 0.15465401300025405, 2.55703478399937, 1.8539671059998]], [34164, [0.20792511150011705, 1.708551078000255, 0.20469984350029335, 0.2137333939999735, 0.2421331690002262, 28.640328184999817, 13.754953991000548, 0.16092295850012306, null, 5.425101769000321, 0.13053403300000355, 0.14823356799979592, 2.5003138410002066, 1.8639435100003539]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.time_predict.json index 12fcae09b5..230d773d28 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.026527937000082602, 0.024992409000333282, 0.026513054499901045, 0.026495306500237348, 0.02652786999988166, 0.02658093399986683, 0.02648378000003504, 0.007820044249911007, null, 0.007420642499710084, 0.007848094000109995, 0.007810131250153063, 0.00780966624984103, 0.00781316625011641]], [34115, [0.024462960499931796, 0.024408012499861798, 0.02506879700013087, 0.0243502405005529, 0.024278559999856952, 0.02421305800044138, 0.024504684000476118, 0.00690506199975971, null, 0.006992351000008057, 0.006894763250102187, 0.006976645749773525, 0.0069201109999994515, 0.00703718349996052]], [34120, [0.025623038000048837, 0.026851099499708653, 0.025349910500153783, 0.025405548000435374, 0.025324631999410485, 0.026986727500116103, 0.025355314499847736, 0.0069791827500012005, null, 0.0069860467501712264, 0.0070004500000777625, 0.006994555749997744, 0.006991890500103182, 0.006980292999969606]], [34126, [0.025724023999828205, 0.02432554600000003, 0.024485530499987362, 0.02589176299989049, 0.02593459699937739, 0.0260511885003325, 0.026083826499871066, 0.007081570999844189, null, 0.006983072250022815, 0.006967789750206066, 0.008136177000324096, 0.007338257499895917, 0.008149580500230513]], [34139, [0.02585483950042544, 0.025850993999483762, 0.02445775400065031, 0.0258769444999416, 0.02592176400048629, 0.025848396500350646, 0.026006614999914746, 0.0077384387500387675, null, 0.007784515749790444, 0.007761987499861789, 0.007784232750054798, 0.007753127499881884, 0.007749445750050654]], [34140, [0.02546200550023059, 0.026705304000188335, 0.025243295000109356, 0.025216291499873478, 0.026718778000031307, 0.025281711999923573, 0.026698323500113474, 0.00783115875015028, null, 0.007106957750011134, 0.007052425499978199, 0.007043008499977077, 0.007035577750002631, 0.007035252000150649]], [34141, [0.025669699500213028, 0.024034036499870126, 0.02544052550001652, 0.025303761000031955, 0.02520277499979784, 0.025229465500160586, 0.025263847499445546, 0.00770285225007683, null, 0.007673829750046934, 0.0076984382501450455, 0.00765860525007156, 0.007748815249897234, 0.007707440250214859]], [34155, [0.02301971900033095, 0.023013675000129297, 0.022893750999628537, 0.023098215999652894, 0.02300098649948268, 0.02307260599991423, 0.024079770500065933, 0.006910126999855493, null, 0.006906221999997797, 0.006926024250105911, 0.006916292499909105, 0.006891628499943181, 0.006903494250082076]], [34158, [0.025745439500042266, 0.025743251999756467, 0.024389699500261486, 0.025844600500022352, 0.025757671000064875, 0.024367084999994404, 0.025824141000157397, 0.007772586749979382, null, 0.007771540749899941, 0.0077763515000697225, 0.007792984249817891, 0.00779436474999784, 0.007849871250073193]], [34160, [0.02529044699986116, 0.025584234500001912, 0.02541305399972771, 0.025335637000353017, 0.025326453000161564, 0.025330991500140954, 0.025620242500281165, 0.0078269419998378, null, 0.007807101750131551, 0.007447582999702718, 0.007105956000032165, 0.007557202999578294, 0.007019138750138154]], [34162, [0.02501278249974348, 0.024962192499970115, 0.024916054000186705, 0.024840090999987297, 0.02483691799989174, 0.024889193000490195, 0.025135125999895536, 0.0070363717500185885, null, 0.007006187999877511, 0.007800729499649606, 0.007547686000179965, 0.007046709249834748, 0.0070075784999517055]]] \ No newline at end of file +[[34113, [0.026527937000082602, 0.024992409000333282, 0.026513054499901045, 0.026495306500237348, 0.02652786999988166, 0.02658093399986683, 0.02648378000003504, 0.007820044249911007, null, 0.007420642499710084, 0.007848094000109995, 0.007810131250153063, 0.00780966624984103, 0.00781316625011641]], [34115, [0.024462960499931796, 0.024408012499861798, 0.02506879700013087, 0.0243502405005529, 0.024278559999856952, 0.02421305800044138, 0.024504684000476118, 0.00690506199975971, null, 0.006992351000008057, 0.006894763250102187, 0.006976645749773525, 0.0069201109999994515, 0.00703718349996052]], [34120, [0.025623038000048837, 0.026851099499708653, 0.025349910500153783, 0.025405548000435374, 0.025324631999410485, 0.026986727500116103, 0.025355314499847736, 0.0069791827500012005, null, 0.0069860467501712264, 0.0070004500000777625, 0.006994555749997744, 0.006991890500103182, 0.006980292999969606]], [34126, [0.025724023999828205, 0.02432554600000003, 0.024485530499987362, 0.02589176299989049, 0.02593459699937739, 0.0260511885003325, 0.026083826499871066, 0.007081570999844189, null, 0.006983072250022815, 0.006967789750206066, 0.008136177000324096, 0.007338257499895917, 0.008149580500230513]], [34139, [0.02585483950042544, 0.025850993999483762, 0.02445775400065031, 0.0258769444999416, 0.02592176400048629, 0.025848396500350646, 0.026006614999914746, 0.0077384387500387675, null, 0.007784515749790444, 0.007761987499861789, 0.007784232750054798, 0.007753127499881884, 0.007749445750050654]], [34140, [0.02546200550023059, 0.026705304000188335, 0.025243295000109356, 0.025216291499873478, 0.026718778000031307, 0.025281711999923573, 0.026698323500113474, 0.00783115875015028, null, 0.007106957750011134, 0.007052425499978199, 0.007043008499977077, 0.007035577750002631, 0.007035252000150649]], [34141, [0.025669699500213028, 0.024034036499870126, 0.02544052550001652, 0.025303761000031955, 0.02520277499979784, 0.025229465500160586, 0.025263847499445546, 0.00770285225007683, null, 0.007673829750046934, 0.0076984382501450455, 0.00765860525007156, 0.007748815249897234, 0.007707440250214859]], [34155, [0.02301971900033095, 0.023013675000129297, 0.022893750999628537, 0.023098215999652894, 0.02300098649948268, 0.02307260599991423, 0.024079770500065933, 0.006910126999855493, null, 0.006906221999997797, 0.006926024250105911, 0.006916292499909105, 0.006891628499943181, 0.006903494250082076]], [34158, [0.025745439500042266, 0.025743251999756467, 0.024389699500261486, 0.025844600500022352, 0.025757671000064875, 0.024367084999994404, 0.025824141000157397, 0.007772586749979382, null, 0.007771540749899941, 0.0077763515000697225, 0.007792984249817891, 0.00779436474999784, 0.007849871250073193]], [34160, [0.02529044699986116, 0.025584234500001912, 0.02541305399972771, 0.025335637000353017, 0.025326453000161564, 0.025330991500140954, 0.025620242500281165, 0.0078269419998378, null, 0.007807101750131551, 0.007447582999702718, 0.007105956000032165, 0.007557202999578294, 0.007019138750138154]], [34162, [0.02501278249974348, 0.024962192499970115, 0.024916054000186705, 0.024840090999987297, 0.02483691799989174, 0.024889193000490195, 0.025135125999895536, 0.0070363717500185885, null, 0.007006187999877511, 0.007800729499649606, 0.007547686000179965, 0.007046709249834748, 0.0070075784999517055]], [34164, [0.023540404500181467, 0.023424676000104228, 0.023478681000142387, 0.02355707649985561, 0.02345715849969565, 0.024676339000052394, 0.024905723500069143, 0.006921824250184727, null, 0.00687568399985139, 0.006869584000014584, 0.006873456749872275, 0.006874372749962276, 0.007714372250120505]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.track_test_score.json index 6d602c3701..154edf3a1a 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9564970784886038, null, 0.9564968154170669, 0.9564970770096821, 0.9564970784886038, 0.9564944499717806, 0.9564947635236616]], [34115, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9563715506926687, null, 0.9563711192716627, 0.9563715545346079, 0.9563715506926687, 0.9563727415177208, 0.9563728137236858]], [34120, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9558002761724455, null, 0.955800393121659, 0.9558002758379966, 0.9558002761724455, 0.9558044915370154, 0.9558047669110146]], [34126, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9553244420113426, null, 0.9553246672126484, 0.9553244415615649, 0.9553244420113426, 0.9553301856707963, 0.9553307186768387]], [34139, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9559830361140461, null, 0.9559826060845279, 0.9559830380236071, 0.9559830361140461, 0.9559844165495949, 0.9559848182490503]], [34140, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.957041999879731, null, 0.957041519047847, 0.9570419958484373, 0.957041999879731, 0.9570431678208173, 0.9570438611544951]], [34141, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9564296413459894, null, 0.9564292115958911, 0.9564296405040651, 0.9564296413459894, 0.9564306494512524, 0.9564308047541376]], [34155, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9557106041332453, null, 0.9557109785531411, 0.9557106076755238, 0.9557106041332453, 0.9557172706664903, 0.9557178373075856]], [34158, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9565186321840092, null, 0.9565184151299725, 0.9565186364059198, 0.9565186321840092, 0.956518653947269, 0.9565183595934064]], [34160, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9564573950261358, null, 0.9564576511098518, 0.9564573935953704, 0.9564573950261358, 0.9564581658450005, 0.9564581365547343]], [34162, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9572922673936104, null, 0.9572921849190216, 0.9572922709486784, 0.9572922673936104, 0.9572933357644464, 0.9572933519233949]]] \ No newline at end of file +[[34113, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9564970784886038, null, 0.9564968154170669, 0.9564970770096821, 0.9564970784886038, 0.9564944499717806, 0.9564947635236616]], [34115, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9563715506926687, null, 0.9563711192716627, 0.9563715545346079, 0.9563715506926687, 0.9563727415177208, 0.9563728137236858]], [34120, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9558002761724455, null, 0.955800393121659, 0.9558002758379966, 0.9558002761724455, 0.9558044915370154, 0.9558047669110146]], [34126, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9553244420113426, null, 0.9553246672126484, 0.9553244415615649, 0.9553244420113426, 0.9553301856707963, 0.9553307186768387]], [34139, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9559830361140461, null, 0.9559826060845279, 0.9559830380236071, 0.9559830361140461, 0.9559844165495949, 0.9559848182490503]], [34140, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.957041999879731, null, 0.957041519047847, 0.9570419958484373, 0.957041999879731, 0.9570431678208173, 0.9570438611544951]], [34141, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9564296413459894, null, 0.9564292115958911, 0.9564296405040651, 0.9564296413459894, 0.9564306494512524, 0.9564308047541376]], [34155, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9557106041332453, null, 0.9557109785531411, 0.9557106076755238, 0.9557106041332453, 0.9557172706664903, 0.9557178373075856]], [34158, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9565186321840092, null, 0.9565184151299725, 0.9565186364059198, 0.9565186321840092, 0.956518653947269, 0.9565183595934064]], [34160, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9564573950261358, null, 0.9564576511098518, 0.9564573935953704, 0.9564573950261358, 0.9564581658450005, 0.9564581365547343]], [34162, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9572922673936104, null, 0.9572921849190216, 0.9572922709486784, 0.9572922673936104, 0.9572933357644464, 0.9572933519233949]], [34164, [0.943399575027382, 0.9433995638980545, 0.943399575027382, 0.9433995757192792, 0.9433995989989826, 0.94339933719428, 0.9433995886080997, 0.9566293314237935, null, 0.9566294205918099, 0.9566293294813514, 0.9566293314237935, 0.9566329028965642, 0.9566330257922844]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.track_train_score.json index d073141500..c534bb33dc 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9657283257611523, null, 0.9657283289629223, 0.965728325494629, 0.9657283257611523, 0.9657247750491627, 0.9657247400283712]], [34115, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9658271880058364, null, 0.9658271907352718, 0.9658271880698462, 0.9658271880058364, 0.9658236285178574, 0.9658235966760852]], [34120, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9659079813120487, null, 0.9659079843178087, 0.9659079819503521, 0.9659079813120487, 0.9659044286064856, 0.9659043971478999]], [34126, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9660019585878454, null, 0.9660019618294015, 0.96600195870035, 0.9660019585878454, 0.9659984045263212, 0.9659983672830587]], [34139, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9661981833128318, null, 0.9661981861719297, 0.9661981830534357, 0.9661981833128318, 0.9661946355054181, 0.9661945988822396]], [34140, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9660236235419267, null, 0.9660236264601697, 0.9660236238465779, 0.9660236235419267, 0.966020066308675, 0.9660200286626738]], [34141, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9656959977001077, null, 0.965696000544036, 0.9656959975998555, 0.9656959977001077, 0.9656924442692604, 0.9656924106028936]], [34155, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9657697955095434, null, 0.9657697983977334, 0.9657697954278325, 0.9657697955095434, 0.9657662431371696, 0.9657662089839146]], [34158, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9657503908108693, null, 0.9657503937819513, 0.9657503907351586, 0.9657503908108693, 0.9657468425537499, 0.9657468070698678]], [34160, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9657976885189085, null, 0.9657976918399981, 0.9657976887741928, 0.9657976885189085, 0.9657941274189181, 0.9657940924662692]], [34162, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9658700486714885, null, 0.9658700514270092, 0.9658700486028667, 0.9658700486714885, 0.96586649214205, 0.9658664561748669]]] \ No newline at end of file +[[34113, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9657283257611523, null, 0.9657283289629223, 0.965728325494629, 0.9657283257611523, 0.9657247750491627, 0.9657247400283712]], [34115, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9658271880058364, null, 0.9658271907352718, 0.9658271880698462, 0.9658271880058364, 0.9658236285178574, 0.9658235966760852]], [34120, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9659079813120487, null, 0.9659079843178087, 0.9659079819503521, 0.9659079813120487, 0.9659044286064856, 0.9659043971478999]], [34126, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9660019585878454, null, 0.9660019618294015, 0.96600195870035, 0.9660019585878454, 0.9659984045263212, 0.9659983672830587]], [34139, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9661981833128318, null, 0.9661981861719297, 0.9661981830534357, 0.9661981833128318, 0.9661946355054181, 0.9661945988822396]], [34140, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9660236235419267, null, 0.9660236264601697, 0.9660236238465779, 0.9660236235419267, 0.966020066308675, 0.9660200286626738]], [34141, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9656959977001077, null, 0.965696000544036, 0.9656959975998555, 0.9656959977001077, 0.9656924442692604, 0.9656924106028936]], [34155, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9657697955095434, null, 0.9657697983977334, 0.9657697954278325, 0.9657697955095434, 0.9657662431371696, 0.9657662089839146]], [34158, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9657503908108693, null, 0.9657503937819513, 0.9657503907351586, 0.9657503908108693, 0.9657468425537499, 0.9657468070698678]], [34160, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9657976885189085, null, 0.9657976918399981, 0.9657976887741928, 0.9657976885189085, 0.9657941274189181, 0.9657940924662692]], [34162, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9658700486714885, null, 0.9658700514270092, 0.9658700486028667, 0.9658700486714885, 0.96586649214205, 0.9658664561748669]], [34164, [0.9444001571921127, 0.9444001571502235, 0.9444001571921127, 0.9444001572131616, 0.9444001571192623, 0.9444001419121766, 0.9444001543688754, 0.9657393826014592, null, 0.9657393858884632, 0.9657393826835505, 0.9657393826014592, 0.9657358295811385, 0.9657357928601014]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.peakmem_fit.json index 4886b57c68..576c0f4f10 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [160374784.0, 87773184.0]], [34115, [159277056.0, 88649728.0]], [34120, [159072256.0, 87302144.0]], [34126, [159158272.0, 87519232.0]], [34139, [159838208.0, 87887872.0]], [34140, [159047680.0, 88330240.0]], [34141, [160071680.0, 87830528.0]], [34155, [160317440.0, 87642112.0]], [34158, [159236096.0, 87293952.0]], [34160, [159510528.0, 88608768.0]], [34162, [159371264.0, 87834624.0]]] \ No newline at end of file +[[34113, [160374784.0, 87773184.0]], [34115, [159277056.0, 88649728.0]], [34120, [159072256.0, 87302144.0]], [34126, [159158272.0, 87519232.0]], [34139, [159838208.0, 87887872.0]], [34140, [159047680.0, 88330240.0]], [34141, [160071680.0, 87830528.0]], [34155, [160317440.0, 87642112.0]], [34158, [159236096.0, 87293952.0]], [34160, [159510528.0, 88608768.0]], [34162, [159371264.0, 87834624.0]], [34164, [159637504.0, 88043520.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.peakmem_predict.json index 261bb0bc38..c843be6a8b 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [158670848.0, 86392832.0]], [34115, [158322688.0, 86220800.0]], [34120, [158023680.0, 85987328.0]], [34126, [158253056.0, 86171648.0]], [34139, [158314496.0, 86339584.0]], [34140, [157917184.0, 85868544.0]], [34141, [158670848.0, 86511616.0]], [34155, [158498816.0, 86302720.0]], [34158, [157962240.0, 85852160.0]], [34160, [158425088.0, 86388736.0]], [34162, [158347264.0, 86282240.0]]] \ No newline at end of file +[[34113, [158670848.0, 86392832.0]], [34115, [158322688.0, 86220800.0]], [34120, [158023680.0, 85987328.0]], [34126, [158253056.0, 86171648.0]], [34139, [158314496.0, 86339584.0]], [34140, [157917184.0, 85868544.0]], [34141, [158670848.0, 86511616.0]], [34155, [158498816.0, 86302720.0]], [34158, [157962240.0, 85852160.0]], [34160, [158425088.0, 86388736.0]], [34162, [158347264.0, 86282240.0]], [34164, [158134272.0, 85889024.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.time_fit.json index 63751d7301..1ce7f9502b 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [5.785732121000365, 4.727221952500258]], [34115, [5.555846737999673, 4.399997176999932]], [34120, [5.7577098060000935, 4.371343242499734]], [34126, [5.407501024999874, 4.410115528999995]], [34139, [5.657023298999775, 4.390607579499829]], [34140, [5.715017427999555, 4.749195399499968]], [34141, [5.278649515999859, 4.383912037999835]], [34155, [5.705368566000288, 4.270766128000105]], [34158, [5.7074692440000945, 4.394337704500231]], [34160, [5.750299745999655, 4.412599603999297]], [34162, [5.435246809000091, 4.2374637789998815]]] \ No newline at end of file +[[34113, [5.785732121000365, 4.727221952500258]], [34115, [5.555846737999673, 4.399997176999932]], [34120, [5.7577098060000935, 4.371343242499734]], [34126, [5.407501024999874, 4.410115528999995]], [34139, [5.657023298999775, 4.390607579499829]], [34140, [5.715017427999555, 4.749195399499968]], [34141, [5.278649515999859, 4.383912037999835]], [34155, [5.705368566000288, 4.270766128000105]], [34158, [5.7074692440000945, 4.394337704500231]], [34160, [5.750299745999655, 4.412599603999297]], [34162, [5.435246809000091, 4.2374637789998815]], [34164, [5.735067309999977, 4.7365718404998916]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.time_predict.json index 1ca92bf177..ef2dd7352e 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.0107545430000755, 0.0024381890999393366]], [34115, [0.010852802000044903, 0.0021456225000292765]], [34120, [0.010439660999963962, 0.0021359264000238905]], [34126, [0.010292853500232013, 0.0021347601000343275]], [34139, [0.010691899500216095, 0.002448476499921526]], [34140, [0.010319746500044857, 0.002442390800024441]], [34141, [0.010260443000333908, 0.00215088189997914]], [34155, [0.01055697150013657, 0.0024598105000222855]], [34158, [0.010537201500028459, 0.0024371529999370977]], [34160, [0.01096846850032307, 0.002176722999956837]], [34162, [0.010649129999819706, 0.0024580297001193683]]] \ No newline at end of file +[[34113, [0.0107545430000755, 0.0024381890999393366]], [34115, [0.010852802000044903, 0.0021456225000292765]], [34120, [0.010439660999963962, 0.0021359264000238905]], [34126, [0.010292853500232013, 0.0021347601000343275]], [34139, [0.010691899500216095, 0.002448476499921526]], [34140, [0.010319746500044857, 0.002442390800024441]], [34141, [0.010260443000333908, 0.00215088189997914]], [34155, [0.01055697150013657, 0.0024598105000222855]], [34158, [0.010537201500028459, 0.0024371529999370977]], [34160, [0.01096846850032307, 0.002176722999956837]], [34162, [0.010649129999819706, 0.0024580297001193683]], [34164, [0.010338596500332642, 0.002448330699917278]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.track_test_score.json index e9874a977d..14e350af9f 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.9636293915848902, 0.9624027601066106]], [34115, [0.9636293915848902, 0.9626026395137807]], [34120, [0.9636293915848902, 0.9620813955968166]], [34126, [0.9636293915848902, 0.9610250012839451]], [34139, [0.9636293915848902, 0.9619097851850607]], [34140, [0.9636293915848902, 0.9613057951915162]], [34141, [0.9636293915848902, 0.9605402641124132]], [34155, [0.9636293915848902, 0.9612530137262341]], [34158, [0.9636293915848902, 0.9624028362301564]], [34160, [0.9636293915848902, 0.9614887790154821]], [34162, [0.9636293915848902, 0.9618417170356984]]] \ No newline at end of file +[[34113, [0.9636293915848902, 0.9624027601066106]], [34115, [0.9636293915848902, 0.9626026395137807]], [34120, [0.9636293915848902, 0.9620813955968166]], [34126, [0.9636293915848902, 0.9610250012839451]], [34139, [0.9636293915848902, 0.9619097851850607]], [34140, [0.9636293915848902, 0.9613057951915162]], [34141, [0.9636293915848902, 0.9605402641124132]], [34155, [0.9636293915848902, 0.9612530137262341]], [34158, [0.9636293915848902, 0.9624028362301564]], [34160, [0.9636293915848902, 0.9614887790154821]], [34162, [0.9636293915848902, 0.9618417170356984]], [34164, [0.9636293915848902, 0.962268737808276]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.track_train_score.json index 079c89e1ad..191f0e0dfd 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.9641785427097553, 0.9619355841349047]], [34115, [0.9641785427097553, 0.9619047558349845]], [34120, [0.9641785427097553, 0.9623006334213435]], [34126, [0.9641785427097553, 0.9620348265454428]], [34139, [0.9641785427097553, 0.961844894326911]], [34140, [0.9641785427097553, 0.9619595728495335]], [34141, [0.9641785427097553, 0.9619247755146642]], [34155, [0.9641785427097553, 0.9616997045225375]], [34158, [0.9641785427097553, 0.9618568027735543]], [34160, [0.9641785427097553, 0.9620010629451068]], [34162, [0.9641785427097553, 0.9615879835158823]]] \ No newline at end of file +[[34113, [0.9641785427097553, 0.9619355841349047]], [34115, [0.9641785427097553, 0.9619047558349845]], [34120, [0.9641785427097553, 0.9623006334213435]], [34126, [0.9641785427097553, 0.9620348265454428]], [34139, [0.9641785427097553, 0.961844894326911]], [34140, [0.9641785427097553, 0.9619595728495335]], [34141, [0.9641785427097553, 0.9619247755146642]], [34155, [0.9641785427097553, 0.9616997045225375]], [34158, [0.9641785427097553, 0.9618568027735543]], [34160, [0.9641785427097553, 0.9620010629451068]], [34162, [0.9641785427097553, 0.9615879835158823]], [34164, [0.9641785427097553, 0.9621822550639929]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.peakmem_fit.json index ba2b9e0aef..8fb1854ae8 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [89276416.0, 96989184.0]], [34115, [89120768.0, 97112064.0]], [34120, [88748032.0, 96579584.0]], [34126, [88784896.0, 96530432.0]], [34139, [88875008.0, 96407552.0]], [34140, [88952832.0, 97062912.0]], [34141, [89088000.0, 97079296.0]], [34155, [88965120.0, 96464896.0]], [34158, [89001984.0, 96133120.0]], [34160, [89018368.0, 96497664.0]], [34162, [89264128.0, 96927744.0]]] \ No newline at end of file +[[34113, [89276416.0, 96989184.0]], [34115, [89120768.0, 97112064.0]], [34120, [88748032.0, 96579584.0]], [34126, [88784896.0, 96530432.0]], [34139, [88875008.0, 96407552.0]], [34140, [88952832.0, 97062912.0]], [34141, [89088000.0, 97079296.0]], [34155, [88965120.0, 96464896.0]], [34158, [89001984.0, 96133120.0]], [34160, [89018368.0, 96497664.0]], [34162, [89264128.0, 96927744.0]], [34164, [88469504.0, 95989760.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.time_fit.json index 888961457b..e38a280c3a 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [6.8866077249995215, 3.287346090000028]], [34115, [6.398079502499968, 3.1800816280001527]], [34120, [6.352371390999906, 3.1843909919998623]], [34126, [6.823952748499778, 3.3756803279998167]], [34139, [7.348718904499947, 3.0746666800005187]], [34140, [6.126922135999848, 3.107337338999969]], [34141, [6.458831746500437, 3.1526409349999085]], [34155, [6.369614407999961, 3.2864330430002155]], [34158, [6.618332401999851, 3.2927622309998696]], [34160, [6.664801721499316, 3.145763741999872]], [34162, [6.222238675499739, 3.508111628000279]]] \ No newline at end of file +[[34113, [6.8866077249995215, 3.287346090000028]], [34115, [6.398079502499968, 3.1800816280001527]], [34120, [6.352371390999906, 3.1843909919998623]], [34126, [6.823952748499778, 3.3756803279998167]], [34139, [7.348718904499947, 3.0746666800005187]], [34140, [6.126922135999848, 3.107337338999969]], [34141, [6.458831746500437, 3.1526409349999085]], [34155, [6.369614407999961, 3.2864330430002155]], [34158, [6.618332401999851, 3.2927622309998696]], [34160, [6.664801721499316, 3.145763741999872]], [34162, [6.222238675499739, 3.508111628000279]], [34164, [6.496687881000071, 3.165360485000747]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.track_test_score.json index 87c18d5037..12743b1304 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.3218818006120378, 0.7243015766143799]], [34115, [0.3218818006120378, 0.7243015766143799]], [34120, [0.3218818006120378, 0.7243015766143799]], [34126, [0.3218818006120378, 0.7243015170097351]], [34139, [0.3218818006120378, 0.7243015170097351]], [34140, [0.3218818006120378, 0.7243015766143799]], [34141, [0.3218818006120378, 0.7243015766143799]], [34155, [0.3218818006120378, 0.7243015170097351]], [34158, [0.3218818006120378, 0.7243015766143799]], [34160, [0.3218818006120378, 0.7243015766143799]], [34162, [0.3218818006120378, 0.7243016362190247]]] \ No newline at end of file +[[34113, [0.3218818006120378, 0.7243015766143799]], [34115, [0.3218818006120378, 0.7243015766143799]], [34120, [0.3218818006120378, 0.7243015766143799]], [34126, [0.3218818006120378, 0.7243015170097351]], [34139, [0.3218818006120378, 0.7243015170097351]], [34140, [0.3218818006120378, 0.7243015766143799]], [34141, [0.3218818006120378, 0.7243015766143799]], [34155, [0.3218818006120378, 0.7243015170097351]], [34158, [0.3218818006120378, 0.7243015766143799]], [34160, [0.3218818006120378, 0.7243015766143799]], [34162, [0.3218818006120378, 0.7243016362190247]], [34164, [0.3218818006120378, 0.7243016362190247]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.track_train_score.json index 87c18d5037..12743b1304 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/manifold.TSNEBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.3218818006120378, 0.7243015766143799]], [34115, [0.3218818006120378, 0.7243015766143799]], [34120, [0.3218818006120378, 0.7243015766143799]], [34126, [0.3218818006120378, 0.7243015170097351]], [34139, [0.3218818006120378, 0.7243015170097351]], [34140, [0.3218818006120378, 0.7243015766143799]], [34141, [0.3218818006120378, 0.7243015766143799]], [34155, [0.3218818006120378, 0.7243015170097351]], [34158, [0.3218818006120378, 0.7243015766143799]], [34160, [0.3218818006120378, 0.7243015766143799]], [34162, [0.3218818006120378, 0.7243016362190247]]] \ No newline at end of file +[[34113, [0.3218818006120378, 0.7243015766143799]], [34115, [0.3218818006120378, 0.7243015766143799]], [34120, [0.3218818006120378, 0.7243015766143799]], [34126, [0.3218818006120378, 0.7243015170097351]], [34139, [0.3218818006120378, 0.7243015170097351]], [34140, [0.3218818006120378, 0.7243015766143799]], [34141, [0.3218818006120378, 0.7243015766143799]], [34155, [0.3218818006120378, 0.7243015170097351]], [34158, [0.3218818006120378, 0.7243015766143799]], [34160, [0.3218818006120378, 0.7243015766143799]], [34162, [0.3218818006120378, 0.7243016362190247]], [34164, [0.3218818006120378, 0.7243016362190247]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json index 9825d54247..5614257754 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json @@ -1 +1 @@ -[[34113, [668336128.0, 785555456.0, 751919104.0, 975503360.0, 254361600.0, 340193280.0, 247554048.0, 482254848.0, 1420054528.0, 1370476544.0, 569954304.0, 895205376.0, 187056128.0, 223531008.0, null, null]], [34115, [668540928.0, 776896512.0, 751300608.0, 1029971968.0, 254316544.0, 339771392.0, 247414784.0, 484433920.0, 1419939840.0, 1127518208.0, 569442304.0, 848465920.0, 186806272.0, 202366976.0, null, null]], [34120, [668020736.0, 785137664.0, 751063040.0, 1016090624.0, 253886464.0, 337154048.0, 247103488.0, 479784960.0, 1419505664.0, 1404891136.0, 569491456.0, 904749056.0, 186466304.0, 210542592.0, null, null]], [34126, [668520448.0, 784654336.0, 751128576.0, 1085104128.0, 254173184.0, 340148224.0, 247377920.0, 484265984.0, 1419546624.0, 1424683008.0, 569524224.0, 948514816.0, 186462208.0, 232296448.0, null, null]], [34139, [668700672.0, 785313792.0, 751448064.0, 1110732800.0, 254320640.0, 316485632.0, 247365632.0, 480030720.0, 1420107776.0, 1398951936.0, 569896960.0, 923725824.0, 186986496.0, 230006784.0, null, null]], [34140, [668307456.0, 787369984.0, 751022080.0, 1002995712.0, 253968384.0, 335732736.0, 247062528.0, 483684352.0, 1419821056.0, 1176707072.0, 569589760.0, 937299968.0, 186793984.0, 208961536.0, null, null]], [34141, [668733440.0, 785018880.0, 751386624.0, 1125871616.0, 254398464.0, 315953152.0, 247681024.0, 484757504.0, 1420042240.0, 1432952832.0, 569987072.0, 918892544.0, 186994688.0, 229142528.0, null, null]], [34155, [668364800.0, 785485824.0, 751468544.0, 1055166464.0, 254300160.0, 340434944.0, 247394304.0, 480092160.0, 1420173312.0, 1423020032.0, 569933824.0, 878006272.0, 187002880.0, 231632896.0, null, null]], [34158, [668123136.0, 785145856.0, 750841856.0, 1041350656.0, 254115840.0, 339578880.0, 247083008.0, 481964032.0, 1419554816.0, 1400074240.0, 569290752.0, 1030852608.0, 186638336.0, 232042496.0, null, null]], [34160, [668495872.0, 785223680.0, 751386624.0, 1062670336.0, 254255104.0, 329031680.0, 247427072.0, 479719424.0, 1420025856.0, 1372549120.0, 569917440.0, 1025478656.0, 186687488.0, 224710656.0, null, null]], [34162, [669143040.0, 787259392.0, 751419392.0, 1059225600.0, 254562304.0, 314036224.0, 247472128.0, 459751424.0, 1420161024.0, 1423708160.0, 569806848.0, 951877632.0, 186904576.0, 232235008.0, null, null]]] \ No newline at end of file +[[34113, [668336128.0, 785555456.0, 751919104.0, 975503360.0, 254361600.0, 340193280.0, 247554048.0, 482254848.0, 1420054528.0, 1370476544.0, 569954304.0, 895205376.0, 187056128.0, 223531008.0, null, null]], [34115, [668540928.0, 776896512.0, 751300608.0, 1029971968.0, 254316544.0, 339771392.0, 247414784.0, 484433920.0, 1419939840.0, 1127518208.0, 569442304.0, 848465920.0, 186806272.0, 202366976.0, null, null]], [34120, [668020736.0, 785137664.0, 751063040.0, 1016090624.0, 253886464.0, 337154048.0, 247103488.0, 479784960.0, 1419505664.0, 1404891136.0, 569491456.0, 904749056.0, 186466304.0, 210542592.0, null, null]], [34126, [668520448.0, 784654336.0, 751128576.0, 1085104128.0, 254173184.0, 340148224.0, 247377920.0, 484265984.0, 1419546624.0, 1424683008.0, 569524224.0, 948514816.0, 186462208.0, 232296448.0, null, null]], [34139, [668700672.0, 785313792.0, 751448064.0, 1110732800.0, 254320640.0, 316485632.0, 247365632.0, 480030720.0, 1420107776.0, 1398951936.0, 569896960.0, 923725824.0, 186986496.0, 230006784.0, null, null]], [34140, [668307456.0, 787369984.0, 751022080.0, 1002995712.0, 253968384.0, 335732736.0, 247062528.0, 483684352.0, 1419821056.0, 1176707072.0, 569589760.0, 937299968.0, 186793984.0, 208961536.0, null, null]], [34141, [668733440.0, 785018880.0, 751386624.0, 1125871616.0, 254398464.0, 315953152.0, 247681024.0, 484757504.0, 1420042240.0, 1432952832.0, 569987072.0, 918892544.0, 186994688.0, 229142528.0, null, null]], [34155, [668364800.0, 785485824.0, 751468544.0, 1055166464.0, 254300160.0, 340434944.0, 247394304.0, 480092160.0, 1420173312.0, 1423020032.0, 569933824.0, 878006272.0, 187002880.0, 231632896.0, null, null]], [34158, [668123136.0, 785145856.0, 750841856.0, 1041350656.0, 254115840.0, 339578880.0, 247083008.0, 481964032.0, 1419554816.0, 1400074240.0, 569290752.0, 1030852608.0, 186638336.0, 232042496.0, null, null]], [34160, [668495872.0, 785223680.0, 751386624.0, 1062670336.0, 254255104.0, 329031680.0, 247427072.0, 479719424.0, 1420025856.0, 1372549120.0, 569917440.0, 1025478656.0, 186687488.0, 224710656.0, null, null]], [34162, [669143040.0, 787259392.0, 751419392.0, 1059225600.0, 254562304.0, 314036224.0, 247472128.0, 459751424.0, 1420161024.0, 1423708160.0, 569806848.0, 951877632.0, 186904576.0, 232235008.0, null, null]], [34164, [668053504.0, 785264640.0, 750964736.0, 1138954240.0, 253886464.0, 339369984.0, 247021568.0, 484114432.0, 1419497472.0, 1422913536.0, 569413632.0, 916946944.0, 186437632.0, 236290048.0, null, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json index dd9eedbf5f..a39caab511 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json @@ -1 +1 @@ -[[34113, [1.096224562000316, 1.2717148649999217, 1.7372055489995546, 3.0944876929997918, 6.251819647000502, 2.1561904800000775, 3.741420676999951, 2.5387837090001995, 3.7623814050002693, 2.5860535255001196, 2.572236699000314, 2.1509490925000136, 1.2217094190000353, 1.3097745579998445, null, null]], [34115, [1.0695048229999884, 1.229621310499624, 1.6882419840003422, 3.0638965009998174, 7.326106210000489, 2.6127353550000407, 3.6838959485003215, 2.5615983639995648, 3.6781222139998135, 2.5125554669998564, 2.8184001115000683, 2.07176092949976, 1.2515521380000791, 1.3248098610001762, null, null]], [34120, [1.1102719669997896, 1.264443721999669, 1.7357375390001835, 3.0676942485001746, 7.2663820110001325, 2.6176616529996863, 3.7434728449998147, 2.56807752099985, 3.6751219170000695, 2.5367154650002703, 2.573155080000106, 2.125312206500439, 1.2423636699995768, 1.3079268389992649, null, null]], [34126, [1.0925308699997913, 1.2440795570000773, 1.7313295399999333, 3.0625505910002175, 6.331074235000415, 2.6389183350001986, 3.273471633000554, 2.51544324400038, 3.683950905000529, 2.6356486720005705, 2.792416732499987, 2.043854016000296, 1.2268449279999913, 1.304415371000232, null, null]], [34139, [1.1105031150000286, 1.254006827000012, 1.73283707399969, 2.9736858054998265, 7.331654244499532, 2.640486456999497, 3.7494715435000217, 2.5429624074999992, 4.090551203000359, 2.6264861139998175, 2.8107713819999844, 2.110986695000065, 1.2235690649999924, 1.30160834399976, null, null]], [34140, [1.0948987880001368, 1.235342427499745, 1.7526936910007862, 3.056231607999507, 6.400862219500141, 2.582848848500362, 3.3036505549998765, 2.5076290635001897, 3.6725709250004, 2.5003912019997188, 2.574084037999455, 2.11009425750035, 1.2445150995004042, 1.3270318210002188, null, null]], [34141, [1.1021281490002366, 1.2574313200002507, 1.756396832000064, 3.0083723765001196, 6.330721553499643, 2.6314126879997275, 3.2657474449997608, 2.161805773999731, 4.157499685999937, 2.6110114455000257, 2.7627851639995242, 2.041567500000383, 1.2255320979998032, 1.2938417824998396, null, null]], [34155, [1.073605965000752, 1.2598956550000366, 1.7201992589998554, 3.059747658499873, 6.304058708499724, 2.6364801750005427, 3.6852423965001435, 2.6577413439999873, 4.105421428000227, 2.527621685000213, 2.778998242999478, 1.8386873350000315, 1.2505110080001032, 1.2831330435001291, null, null]], [34158, [1.072992883000552, 1.246322556999985, 1.695426217000204, 3.0147993034997853, 6.433149155000137, 2.607085524000013, 3.511249164500441, 2.5391199230002712, 4.127793399999973, 2.6385916380004346, 2.8121597795002344, 2.0794828150001194, 1.242909857000086, 1.313895422999849, null, null]], [34160, [1.1190594754998529, 1.2531879289999779, 1.73917551500017, 3.0236446064996017, 7.17245846600008, 2.6138359160004256, 3.2657166680000955, 2.541567272499833, 4.0535275329993965, 2.605231241000183, 2.59981175700068, 1.8509852389997832, 1.2495580610002435, 1.3237213439997504, null, null]], [34162, [1.0880350199995519, 1.2533258899993598, 1.7032072130004963, 3.0919631700003265, 6.309624622000683, 2.623034252999787, 3.727726663500107, 2.5598424650002016, 3.8284464769994884, 2.6016378949998398, 2.5913589709998632, 2.0907891044998905, 1.2228554975004045, 1.306165883000176, null, null]]] \ No newline at end of file +[[34113, [1.096224562000316, 1.2717148649999217, 1.7372055489995546, 3.0944876929997918, 6.251819647000502, 2.1561904800000775, 3.741420676999951, 2.5387837090001995, 3.7623814050002693, 2.5860535255001196, 2.572236699000314, 2.1509490925000136, 1.2217094190000353, 1.3097745579998445, null, null]], [34115, [1.0695048229999884, 1.229621310499624, 1.6882419840003422, 3.0638965009998174, 7.326106210000489, 2.6127353550000407, 3.6838959485003215, 2.5615983639995648, 3.6781222139998135, 2.5125554669998564, 2.8184001115000683, 2.07176092949976, 1.2515521380000791, 1.3248098610001762, null, null]], [34120, [1.1102719669997896, 1.264443721999669, 1.7357375390001835, 3.0676942485001746, 7.2663820110001325, 2.6176616529996863, 3.7434728449998147, 2.56807752099985, 3.6751219170000695, 2.5367154650002703, 2.573155080000106, 2.125312206500439, 1.2423636699995768, 1.3079268389992649, null, null]], [34126, [1.0925308699997913, 1.2440795570000773, 1.7313295399999333, 3.0625505910002175, 6.331074235000415, 2.6389183350001986, 3.273471633000554, 2.51544324400038, 3.683950905000529, 2.6356486720005705, 2.792416732499987, 2.043854016000296, 1.2268449279999913, 1.304415371000232, null, null]], [34139, [1.1105031150000286, 1.254006827000012, 1.73283707399969, 2.9736858054998265, 7.331654244499532, 2.640486456999497, 3.7494715435000217, 2.5429624074999992, 4.090551203000359, 2.6264861139998175, 2.8107713819999844, 2.110986695000065, 1.2235690649999924, 1.30160834399976, null, null]], [34140, [1.0948987880001368, 1.235342427499745, 1.7526936910007862, 3.056231607999507, 6.400862219500141, 2.582848848500362, 3.3036505549998765, 2.5076290635001897, 3.6725709250004, 2.5003912019997188, 2.574084037999455, 2.11009425750035, 1.2445150995004042, 1.3270318210002188, null, null]], [34141, [1.1021281490002366, 1.2574313200002507, 1.756396832000064, 3.0083723765001196, 6.330721553499643, 2.6314126879997275, 3.2657474449997608, 2.161805773999731, 4.157499685999937, 2.6110114455000257, 2.7627851639995242, 2.041567500000383, 1.2255320979998032, 1.2938417824998396, null, null]], [34155, [1.073605965000752, 1.2598956550000366, 1.7201992589998554, 3.059747658499873, 6.304058708499724, 2.6364801750005427, 3.6852423965001435, 2.6577413439999873, 4.105421428000227, 2.527621685000213, 2.778998242999478, 1.8386873350000315, 1.2505110080001032, 1.2831330435001291, null, null]], [34158, [1.072992883000552, 1.246322556999985, 1.695426217000204, 3.0147993034997853, 6.433149155000137, 2.607085524000013, 3.511249164500441, 2.5391199230002712, 4.127793399999973, 2.6385916380004346, 2.8121597795002344, 2.0794828150001194, 1.242909857000086, 1.313895422999849, null, null]], [34160, [1.1190594754998529, 1.2531879289999779, 1.73917551500017, 3.0236446064996017, 7.17245846600008, 2.6138359160004256, 3.2657166680000955, 2.541567272499833, 4.0535275329993965, 2.605231241000183, 2.59981175700068, 1.8509852389997832, 1.2495580610002435, 1.3237213439997504, null, null]], [34162, [1.0880350199995519, 1.2533258899993598, 1.7032072130004963, 3.0919631700003265, 6.309624622000683, 2.623034252999787, 3.727726663500107, 2.5598424650002016, 3.8284464769994884, 2.6016378949998398, 2.5913589709998632, 2.0907891044998905, 1.2228554975004045, 1.306165883000176, null, null]], [34164, [1.1084115129997372, 1.241372282499924, 1.7287864840000111, 3.129223408999678, 6.324033079999936, 2.6631510420002087, 3.74481577250026, 2.4759092530002818, 3.787390147499991, 2.4835890959998324, 2.7595024449997254, 2.119749861499713, 1.2235831774996768, 1.3249360879999585, null, null]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.peakmem_crossval.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.peakmem_crossval.json index 65c0d07eb5..72cc2a27d5 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.peakmem_crossval.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.peakmem_crossval.json @@ -1 +1 @@ -[[34113, [218046464.0, 118632448.0]], [34115, [217903104.0, 118136832.0]], [34120, [217542656.0, 118091776.0]], [34126, [217755648.0, 118341632.0]], [34139, [218038272.0, 118169600.0]], [34140, [217804800.0, 118128640.0]], [34141, [218091520.0, 118374400.0]], [34155, [217985024.0, 118468608.0]], [34158, [217710592.0, 117874688.0]], [34160, [217960448.0, 118276096.0]], [34162, [218128384.0, 118403072.0]]] \ No newline at end of file +[[34113, [218046464.0, 118632448.0]], [34115, [217903104.0, 118136832.0]], [34120, [217542656.0, 118091776.0]], [34126, [217755648.0, 118341632.0]], [34139, [218038272.0, 118169600.0]], [34140, [217804800.0, 118128640.0]], [34141, [218091520.0, 118374400.0]], [34155, [217985024.0, 118468608.0]], [34158, [217710592.0, 117874688.0]], [34160, [217960448.0, 118276096.0]], [34162, [218128384.0, 118403072.0]], [34164, [217661440.0, 118079488.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.time_crossval.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.time_crossval.json index d64cb61b55..022064d641 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.time_crossval.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.time_crossval.json @@ -1 +1 @@ -[[34113, [64.2886444120004, 17.09262771000067]], [34115, [64.21327091200055, 17.30094022999947]], [34120, [64.08283332500014, 17.195363630999964]], [34126, [64.27279506600007, 17.233828422999977]], [34139, [57.47834499600049, 17.196938581999348]], [34140, [55.77678843800004, 17.397581309999623]], [34141, [63.216229812000165, 17.070054533000075]], [34155, [64.20923325100011, 16.2959160850005]], [34158, [64.43946394399973, 17.885456244000125]], [34160, [62.73974995699973, 17.364847056000144]], [34162, [57.223468524000054, 17.245325756000057]]] \ No newline at end of file +[[34113, [64.2886444120004, 17.09262771000067]], [34115, [64.21327091200055, 17.30094022999947]], [34120, [64.08283332500014, 17.195363630999964]], [34126, [64.27279506600007, 17.233828422999977]], [34139, [57.47834499600049, 17.196938581999348]], [34140, [55.77678843800004, 17.397581309999623]], [34141, [63.216229812000165, 17.070054533000075]], [34155, [64.20923325100011, 16.2959160850005]], [34158, [64.43946394399973, 17.885456244000125]], [34160, [62.73974995699973, 17.364847056000144]], [34162, [57.223468524000054, 17.245325756000057]], [34164, [57.03710744300042, 16.760784000000058]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.track_crossval.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.track_crossval.json index cb8a2749ef..d18486a045 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.track_crossval.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.CrossValidationBenchmark.track_crossval.json @@ -1 +1 @@ -[[34113, [0.9001555555555555, 0.9001555555555555]], [34115, [0.9001555555555555, 0.9001555555555555]], [34120, [0.9001555555555555, 0.9001555555555555]], [34126, [0.9001555555555555, 0.9001555555555555]], [34139, [0.9001555555555555, 0.9001555555555555]], [34140, [0.9001555555555555, 0.9001555555555555]], [34141, [0.9001555555555555, 0.9001555555555555]], [34155, [0.9001555555555555, 0.9001555555555555]], [34158, [0.9001555555555555, 0.9001555555555555]], [34160, [0.9001555555555555, 0.9001555555555555]], [34162, [0.9001555555555555, 0.9001555555555555]]] \ No newline at end of file +[[34113, [0.9001555555555555, 0.9001555555555555]], [34115, [0.9001555555555555, 0.9001555555555555]], [34120, [0.9001555555555555, 0.9001555555555555]], [34126, [0.9001555555555555, 0.9001555555555555]], [34139, [0.9001555555555555, 0.9001555555555555]], [34140, [0.9001555555555555, 0.9001555555555555]], [34141, [0.9001555555555555, 0.9001555555555555]], [34155, [0.9001555555555555, 0.9001555555555555]], [34158, [0.9001555555555555, 0.9001555555555555]], [34160, [0.9001555555555555, 0.9001555555555555]], [34162, [0.9001555555555555, 0.9001555555555555]], [34164, [0.9001555555555555, 0.9001555555555555]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.peakmem_fit.json index f38a3c02e7..bd9e8c86f0 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [95596544.0, 93147136.0]], [34115, [95379456.0, 92909568.0]], [34120, [94920704.0, 92553216.0]], [34126, [95195136.0, 92930048.0]], [34139, [95379456.0, 92917760.0]], [34140, [95145984.0, 92479488.0]], [34141, [95662080.0, 93159424.0]], [34155, [95436800.0, 92954624.0]], [34158, [95027200.0, 92598272.0]], [34160, [95338496.0, 92966912.0]], [34162, [95539200.0, 93138944.0]]] \ No newline at end of file +[[34113, [95596544.0, 93147136.0]], [34115, [95379456.0, 92909568.0]], [34120, [94920704.0, 92553216.0]], [34126, [95195136.0, 92930048.0]], [34139, [95379456.0, 92917760.0]], [34140, [95145984.0, 92479488.0]], [34141, [95662080.0, 93159424.0]], [34155, [95436800.0, 92954624.0]], [34158, [95027200.0, 92598272.0]], [34160, [95338496.0, 92966912.0]], [34162, [95539200.0, 93138944.0]], [34164, [95092736.0, 92602368.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.peakmem_predict.json index fa8cfc619d..a8d9fbbfd0 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [87896064.0, 87896064.0]], [34115, [87900160.0, 87900160.0]], [34120, [87318528.0, 87318528.0]], [34126, [87814144.0, 87683072.0]], [34139, [87703552.0, 87703552.0]], [34140, [87461888.0, 87461888.0]], [34141, [88137728.0, 88141824.0]], [34155, [87703552.0, 87703552.0]], [34158, [87498752.0, 87494656.0]], [34160, [87748608.0, 87744512.0]], [34162, [87937024.0, 87937024.0]]] \ No newline at end of file +[[34113, [87896064.0, 87896064.0]], [34115, [87900160.0, 87900160.0]], [34120, [87318528.0, 87318528.0]], [34126, [87814144.0, 87683072.0]], [34139, [87703552.0, 87703552.0]], [34140, [87461888.0, 87461888.0]], [34141, [88137728.0, 88141824.0]], [34155, [87703552.0, 87703552.0]], [34158, [87498752.0, 87494656.0]], [34160, [87748608.0, 87744512.0]], [34162, [87937024.0, 87937024.0]], [34164, [87429120.0, 87400448.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.time_fit.json index 6b20f4f9b7..6e9e31f0f3 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [374.4642131640012, 102.40908155500074]], [34115, [372.1445956989992, 102.37117459599904]], [34120, [344.9167734419998, 103.44403336799951]], [34126, [375.1419901519994, 101.97054501500133]], [34139, [346.896038814999, 104.49649032300113]], [34140, [386.8189775109995, 101.11131621200002]], [34141, [373.46130339499905, 102.00770049400126]], [34155, [349.34945297299964, 101.55457300200032]], [34158, [372.74220539200087, 102.56052423499932]], [34160, [350.47552635600096, 102.00490205000096]], [34162, [346.82019891100026, 103.23968204899938]]] \ No newline at end of file +[[34113, [374.4642131640012, 102.40908155500074]], [34115, [372.1445956989992, 102.37117459599904]], [34120, [344.9167734419998, 103.44403336799951]], [34126, [375.1419901519994, 101.97054501500133]], [34139, [346.896038814999, 104.49649032300113]], [34140, [386.8189775109995, 101.11131621200002]], [34141, [373.46130339499905, 102.00770049400126]], [34155, [349.34945297299964, 101.55457300200032]], [34158, [372.74220539200087, 102.56052423499932]], [34160, [350.47552635600096, 102.00490205000096]], [34162, [346.82019891100026, 103.23968204899938]], [34164, [345.57343498200044, 101.52767383900027]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.time_predict.json index d94bc68f2e..ba2837fdeb 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.06898502649983129, 0.06901015050061687]], [34115, [0.07129990399971575, 0.0702748479998263]], [34120, [0.07133637049992103, 0.07126558900017699]], [34126, [0.07144070350022957, 0.07091360399954283]], [34139, [0.07070325499989849, 0.0709344750011951]], [34140, [0.07095141599984345, 0.07095486849993904]], [34141, [0.07147129799977847, 0.07145856200077105]], [34155, [0.07084761799887929, 0.0708904334996987]], [34158, [0.07054813800004922, 0.0704705219995958]], [34160, [0.07115156249892607, 0.07110792549974576]], [34162, [0.05741952699918329, 0.0702970969996386]]] \ No newline at end of file +[[34113, [0.06898502649983129, 0.06901015050061687]], [34115, [0.07129990399971575, 0.0702748479998263]], [34120, [0.07133637049992103, 0.07126558900017699]], [34126, [0.07144070350022957, 0.07091360399954283]], [34139, [0.07070325499989849, 0.0709344750011951]], [34140, [0.07095141599984345, 0.07095486849993904]], [34141, [0.07147129799977847, 0.07145856200077105]], [34155, [0.07084761799887929, 0.0708904334996987]], [34158, [0.07054813800004922, 0.0704705219995958]], [34160, [0.07115156249892607, 0.07110792549974576]], [34162, [0.05741952699918329, 0.0702970969996386]], [34164, [0.07076135449915455, 0.07084873300027539]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.track_test_score.json index ae9c5527c3..e56b904fbf 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.8678060899936387, 0.8678060899936387]], [34115, [0.8678060899936387, 0.8678060899936387]], [34120, [0.8678060899936387, 0.8678060899936387]], [34126, [0.8678060899936387, 0.8678060899936387]], [34139, [0.8678060899936387, 0.8678060899936387]], [34140, [0.8678060899936387, 0.8678060899936387]], [34141, [0.8678060899936387, 0.8678060899936387]], [34155, [0.8678060899936387, 0.8678060899936387]], [34158, [0.8678060899936387, 0.8678060899936387]], [34160, [0.8678060899936387, 0.8678060899936387]], [34162, [0.8678060899936387, 0.8678060899936387]]] \ No newline at end of file +[[34113, [0.8678060899936387, 0.8678060899936387]], [34115, [0.8678060899936387, 0.8678060899936387]], [34120, [0.8678060899936387, 0.8678060899936387]], [34126, [0.8678060899936387, 0.8678060899936387]], [34139, [0.8678060899936387, 0.8678060899936387]], [34140, [0.8678060899936387, 0.8678060899936387]], [34141, [0.8678060899936387, 0.8678060899936387]], [34155, [0.8678060899936387, 0.8678060899936387]], [34158, [0.8678060899936387, 0.8678060899936387]], [34160, [0.8678060899936387, 0.8678060899936387]], [34162, [0.8678060899936387, 0.8678060899936387]], [34164, [0.8678060899936387, 0.8678060899936387]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.track_train_score.json index 5afd0886e2..3ecd3459d9 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/model_selection.GridSearchBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.9966662088870577, 0.9966662088870577]], [34115, [0.9966662088870577, 0.9966662088870577]], [34120, [0.9966662088870577, 0.9966662088870577]], [34126, [0.9966662088870577, 0.9966662088870577]], [34139, [0.9966662088870577, 0.9966662088870577]], [34140, [0.9966662088870577, 0.9966662088870577]], [34141, [0.9966662088870577, 0.9966662088870577]], [34155, [0.9966662088870577, 0.9966662088870577]], [34158, [0.9966662088870577, 0.9966662088870577]], [34160, [0.9966662088870577, 0.9966662088870577]], [34162, [0.9966662088870577, 0.9966662088870577]]] \ No newline at end of file +[[34113, [0.9966662088870577, 0.9966662088870577]], [34115, [0.9966662088870577, 0.9966662088870577]], [34120, [0.9966662088870577, 0.9966662088870577]], [34126, [0.9966662088870577, 0.9966662088870577]], [34139, [0.9966662088870577, 0.9966662088870577]], [34140, [0.9966662088870577, 0.9966662088870577]], [34141, [0.9966662088870577, 0.9966662088870577]], [34155, [0.9966662088870577, 0.9966662088870577]], [34158, [0.9966662088870577, 0.9966662088870577]], [34160, [0.9966662088870577, 0.9966662088870577]], [34162, [0.9966662088870577, 0.9966662088870577]], [34164, [0.9966662088870577, 0.9966662088870577]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json index 6199b4af65..a6ad456ca0 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [77602816.0, 77602816.0, 80912384.0, 80916480.0, 80019456.0, 79953920.0, 88498176.0, 88498176.0, 79970304.0, 80044032.0, 88313856.0, 88313856.0]], [34115, [77434880.0, 77410304.0, 80941056.0, 80941056.0, 80322560.0, 80322560.0, 88408064.0, 88408064.0, 80261120.0, 80261120.0, 88203264.0, 88203264.0]], [34120, [77082624.0, 77062144.0, 80592896.0, 80613376.0, 79921152.0, 79921152.0, 88043520.0, 88043520.0, 79888384.0, 79888384.0, 87871488.0, 87871488.0]], [34126, [77258752.0, 77283328.0, 80769024.0, 80789504.0, 80216064.0, 80228352.0, 88313856.0, 88313856.0, 80183296.0, 80183296.0, 88125440.0, 88125440.0]], [34139, [77316096.0, 77291520.0, 80572416.0, 80781312.0, 79687680.0, 79671296.0, 88342528.0, 88342528.0, 79667200.0, 79642624.0, 88121344.0, 88121344.0]], [34140, [77131776.0, 77111296.0, 80609280.0, 80621568.0, 79683584.0, 79683584.0, 88104960.0, 88104960.0, 79753216.0, 79626240.0, 87965696.0, 87965696.0]], [34141, [77524992.0, 77520896.0, 81027072.0, 81059840.0, 80527360.0, 80515072.0, 88563712.0, 88559616.0, 80420864.0, 80359424.0, 88375296.0, 88371200.0]], [34155, [77287424.0, 77279232.0, 80805888.0, 80785408.0, 79953920.0, 79888384.0, 88350720.0, 88358912.0, 79794176.0, 79794176.0, 88117248.0, 88125440.0]], [34158, [77115392.0, 77123584.0, 80625664.0, 80625664.0, 79904768.0, 79843328.0, 88133632.0, 88129536.0, 79749120.0, 79814656.0, 87957504.0, 87957504.0]], [34160, [77336576.0, 77320192.0, 80855040.0, 80842752.0, 80244736.0, 80244736.0, 88358912.0, 88358912.0, 80216064.0, 80216064.0, 88195072.0, 88195072.0]], [34162, [77516800.0, 77508608.0, 81018880.0, 81022976.0, 80392192.0, 80392192.0, 88539136.0, 88539136.0, 80379904.0, 80367616.0, 88383488.0, 88383488.0]]] \ No newline at end of file +[[34113, [77602816.0, 77602816.0, 80912384.0, 80916480.0, 80019456.0, 79953920.0, 88498176.0, 88498176.0, 79970304.0, 80044032.0, 88313856.0, 88313856.0]], [34115, [77434880.0, 77410304.0, 80941056.0, 80941056.0, 80322560.0, 80322560.0, 88408064.0, 88408064.0, 80261120.0, 80261120.0, 88203264.0, 88203264.0]], [34120, [77082624.0, 77062144.0, 80592896.0, 80613376.0, 79921152.0, 79921152.0, 88043520.0, 88043520.0, 79888384.0, 79888384.0, 87871488.0, 87871488.0]], [34126, [77258752.0, 77283328.0, 80769024.0, 80789504.0, 80216064.0, 80228352.0, 88313856.0, 88313856.0, 80183296.0, 80183296.0, 88125440.0, 88125440.0]], [34139, [77316096.0, 77291520.0, 80572416.0, 80781312.0, 79687680.0, 79671296.0, 88342528.0, 88342528.0, 79667200.0, 79642624.0, 88121344.0, 88121344.0]], [34140, [77131776.0, 77111296.0, 80609280.0, 80621568.0, 79683584.0, 79683584.0, 88104960.0, 88104960.0, 79753216.0, 79626240.0, 87965696.0, 87965696.0]], [34141, [77524992.0, 77520896.0, 81027072.0, 81059840.0, 80527360.0, 80515072.0, 88563712.0, 88559616.0, 80420864.0, 80359424.0, 88375296.0, 88371200.0]], [34155, [77287424.0, 77279232.0, 80805888.0, 80785408.0, 79953920.0, 79888384.0, 88350720.0, 88358912.0, 79794176.0, 79794176.0, 88117248.0, 88125440.0]], [34158, [77115392.0, 77123584.0, 80625664.0, 80625664.0, 79904768.0, 79843328.0, 88133632.0, 88129536.0, 79749120.0, 79814656.0, 87957504.0, 87957504.0]], [34160, [77336576.0, 77320192.0, 80855040.0, 80842752.0, 80244736.0, 80244736.0, 88358912.0, 88358912.0, 80216064.0, 80216064.0, 88195072.0, 88195072.0]], [34162, [77516800.0, 77508608.0, 81018880.0, 81022976.0, 80392192.0, 80392192.0, 88539136.0, 88539136.0, 80379904.0, 80367616.0, 88383488.0, 88383488.0]], [34164, [76894208.0, 77119488.0, 80396288.0, 80367616.0, 79597568.0, 79532032.0, 88010752.0, 88010752.0, 79572992.0, 79507456.0, 87838720.0, 87838720.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json index ade1f34181..d35786e10f 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [88272896.0, 88420352.0, 93073408.0, 93372416.0, 81678336.0, 84414464.0, 91570176.0, 91295744.0, 81465344.0, 84275200.0, 91119616.0, 90718208.0]], [34115, [88006656.0, 88039424.0, 92938240.0, 93061120.0, 81412096.0, 83898368.0, 91095040.0, 91222016.0, 81154048.0, 83685376.0, 90845184.0, 90808320.0]], [34120, [87511040.0, 87773184.0, 92778496.0, 92508160.0, 81154048.0, 83300352.0, 90624000.0, 90095616.0, 81022976.0, 83464192.0, 90509312.0, 90562560.0]], [34126, [88285184.0, 88424448.0, 93503488.0, 93233152.0, 81457152.0, 83808256.0, 91340800.0, 90640384.0, 81281024.0, 83705856.0, 90935296.0, 90906624.0]], [34139, [87896064.0, 88313856.0, 92823552.0, 92884992.0, 81485824.0, 83959808.0, 91181056.0, 90738688.0, 81338368.0, 83820544.0, 90742784.0, 90779648.0]], [34140, [87769088.0, 87715840.0, 92631040.0, 92426240.0, 81203200.0, 83927040.0, 90927104.0, 90984448.0, 80965632.0, 83734528.0, 90427392.0, 90333184.0]], [34141, [88440832.0, 88457216.0, 93794304.0, 93409280.0, 81772544.0, 84475904.0, 91406336.0, 90836992.0, 81530880.0, 84328448.0, 91226112.0, 91230208.0]], [34155, [87990272.0, 88023040.0, 93245440.0, 92942336.0, 81543168.0, 83931136.0, 91095040.0, 90468352.0, 81334272.0, 83795968.0, 90902528.0, 90947584.0]], [34158, [87674880.0, 87814144.0, 92602368.0, 92622848.0, 81190912.0, 83570688.0, 90959872.0, 90263552.0, 80936960.0, 83382272.0, 90443776.0, 90406912.0]], [34160, [88145920.0, 88199168.0, 92991488.0, 93175808.0, 81477632.0, 83685376.0, 91049984.0, 90902528.0, 81285120.0, 83599360.0, 90931200.0, 90951680.0]], [34162, [88031232.0, 88334336.0, 92934144.0, 93036544.0, 81612800.0, 84258816.0, 91168768.0, 90783744.0, 81408000.0, 84103168.0, 90726400.0, 90882048.0]]] \ No newline at end of file +[[34113, [88272896.0, 88420352.0, 93073408.0, 93372416.0, 81678336.0, 84414464.0, 91570176.0, 91295744.0, 81465344.0, 84275200.0, 91119616.0, 90718208.0]], [34115, [88006656.0, 88039424.0, 92938240.0, 93061120.0, 81412096.0, 83898368.0, 91095040.0, 91222016.0, 81154048.0, 83685376.0, 90845184.0, 90808320.0]], [34120, [87511040.0, 87773184.0, 92778496.0, 92508160.0, 81154048.0, 83300352.0, 90624000.0, 90095616.0, 81022976.0, 83464192.0, 90509312.0, 90562560.0]], [34126, [88285184.0, 88424448.0, 93503488.0, 93233152.0, 81457152.0, 83808256.0, 91340800.0, 90640384.0, 81281024.0, 83705856.0, 90935296.0, 90906624.0]], [34139, [87896064.0, 88313856.0, 92823552.0, 92884992.0, 81485824.0, 83959808.0, 91181056.0, 90738688.0, 81338368.0, 83820544.0, 90742784.0, 90779648.0]], [34140, [87769088.0, 87715840.0, 92631040.0, 92426240.0, 81203200.0, 83927040.0, 90927104.0, 90984448.0, 80965632.0, 83734528.0, 90427392.0, 90333184.0]], [34141, [88440832.0, 88457216.0, 93794304.0, 93409280.0, 81772544.0, 84475904.0, 91406336.0, 90836992.0, 81530880.0, 84328448.0, 91226112.0, 91230208.0]], [34155, [87990272.0, 88023040.0, 93245440.0, 92942336.0, 81543168.0, 83931136.0, 91095040.0, 90468352.0, 81334272.0, 83795968.0, 90902528.0, 90947584.0]], [34158, [87674880.0, 87814144.0, 92602368.0, 92622848.0, 81190912.0, 83570688.0, 90959872.0, 90263552.0, 80936960.0, 83382272.0, 90443776.0, 90406912.0]], [34160, [88145920.0, 88199168.0, 92991488.0, 93175808.0, 81477632.0, 83685376.0, 91049984.0, 90902528.0, 81285120.0, 83599360.0, 90931200.0, 90951680.0]], [34162, [88031232.0, 88334336.0, 92934144.0, 93036544.0, 81612800.0, 84258816.0, 91168768.0, 90783744.0, 81408000.0, 84103168.0, 90726400.0, 90882048.0]], [34164, [87457792.0, 87666688.0, 92925952.0, 92618752.0, 81260544.0, 83734528.0, 90968064.0, 90947584.0, 81076224.0, 83628032.0, 90529792.0, 90615808.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_fit.json index 17548bd575..825514daa8 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [0.001498903285729674, 0.0011737233499843568, 0.0013813911111558103, 0.0017440364999856683, 0.017214993999004946, 0.017101149499467283, 0.05844060000072204, 0.052067245000216644, 0.008822175499972218, 0.012373359500998049, 0.033484543499980646, 0.03563174450027873]], [34115, [0.001502064416702827, 0.0014785859164779445, 0.0017418442001144285, 0.001699621416567728, 0.013873884000531689, 0.01399644250068377, 0.05909296350000659, 0.059145684499526396, 0.010076795000259153, 0.010096418500324944, 0.038070800000241434, 0.03306273349971889]], [34120, [0.0014222183570901897, 0.0011845105499560305, 0.0013467130625031132, 0.0013611816111733788, 0.013309717000083765, 0.013822529000208306, 0.05924792649966548, 0.0587864509989231, 0.009825608250594087, 0.012117820499952359, 0.03725109550032357, 0.03756127999895398]], [34126, [0.0015012015714351687, 0.0015098520001023037, 0.0015012819167168345, 0.0012261971665389459, 0.01217280299988488, 0.012215865000143822, 0.05197018350008875, 0.05197553699872515, 0.008857035750224895, 0.00889933700000256, 0.03402173500035133, 0.034138146500481525]], [34139, [0.00108602492868418, 0.0010425443500025721, 0.0012211487222278568, 0.0012066918888093722, 0.012041816499731794, 0.01716366900018329, 0.05226113849948888, 0.05158727999969415, 0.01242584400006308, 0.012145908000093186, 0.03867070100022829, 0.03837241749988607]], [34140, [0.0018933864998871286, 0.0014725984284658417, 0.0017468648999056312, 0.0017415825832358678, 0.012335131500549323, 0.012227947000610584, 0.051478109499839775, 0.05177084599927184, 0.012596919500538206, 0.012488700999711, 0.038693658999363834, 0.033885375499266956]], [34141, [0.0015102158333017237, 0.0012268145714447848, 0.0014014343332746648, 0.0017110620714707433, 0.01388327950007806, 0.017249364500457887, 0.05890629599980457, 0.0588503375001892, 0.012469884500205808, 0.012252143501427781, 0.03761011149981641, 0.03714136300004611]], [34155, [0.0015078659284232083, 0.0010583937999399495, 0.0012312470000526649, 0.0012289756112093325, 0.012145177500315185, 0.01213232850022905, 0.059392770501290215, 0.0622183794994271, 0.012541162499474012, 0.009269627499634225, 0.03397333799966873, 0.03395321249990957]], [34158, [0.001471250785730912, 0.0010323202000108722, 0.0011984565555596622, 0.0011942828889206997, 0.011989465499937069, 0.017088515499381174, 0.051294549000886036, 0.05096109550049732, 0.008809278499938955, 0.008726258000478992, 0.03304653849954775, 0.03295676699963224]], [34160, [0.0010724060001458774, 0.0010549167499448232, 0.0012262408888798542, 0.0012185581666320409, 0.01209415999983321, 0.012096038500203576, 0.05148695099978795, 0.05088701749991742, 0.012515771499238326, 0.009086560498872132, 0.033491415499156574, 0.03343777349891752]], [34162, [0.001502399750127855, 0.0013049637857745567, 0.001220400722255969, 0.001219530888900206, 0.01714437049940898, 0.013974741499623633, 0.05938216250069672, 0.05923370399978012, 0.010037124750397197, 0.012451237499590206, 0.03815798249979707, 0.03812760599976173]]] \ No newline at end of file +[[34113, [0.001498903285729674, 0.0011737233499843568, 0.0013813911111558103, 0.0017440364999856683, 0.017214993999004946, 0.017101149499467283, 0.05844060000072204, 0.052067245000216644, 0.008822175499972218, 0.012373359500998049, 0.033484543499980646, 0.03563174450027873]], [34115, [0.001502064416702827, 0.0014785859164779445, 0.0017418442001144285, 0.001699621416567728, 0.013873884000531689, 0.01399644250068377, 0.05909296350000659, 0.059145684499526396, 0.010076795000259153, 0.010096418500324944, 0.038070800000241434, 0.03306273349971889]], [34120, [0.0014222183570901897, 0.0011845105499560305, 0.0013467130625031132, 0.0013611816111733788, 0.013309717000083765, 0.013822529000208306, 0.05924792649966548, 0.0587864509989231, 0.009825608250594087, 0.012117820499952359, 0.03725109550032357, 0.03756127999895398]], [34126, [0.0015012015714351687, 0.0015098520001023037, 0.0015012819167168345, 0.0012261971665389459, 0.01217280299988488, 0.012215865000143822, 0.05197018350008875, 0.05197553699872515, 0.008857035750224895, 0.00889933700000256, 0.03402173500035133, 0.034138146500481525]], [34139, [0.00108602492868418, 0.0010425443500025721, 0.0012211487222278568, 0.0012066918888093722, 0.012041816499731794, 0.01716366900018329, 0.05226113849948888, 0.05158727999969415, 0.01242584400006308, 0.012145908000093186, 0.03867070100022829, 0.03837241749988607]], [34140, [0.0018933864998871286, 0.0014725984284658417, 0.0017468648999056312, 0.0017415825832358678, 0.012335131500549323, 0.012227947000610584, 0.051478109499839775, 0.05177084599927184, 0.012596919500538206, 0.012488700999711, 0.038693658999363834, 0.033885375499266956]], [34141, [0.0015102158333017237, 0.0012268145714447848, 0.0014014343332746648, 0.0017110620714707433, 0.01388327950007806, 0.017249364500457887, 0.05890629599980457, 0.0588503375001892, 0.012469884500205808, 0.012252143501427781, 0.03761011149981641, 0.03714136300004611]], [34155, [0.0015078659284232083, 0.0010583937999399495, 0.0012312470000526649, 0.0012289756112093325, 0.012145177500315185, 0.01213232850022905, 0.059392770501290215, 0.0622183794994271, 0.012541162499474012, 0.009269627499634225, 0.03397333799966873, 0.03395321249990957]], [34158, [0.001471250785730912, 0.0010323202000108722, 0.0011984565555596622, 0.0011942828889206997, 0.011989465499937069, 0.017088515499381174, 0.051294549000886036, 0.05096109550049732, 0.008809278499938955, 0.008726258000478992, 0.03304653849954775, 0.03295676699963224]], [34160, [0.0010724060001458774, 0.0010549167499448232, 0.0012262408888798542, 0.0012185581666320409, 0.01209415999983321, 0.012096038500203576, 0.05148695099978795, 0.05088701749991742, 0.012515771499238326, 0.009086560498872132, 0.033491415499156574, 0.03343777349891752]], [34162, [0.001502399750127855, 0.0013049637857745567, 0.001220400722255969, 0.001219530888900206, 0.01714437049940898, 0.013974741499623633, 0.05938216250069672, 0.05923370399978012, 0.010037124750397197, 0.012451237499590206, 0.03815798249979707, 0.03812760599976173]], [34164, [0.001185342928433134, 0.0010363823999796295, 0.0011994113332952515, 0.001198534166683708, 0.011929710000003979, 0.011925631500162126, 0.050763619499775814, 0.05086634249983035, 0.00858481999966898, 0.008579190749969712, 0.03290056049991108, 0.03282508699976461]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_predict.json index 661a75265e..7ff2ada747 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.09049665000111418, 0.09047138949972577, 0.12946567999915715, 0.1302455140003076, 1.3245484435001345, 2.667828218998693, 8.30450277500131, 8.113323002999095, 2.2061231580009917, 5.752544733000832, 7.526197360000879, 10.755202964001]], [34115, [0.09022266199917794, 0.09058564950100845, 0.1250513195000167, 0.12436711349982943, 1.2470771610005613, 2.868727838000268, 9.289307909000854, 8.550280974999623, 2.352441653000824, 5.598212670000066, 8.256390124999598, 10.7691750160011]], [34120, [0.08882128599998396, 0.0902263590005532, 0.1248192855000525, 0.12948624799992103, 1.3250302714986901, 2.8264432360010687, 8.739353008000762, 7.788882566001121, 2.311815346500225, 5.606413034998695, 7.151612710998961, 11.064935436999804]], [34126, [0.09129178300008789, 0.09080898699903628, 0.12467084350009827, 0.13085541750024277, 1.2949519209996652, 2.9690581754994128, 8.261331526000504, 8.607819728000322, 2.3852714090007794, 5.6948488039997756, 7.358123495499967, 10.543665378001606]], [34139, [0.08892489149911853, 0.08850820350016875, 0.12627390399848082, 0.12825392749982711, 1.2215345079994222, 2.8610398105001877, 9.433181464999507, 7.944575391000399, 2.166272898999523, 5.451130918000672, 7.667074585999217, 11.148139920000176]], [34140, [0.08682420299919613, 0.08870430150091124, 0.12396756350062788, 0.1243411979994562, 1.286694823000289, 2.9006115784995927, 8.376747158001308, 8.0518865490003, 2.430342091500279, 5.639076026998737, 8.117663308999909, 9.043899398000576]], [34141, [0.09055840200016974, 0.09056584350037156, 0.12973354950099747, 0.1298132350002561, 1.4918125439990035, 3.003603833500165, 9.48638327899971, 7.9443858610011375, 2.390298430000257, 4.2997974194986455, 7.131626152500758, 10.009485701999438]], [34155, [0.09076159950018337, 0.08803395599989017, 0.13045257499925356, 0.1264608480005336, 1.434193196000706, 2.8138044780007476, 9.610358738998912, 8.441220032000274, 2.144222336999519, 5.166311054000289, 7.4713600490003955, 10.870978098000705]], [34158, [0.091351392499746, 0.09145007450024423, 0.1294272525010456, 0.12960747350007296, 1.3981477490015095, 2.8313588300006813, 9.344857955999032, 8.10535457700098, 2.407856812499631, 5.6674960929994995, 8.201274101000308, 10.683626691999962]], [34160, [0.0910110340000756, 0.08860701750018052, 0.12589525649946154, 0.12964923449999333, 1.2219807540004695, 2.780512962001012, 8.485664365000048, 8.12215476899837, 2.2924152790001244, 5.516304728998875, 7.909542114999567, 10.835874012000204]], [34162, [0.0909184069996627, 0.08892916049990163, 0.13059214150052867, 0.1297198809998008, 1.2530761879997954, 2.921873371999027, 8.774020103001021, 8.504951791999702, 2.162120655000763, 5.524396067999987, 8.175798162999854, 10.565359949001504]]] \ No newline at end of file +[[34113, [0.09049665000111418, 0.09047138949972577, 0.12946567999915715, 0.1302455140003076, 1.3245484435001345, 2.667828218998693, 8.30450277500131, 8.113323002999095, 2.2061231580009917, 5.752544733000832, 7.526197360000879, 10.755202964001]], [34115, [0.09022266199917794, 0.09058564950100845, 0.1250513195000167, 0.12436711349982943, 1.2470771610005613, 2.868727838000268, 9.289307909000854, 8.550280974999623, 2.352441653000824, 5.598212670000066, 8.256390124999598, 10.7691750160011]], [34120, [0.08882128599998396, 0.0902263590005532, 0.1248192855000525, 0.12948624799992103, 1.3250302714986901, 2.8264432360010687, 8.739353008000762, 7.788882566001121, 2.311815346500225, 5.606413034998695, 7.151612710998961, 11.064935436999804]], [34126, [0.09129178300008789, 0.09080898699903628, 0.12467084350009827, 0.13085541750024277, 1.2949519209996652, 2.9690581754994128, 8.261331526000504, 8.607819728000322, 2.3852714090007794, 5.6948488039997756, 7.358123495499967, 10.543665378001606]], [34139, [0.08892489149911853, 0.08850820350016875, 0.12627390399848082, 0.12825392749982711, 1.2215345079994222, 2.8610398105001877, 9.433181464999507, 7.944575391000399, 2.166272898999523, 5.451130918000672, 7.667074585999217, 11.148139920000176]], [34140, [0.08682420299919613, 0.08870430150091124, 0.12396756350062788, 0.1243411979994562, 1.286694823000289, 2.9006115784995927, 8.376747158001308, 8.0518865490003, 2.430342091500279, 5.639076026998737, 8.117663308999909, 9.043899398000576]], [34141, [0.09055840200016974, 0.09056584350037156, 0.12973354950099747, 0.1298132350002561, 1.4918125439990035, 3.003603833500165, 9.48638327899971, 7.9443858610011375, 2.390298430000257, 4.2997974194986455, 7.131626152500758, 10.009485701999438]], [34155, [0.09076159950018337, 0.08803395599989017, 0.13045257499925356, 0.1264608480005336, 1.434193196000706, 2.8138044780007476, 9.610358738998912, 8.441220032000274, 2.144222336999519, 5.166311054000289, 7.4713600490003955, 10.870978098000705]], [34158, [0.091351392499746, 0.09145007450024423, 0.1294272525010456, 0.12960747350007296, 1.3981477490015095, 2.8313588300006813, 9.344857955999032, 8.10535457700098, 2.407856812499631, 5.6674960929994995, 8.201274101000308, 10.683626691999962]], [34160, [0.0910110340000756, 0.08860701750018052, 0.12589525649946154, 0.12964923449999333, 1.2219807540004695, 2.780512962001012, 8.485664365000048, 8.12215476899837, 2.2924152790001244, 5.516304728998875, 7.909542114999567, 10.835874012000204]], [34162, [0.0909184069996627, 0.08892916049990163, 0.13059214150052867, 0.1297198809998008, 1.2530761879997954, 2.921873371999027, 8.774020103001021, 8.504951791999702, 2.162120655000763, 5.524396067999987, 8.175798162999854, 10.565359949001504]], [34164, [0.09026961200015649, 0.08853839700077515, 0.12965472050018434, 0.13066791250003007, 1.3762200390010548, 2.817162584000471, 9.001036760000716, 8.111659842001245, 2.4066625955001655, 6.049014292999345, 7.308373114999995, 11.336473118999493]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.track_test_score.json index a33ad6c7e2..b72ee6194f 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.44374198908197104, 0.44374198908197104, 0.6616805840891441, 0.6616805840891441, 0.44374198908197104, 0.44374198908197104, 0.6616805840891441, 0.6616805840891441, 0.44374198908197104, 0.44374198908197104, 0.6616805840891441, 0.6616805840891441]], [34115, [0.4430257891411856, 0.4430257891411856, 0.6534847923516497, 0.6534847923516497, 0.4430257891411856, 0.4430257891411856, 0.6534847923516497, 0.6534847923516497, 0.4430257891411856, 0.4430257891411856, 0.6534847923516497, 0.6534847923516497]], [34120, [0.4359730524061554, 0.4359730524061554, 0.6765139480428333, 0.6765139480428333, 0.4359730524061554, 0.4359730524061554, 0.6765139480428333, 0.6765139480428333, 0.4359730524061554, 0.4359730524061554, 0.6765139480428333, 0.6765139480428333]], [34126, [0.44725035467974805, 0.44725035467974805, 0.6704371896867277, 0.6704371896867277, 0.44725035467974805, 0.44725035467974805, 0.6704371896867277, 0.6704371896867277, 0.44725035467974805, 0.44725035467974805, 0.6704371896867277, 0.6704371896867277]], [34139, [0.42930131038613395, 0.42930131038613395, 0.6604858763543322, 0.6604858763543322, 0.42930131038613395, 0.42930131038613395, 0.6604858763543322, 0.6604858763543322, 0.42930131038613395, 0.42930131038613395, 0.6604858763543322, 0.6604858763543322]], [34140, [0.43667668230599316, 0.43667668230599316, 0.6482430798278419, 0.6482430798278419, 0.43667668230599316, 0.43667668230599316, 0.6482430798278419, 0.6482430798278419, 0.43667668230599316, 0.43667668230599316, 0.6482430798278419, 0.6482430798278419]], [34141, [0.4348374231619834, 0.4348374231619834, 0.6621362400001549, 0.6621362400001549, 0.4348374231619834, 0.4348374231619834, 0.6621362400001549, 0.6621362400001549, 0.4348374231619834, 0.4348374231619834, 0.6621362400001549, 0.6621362400001549]], [34155, [0.4471440281900291, 0.4471440281900291, 0.6593866736049172, 0.6593866736049172, 0.4471440281900291, 0.4471440281900291, 0.6593866736049172, 0.6593866736049172, 0.4471440281900291, 0.4471440281900291, 0.6593866736049172, 0.6593866736049172]], [34158, [0.424577117523659, 0.424577117523659, 0.6635121068818588, 0.6635121068818588, 0.424577117523659, 0.424577117523659, 0.6635121068818588, 0.6635121068818588, 0.424577117523659, 0.424577117523659, 0.6635121068818588, 0.6635121068818588]], [34160, [0.4167145121509801, 0.4167145121509801, 0.6507839792369807, 0.6507839792369807, 0.4167145121509801, 0.4167145121509801, 0.6507839792369807, 0.6507839792369807, 0.4167145121509801, 0.4167145121509801, 0.6507839792369807, 0.6507839792369807]], [34162, [0.43658423817067005, 0.43658423817067005, 0.6635318213909278, 0.6635318213909278, 0.43658423817067005, 0.43658423817067005, 0.6635318213909278, 0.6635318213909278, 0.43658423817067005, 0.43658423817067005, 0.6635318213909278, 0.6635318213909278]]] \ No newline at end of file +[[34113, [0.44374198908197104, 0.44374198908197104, 0.6616805840891441, 0.6616805840891441, 0.44374198908197104, 0.44374198908197104, 0.6616805840891441, 0.6616805840891441, 0.44374198908197104, 0.44374198908197104, 0.6616805840891441, 0.6616805840891441]], [34115, [0.4430257891411856, 0.4430257891411856, 0.6534847923516497, 0.6534847923516497, 0.4430257891411856, 0.4430257891411856, 0.6534847923516497, 0.6534847923516497, 0.4430257891411856, 0.4430257891411856, 0.6534847923516497, 0.6534847923516497]], [34120, [0.4359730524061554, 0.4359730524061554, 0.6765139480428333, 0.6765139480428333, 0.4359730524061554, 0.4359730524061554, 0.6765139480428333, 0.6765139480428333, 0.4359730524061554, 0.4359730524061554, 0.6765139480428333, 0.6765139480428333]], [34126, [0.44725035467974805, 0.44725035467974805, 0.6704371896867277, 0.6704371896867277, 0.44725035467974805, 0.44725035467974805, 0.6704371896867277, 0.6704371896867277, 0.44725035467974805, 0.44725035467974805, 0.6704371896867277, 0.6704371896867277]], [34139, [0.42930131038613395, 0.42930131038613395, 0.6604858763543322, 0.6604858763543322, 0.42930131038613395, 0.42930131038613395, 0.6604858763543322, 0.6604858763543322, 0.42930131038613395, 0.42930131038613395, 0.6604858763543322, 0.6604858763543322]], [34140, [0.43667668230599316, 0.43667668230599316, 0.6482430798278419, 0.6482430798278419, 0.43667668230599316, 0.43667668230599316, 0.6482430798278419, 0.6482430798278419, 0.43667668230599316, 0.43667668230599316, 0.6482430798278419, 0.6482430798278419]], [34141, [0.4348374231619834, 0.4348374231619834, 0.6621362400001549, 0.6621362400001549, 0.4348374231619834, 0.4348374231619834, 0.6621362400001549, 0.6621362400001549, 0.4348374231619834, 0.4348374231619834, 0.6621362400001549, 0.6621362400001549]], [34155, [0.4471440281900291, 0.4471440281900291, 0.6593866736049172, 0.6593866736049172, 0.4471440281900291, 0.4471440281900291, 0.6593866736049172, 0.6593866736049172, 0.4471440281900291, 0.4471440281900291, 0.6593866736049172, 0.6593866736049172]], [34158, [0.424577117523659, 0.424577117523659, 0.6635121068818588, 0.6635121068818588, 0.424577117523659, 0.424577117523659, 0.6635121068818588, 0.6635121068818588, 0.424577117523659, 0.424577117523659, 0.6635121068818588, 0.6635121068818588]], [34160, [0.4167145121509801, 0.4167145121509801, 0.6507839792369807, 0.6507839792369807, 0.4167145121509801, 0.4167145121509801, 0.6507839792369807, 0.6507839792369807, 0.4167145121509801, 0.4167145121509801, 0.6507839792369807, 0.6507839792369807]], [34162, [0.43658423817067005, 0.43658423817067005, 0.6635318213909278, 0.6635318213909278, 0.43658423817067005, 0.43658423817067005, 0.6635318213909278, 0.6635318213909278, 0.43658423817067005, 0.43658423817067005, 0.6635318213909278, 0.6635318213909278]], [34164, [0.43764350424799614, 0.43764350424799614, 0.6681073740828299, 0.6681073740828299, 0.43764350424799614, 0.43764350424799614, 0.6681073740828299, 0.6681073740828299, 0.43764350424799614, 0.43764350424799614, 0.6681073740828299, 0.6681073740828299]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.track_train_score.json index d4d39b753e..8ac927bffe 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.635997909198698, 0.635997909198698, 0.7950178376208666, 0.7950178376208666, 0.635997909198698, 0.635997909198698, 0.7950178376208666, 0.7950178376208666, 0.635997909198698, 0.635997909198698, 0.7950178376208666, 0.7950178376208666]], [34115, [0.6408049227811612, 0.6408049227811612, 0.7932300880662926, 0.7932300880662926, 0.6408049227811612, 0.6408049227811612, 0.7932300880662926, 0.7932300880662926, 0.6408049227811612, 0.6408049227811612, 0.7932300880662926, 0.7932300880662926]], [34120, [0.6382177039003454, 0.6382177039003454, 0.7963256832121891, 0.7963256832121891, 0.6382177039003454, 0.6382177039003454, 0.7963256832121891, 0.7963256832121891, 0.6382177039003454, 0.6382177039003454, 0.7963256832121891, 0.7963256832121891]], [34126, [0.6415319303258984, 0.6415319303258984, 0.7910612617361351, 0.7910612617361351, 0.6415319303258984, 0.6415319303258984, 0.7910612617361351, 0.7910612617361351, 0.6415319303258984, 0.6415319303258984, 0.7910612617361351, 0.7910612617361351]], [34139, [0.6289544676693555, 0.6289544676693555, 0.7932022287872915, 0.7932022287872915, 0.6289544676693555, 0.6289544676693555, 0.7932022287872915, 0.7932022287872915, 0.6289544676693555, 0.6289544676693555, 0.7932022287872915, 0.7932022287872915]], [34140, [0.6386652428987774, 0.6386652428987774, 0.7890448140963007, 0.7890448140963007, 0.6386652428987774, 0.6386652428987774, 0.7890448140963007, 0.7890448140963007, 0.6386652428987774, 0.6386652428987774, 0.7890448140963007, 0.7890448140963007]], [34141, [0.6364138258769027, 0.6364138258769027, 0.7920831060837519, 0.7920831060837519, 0.6364138258769027, 0.6364138258769027, 0.7920831060837519, 0.7920831060837519, 0.6364138258769027, 0.6364138258769027, 0.7920831060837519, 0.7920831060837519]], [34155, [0.6378277604534549, 0.6378277604534549, 0.7923535027258366, 0.7923535027258366, 0.6378277604534549, 0.6378277604534549, 0.7923535027258366, 0.7923535027258366, 0.6378277604534549, 0.6378277604534549, 0.7923535027258366, 0.7923535027258366]], [34158, [0.6330472706534775, 0.6330472706534775, 0.7955876073104108, 0.7955876073104108, 0.6330472706534775, 0.6330472706534775, 0.7955876073104108, 0.7955876073104108, 0.6330472706534775, 0.6330472706534775, 0.7955876073104108, 0.7955876073104108]], [34160, [0.6321523080976755, 0.6321523080976755, 0.79093655131027, 0.79093655131027, 0.6321523080976755, 0.6321523080976755, 0.79093655131027, 0.79093655131027, 0.6321523080976755, 0.6321523080976755, 0.79093655131027, 0.79093655131027]], [34162, [0.6375753718595948, 0.6375753718595948, 0.7903530286486687, 0.7903530286486687, 0.6375753718595948, 0.6375753718595948, 0.7903530286486687, 0.7903530286486687, 0.6375753718595948, 0.6375753718595948, 0.7903530286486687, 0.7903530286486687]]] \ No newline at end of file +[[34113, [0.635997909198698, 0.635997909198698, 0.7950178376208666, 0.7950178376208666, 0.635997909198698, 0.635997909198698, 0.7950178376208666, 0.7950178376208666, 0.635997909198698, 0.635997909198698, 0.7950178376208666, 0.7950178376208666]], [34115, [0.6408049227811612, 0.6408049227811612, 0.7932300880662926, 0.7932300880662926, 0.6408049227811612, 0.6408049227811612, 0.7932300880662926, 0.7932300880662926, 0.6408049227811612, 0.6408049227811612, 0.7932300880662926, 0.7932300880662926]], [34120, [0.6382177039003454, 0.6382177039003454, 0.7963256832121891, 0.7963256832121891, 0.6382177039003454, 0.6382177039003454, 0.7963256832121891, 0.7963256832121891, 0.6382177039003454, 0.6382177039003454, 0.7963256832121891, 0.7963256832121891]], [34126, [0.6415319303258984, 0.6415319303258984, 0.7910612617361351, 0.7910612617361351, 0.6415319303258984, 0.6415319303258984, 0.7910612617361351, 0.7910612617361351, 0.6415319303258984, 0.6415319303258984, 0.7910612617361351, 0.7910612617361351]], [34139, [0.6289544676693555, 0.6289544676693555, 0.7932022287872915, 0.7932022287872915, 0.6289544676693555, 0.6289544676693555, 0.7932022287872915, 0.7932022287872915, 0.6289544676693555, 0.6289544676693555, 0.7932022287872915, 0.7932022287872915]], [34140, [0.6386652428987774, 0.6386652428987774, 0.7890448140963007, 0.7890448140963007, 0.6386652428987774, 0.6386652428987774, 0.7890448140963007, 0.7890448140963007, 0.6386652428987774, 0.6386652428987774, 0.7890448140963007, 0.7890448140963007]], [34141, [0.6364138258769027, 0.6364138258769027, 0.7920831060837519, 0.7920831060837519, 0.6364138258769027, 0.6364138258769027, 0.7920831060837519, 0.7920831060837519, 0.6364138258769027, 0.6364138258769027, 0.7920831060837519, 0.7920831060837519]], [34155, [0.6378277604534549, 0.6378277604534549, 0.7923535027258366, 0.7923535027258366, 0.6378277604534549, 0.6378277604534549, 0.7923535027258366, 0.7923535027258366, 0.6378277604534549, 0.6378277604534549, 0.7923535027258366, 0.7923535027258366]], [34158, [0.6330472706534775, 0.6330472706534775, 0.7955876073104108, 0.7955876073104108, 0.6330472706534775, 0.6330472706534775, 0.7955876073104108, 0.7955876073104108, 0.6330472706534775, 0.6330472706534775, 0.7955876073104108, 0.7955876073104108]], [34160, [0.6321523080976755, 0.6321523080976755, 0.79093655131027, 0.79093655131027, 0.6321523080976755, 0.6321523080976755, 0.79093655131027, 0.79093655131027, 0.6321523080976755, 0.6321523080976755, 0.79093655131027, 0.79093655131027]], [34162, [0.6375753718595948, 0.6375753718595948, 0.7903530286486687, 0.7903530286486687, 0.6375753718595948, 0.6375753718595948, 0.7903530286486687, 0.7903530286486687, 0.6375753718595948, 0.6375753718595948, 0.7903530286486687, 0.7903530286486687]], [34164, [0.6417771228408591, 0.6417771228408591, 0.7930458884952338, 0.7930458884952338, 0.6417771228408591, 0.6417771228408591, 0.7930458884952338, 0.7930458884952338, 0.6417771228408591, 0.6417771228408591, 0.7930458884952338, 0.7930458884952338]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/summary.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/summary.json index 960a8cbe84..f9b4074f2e 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/summary.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/summary.json @@ -1 +1 @@ -[{"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('dense', 'lloyd', 'random')", "last_rev": 34162, "last_value": 103350272.0, "last_err": 197725.0909090909, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('dense', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 113692672.0, "last_err": 173893.81818181818, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('dense', 'elkan', 'random')", "last_rev": 34162, "last_value": 137211904.0, "last_err": 112453.81818181818, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('dense', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 137601024.0, "last_err": 154530.9090909091, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('sparse', 'lloyd', 'random')", "last_rev": 34162, "last_value": 254574592.0, "last_err": 160116.36363636365, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('sparse', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 254570496.0, "last_err": 187298.9090909091, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('sparse', 'elkan', 'random')", "last_rev": 34162, "last_value": 261480448.0, "last_err": 86016.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('sparse', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 260530176.0, "last_err": 234589.0909090909, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('dense', 'lloyd', 'random')", "last_rev": 34162, "last_value": 89739264.0, "last_err": 269591.2727272727, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('dense', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 89812992.0, "last_err": 268101.8181818182, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('dense', 'elkan', 'random')", "last_rev": 34162, "last_value": 89739264.0, "last_err": 255069.0909090909, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('dense', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 89743360.0, "last_err": 256186.18181818182, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('sparse', 'lloyd', 'random')", "last_rev": 34162, "last_value": 97505280.0, "last_err": 198097.45454545456, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('sparse', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 97505280.0, "last_err": 198469.81818181818, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('sparse', 'elkan', 'random')", "last_rev": 34162, "last_value": 97505280.0, "last_err": 198097.45454545456, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('sparse', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 97505280.0, "last_err": 198097.45454545456, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('dense', 'lloyd', 'random')", "last_rev": 34162, "last_value": 120754176.0, "last_err": 151552.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('dense', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 120745984.0, "last_err": 155648.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('dense', 'elkan', 'random')", "last_rev": 34162, "last_value": 120741888.0, "last_err": 150807.27272727274, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('dense', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 120750080.0, "last_err": 152669.0909090909, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('sparse', 'lloyd', 'random')", "last_rev": 34162, "last_value": 124948480.0, "last_err": 145221.81818181818, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('sparse', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 124948480.0, "last_err": 145594.18181818182, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('sparse', 'elkan', 'random')", "last_rev": 34162, "last_value": 124948480.0, "last_err": 145594.18181818182, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('sparse', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 124948480.0, "last_err": 145966.54545454544, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.time_fit('dense', 'lloyd', 'random')", "last_rev": 34162, "last_value": 0.40211216299996977, "last_err": 0.002036837145222635, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.time_fit('dense', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 1.1734618240000145, "last_err": 0.023542757428865215, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.time_fit('dense', 'elkan', 'random')", "last_rev": 34162, "last_value": 2.1956100815000354, "last_err": 0.008606639667824203, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.time_fit('dense', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 2.0139847700002065, "last_err": 0.07621451608629351, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.time_fit('sparse', 'lloyd', 'random')", "last_rev": 34162, "last_value": 1.7108321509999769, "last_err": 0.03160380375513374, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.time_fit('sparse', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 4.488032942000018, "last_err": 0.032486801471667555, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.time_fit('sparse', 'elkan', 'random')", "last_rev": 34162, "last_value": 3.469436167500021, "last_err": 0.036436845644435084, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.time_fit('sparse', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 5.139550787999951, "last_err": 0.12438904267917351, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.time_predict('dense', 'lloyd', 'random')", "last_rev": 34162, "last_value": 0.005369411749995834, "last_err": 5.379217660753438e-05, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.time_predict('dense', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 0.005277451000040401, "last_err": 0.00016960525094768055, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.time_predict('dense', 'elkan', 'random')", "last_rev": 34162, "last_value": 0.0050876790000415895, "last_err": 0.00022501855942005128, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.time_predict('dense', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 0.005351551999979165, "last_err": 0.0002130268828251738, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.time_predict('sparse', 'lloyd', 'random')", "last_rev": 34162, "last_value": 0.027433640500021284, "last_err": 0.0, "prev_value": 0.02009956599999896, "change_rev": [34160, 34162]}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.time_predict('sparse', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 0.015813256000001275, "last_err": 0.005039345556521558, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.time_predict('sparse', 'elkan', 'random')", "last_rev": 34162, "last_value": 0.027959162500110324, "last_err": 0.0020535141830844636, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.time_predict('sparse', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 0.016581200000132412, "last_err": 0.007158086993207183, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.time_transform('dense', 'lloyd', 'random')", "last_rev": 34162, "last_value": 0.08655621550008163, "last_err": 0.0039202052234796675, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.time_transform('dense', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 0.0856344444999877, "last_err": 0.004149146001935665, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'random')", "last_rev": 34162, "last_value": 0.08531690399991021, "last_err": 0.002657606897257052, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 0.0849672819999796, "last_err": 0.004469155582998088, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'random')", "last_rev": 34162, "last_value": 3.8029851090000193, "last_err": 0.19031416041238924, "prev_value": 3.570233304000112, "change_rev": [34120, 34126]}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": 3.8003822919999948, "last_err": 0.22050029952998554, "prev_value": 3.5546480730001804, "change_rev": [null, 34141]}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'random')", "last_rev": 34162, "last_value": 3.781139291000045, "last_err": 0.11355892622262496, "prev_value": 3.521388963999925, "change_rev": [null, 34140]}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": 3.8138180620001094, "last_err": 0.11127036779331395, "prev_value": 3.5410637559998577, "change_rev": [null, 34140]}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'random')", "last_rev": 34162, "last_value": -4.109885215759277, "last_err": 0.0, "prev_value": -4.109886169433594, "change_rev": [34160, 34162]}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": -3.0753684043884277, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'random')", "last_rev": 34162, "last_value": -4.109886169433594, "last_err": 0.0, "prev_value": -4.109885215759277, "change_rev": [34158, 34160]}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": -3.0753684043884277, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.track_test_score('sparse', 'lloyd', 'random')", "last_rev": 34162, "last_value": -0.9266619682312012, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.track_test_score('sparse', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": -0.9249227643013, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.track_test_score('sparse', 'elkan', 'random')", "last_rev": 34162, "last_value": -0.9266619682312012, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.track_test_score('sparse', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": -0.9249262809753418, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'random')", "last_rev": 34162, "last_value": -4.1075520515441895, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": -3.0780563354492188, "last_err": 0.0, "prev_value": -3.0780560970306396, "change_rev": [34160, 34162]}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'random')", "last_rev": 34162, "last_value": -4.1075520515441895, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": -3.0780563354492188, "last_err": 0.0, "prev_value": -3.0780560970306396, "change_rev": [null, 34141]}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.track_train_score('sparse', 'lloyd', 'random')", "last_rev": 34162, "last_value": -0.9227071404457092, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.track_train_score('sparse', 'lloyd', 'k-means++')", "last_rev": 34162, "last_value": -0.922096312046051, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.track_train_score('sparse', 'elkan', 'random')", "last_rev": 34162, "last_value": -0.9227071404457092, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.track_train_score('sparse', 'elkan', 'k-means++')", "last_rev": 34162, "last_value": -0.9221000075340271, "last_err": 5.418604070490057e-09, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'random')", "last_rev": 34162, "last_value": 90939392.0, "last_err": 210757.81818181818, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'k-means++')", "last_rev": 34162, "last_value": 91521024.0, "last_err": 270708.36363636365, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit('sparse', 'random')", "last_rev": 34162, "last_value": 174022656.0, "last_err": 240546.9090909091, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit('sparse', 'k-means++')", "last_rev": 34162, "last_value": 175554560.0, "last_err": 225280.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'random')", "last_rev": 34162, "last_value": 88145920.0, "last_err": 174638.54545454544, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'k-means++')", "last_rev": 34162, "last_value": 88100864.0, "last_err": 226769.45454545456, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'random')", "last_rev": 34162, "last_value": 103399424.0, "last_err": 197352.72727272726, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'k-means++')", "last_rev": 34162, "last_value": 103399424.0, "last_err": 196980.36363636365, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'random')", "last_rev": 34162, "last_value": 119070720.0, "last_err": 164957.0909090909, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'k-means++')", "last_rev": 34162, "last_value": 119058432.0, "last_err": 159744.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'random')", "last_rev": 34162, "last_value": 124137472.0, "last_err": 155275.63636363635, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'k-means++')", "last_rev": 34162, "last_value": 124133376.0, "last_err": 147828.36363636365, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_fit", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_fit('dense', 'random')", "last_rev": 34162, "last_value": 0.47880918050009313, "last_err": 0.006493088910636346, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_fit", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_fit('dense', 'k-means++')", "last_rev": 34162, "last_value": 0.4876799360001769, "last_err": 0.008525889383844925, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_fit", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_fit('sparse', 'random')", "last_rev": 34162, "last_value": 0.6201266324999324, "last_err": 0.03879961413134524, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_fit", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_fit('sparse', 'k-means++')", "last_rev": 34162, "last_value": 1.6373085924999486, "last_err": 0.034317397030799626, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_predict", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_predict('dense', 'random')", "last_rev": 34162, "last_value": 0.0053397412500544306, "last_err": 0.00021273637703344528, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_predict", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_predict('dense', 'k-means++')", "last_rev": 34162, "last_value": 0.005341644000054657, "last_err": 0.0005903898951265736, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_predict", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_predict('sparse', 'random')", "last_rev": 34162, "last_value": 0.03675511300002654, "last_err": 0.0032052103287942557, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_predict", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_predict('sparse', 'k-means++')", "last_rev": 34162, "last_value": 0.036925888000041596, "last_err": 0.002133930204325451, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_transform", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'random')", "last_rev": 34162, "last_value": 0.09212016650008081, "last_err": 0.005638882663888915, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_transform", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'k-means++')", "last_rev": 34162, "last_value": 0.09256515350011796, "last_err": 0.006519137047484838, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_transform", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_transform('sparse', 'random')", "last_rev": 34162, "last_value": 7.182846978000043, "last_err": 0.25985262259848435, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_transform", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_transform('sparse', 'k-means++')", "last_rev": 34162, "last_value": 7.153372103500033, "last_err": 0.17515430532300724, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_test_score", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_test_score('dense', 'random')", "last_rev": 34162, "last_value": -4.596621036529541, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_test_score", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_test_score('dense', 'k-means++')", "last_rev": 34162, "last_value": -3.1085314750671387, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_test_score", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_test_score('sparse', 'random')", "last_rev": 34162, "last_value": -0.9366871118545532, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_test_score", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_test_score('sparse', 'k-means++')", "last_rev": 34162, "last_value": -0.9386959075927734, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_train_score", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_train_score('dense', 'random')", "last_rev": 34162, "last_value": -4.584851264953613, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_train_score", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_train_score('dense', 'k-means++')", "last_rev": 34162, "last_value": -3.115997314453125, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_train_score", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_train_score('sparse', 'random')", "last_rev": 34162, "last_value": -0.9323447346687317, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_train_score", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_train_score('sparse', 'k-means++')", "last_rev": 34162, "last_value": -0.934399425983429, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_fit", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_fit('lars', 1)", "last_rev": 34162, "last_value": 109260800.0, "last_err": 177989.81818181818, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_fit", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_fit('lars', 4)", "last_rev": 34162, "last_value": 130101248.0, "last_err": 269963.63636363635, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_fit", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_fit('cd', 1)", "last_rev": 34162, "last_value": 103333888.0, "last_err": 322094.54545454547, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_fit", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_fit('cd', 4)", "last_rev": 34162, "last_value": 130240512.0, "last_err": 280762.1818181818, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_transform", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 1)", "last_rev": 34162, "last_value": 85090304.0, "last_err": 88994.90909090909, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_transform", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 4)", "last_rev": 34162, "last_value": 87187456.0, "last_err": 178362.18181818182, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_transform", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_transform('cd', 1)", "last_rev": 34162, "last_value": 85078016.0, "last_err": 93835.63636363637, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_transform", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_transform('cd', 4)", "last_rev": 34162, "last_value": 87187456.0, "last_err": 176500.36363636365, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_fit", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_fit('lars', 1)", "last_rev": 34162, "last_value": 17.26241022999966, "last_err": 0.9819761853587071, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_fit", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_fit('lars', 4)", "last_rev": 34162, "last_value": 10.113518836999901, "last_err": 0.27016329574816794, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_fit", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_fit('cd', 1)", "last_rev": 34162, "last_value": 0.7538921509999454, "last_err": 0.021972986171771205, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_fit", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_fit('cd', 4)", "last_rev": 34162, "last_value": 3.321303674000319, "last_err": 0.1730312996604398, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_transform", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_transform('lars', 1)", "last_rev": 34162, "last_value": 0.23449252249997699, "last_err": 0.023455261648830786, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_transform", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_transform('lars', 4)", "last_rev": 34162, "last_value": 0.29691259550031646, "last_err": 0.012144806874981512, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_transform", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_transform('cd', 1)", "last_rev": 34162, "last_value": 0.24220178549990123, "last_err": 0.009789168246512252, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_transform", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_transform('cd', 4)", "last_rev": 34162, "last_value": 0.29159356600007413, "last_err": 0.003865353054886636, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_test_score", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_test_score('lars', 1)", "last_rev": 34162, "last_value": -0.07475553452968597, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_test_score", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_test_score('lars', 4)", "last_rev": 34162, "last_value": -0.07475553452713135, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_test_score", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_test_score('cd', 1)", "last_rev": 34162, "last_value": -0.07475554198026657, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_test_score", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_test_score('cd', 4)", "last_rev": 34162, "last_value": -0.07475553814463735, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_train_score", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_train_score('lars', 1)", "last_rev": 34162, "last_value": -0.07231885939836502, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_train_score", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_train_score('lars', 4)", "last_rev": 34162, "last_value": -0.07231886142463793, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_train_score", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_train_score('cd', 1)", "last_rev": 34162, "last_value": -0.07231885939836502, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_train_score", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_train_score('cd', 4)", "last_rev": 34162, "last_value": -0.07231886151447059, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('lars', 1)", "last_rev": 34162, "last_value": 97640448.0, "last_err": 197725.0909090909, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('lars', 4)", "last_rev": 34162, "last_value": 107974656.0, "last_err": 470295.2727272727, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('cd', 1)", "last_rev": 34162, "last_value": 97509376.0, "last_err": 196235.63636363635, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('cd', 4)", "last_rev": 34162, "last_value": 107732992.0, "last_err": 360448.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 1)", "last_rev": 34162, "last_value": 86306816.0, "last_err": 122507.63636363637, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 4)", "last_rev": 34162, "last_value": 88018944.0, "last_err": 200704.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 1)", "last_rev": 34162, "last_value": 86126592.0, "last_err": 110964.36363636363, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 4)", "last_rev": 34162, "last_value": 88018944.0, "last_err": 199586.9090909091, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('lars', 1)", "last_rev": 34162, "last_value": 10.678223337999952, "last_err": 0.318016710556852, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('lars', 4)", "last_rev": 34162, "last_value": 20.457598145000247, "last_err": 1.7592993599760574, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 1)", "last_rev": 34162, "last_value": 3.1037892630001807, "last_err": 0.08656552671036474, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 4)", "last_rev": 34162, "last_value": 18.712739478999993, "last_err": 1.2338808998630622, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('lars', 1)", "last_rev": 34162, "last_value": 0.2381800010000461, "last_err": 0.009720558207944312, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('lars', 4)", "last_rev": 34162, "last_value": 0.3009983940000893, "last_err": 0.00663241289339556, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('cd', 1)", "last_rev": 34162, "last_value": 0.22955045300000165, "last_err": 0.010757435208278762, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('cd', 4)", "last_rev": 34162, "last_value": 0.300423385999693, "last_err": 0.004158422751268644, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('lars', 1)", "last_rev": 34162, "last_value": -0.07506909221410751, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('lars', 4)", "last_rev": 34162, "last_value": -0.0750688759007175, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('cd', 1)", "last_rev": 34162, "last_value": -0.0750984251499176, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('cd', 4)", "last_rev": 34162, "last_value": -0.07509369093642158, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 1)", "last_rev": 34162, "last_value": -0.07244396954774857, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 4)", "last_rev": 34162, "last_value": -0.072444055250929, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('cd', 1)", "last_rev": 34162, "last_value": -0.07244586199522018, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('cd', 4)", "last_rev": 34162, "last_value": -0.07244519704497496, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.peakmem_fit", "idx": 0, "pretty_name": "decomposition.PCABenchmark.peakmem_fit('full')", "last_rev": 34162, "last_value": 907452416.0, "last_err": 540299.6363636364, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.peakmem_fit", "idx": 1, "pretty_name": "decomposition.PCABenchmark.peakmem_fit('arpack')", "last_rev": 34162, "last_value": 605138944.0, "last_err": 172776.72727272726, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.peakmem_fit", "idx": 2, "pretty_name": "decomposition.PCABenchmark.peakmem_fit('randomized')", "last_rev": 34162, "last_value": 632092672.0, "last_err": 238387.2, "prev_value": 622297088.0, "change_rev": [34113, 34115]}, {"name": "decomposition.PCABenchmark.peakmem_transform", "idx": 0, "pretty_name": "decomposition.PCABenchmark.peakmem_transform('full')", "last_rev": 34162, "last_value": 582782976.0, "last_err": 231982.54545454544, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.peakmem_transform", "idx": 1, "pretty_name": "decomposition.PCABenchmark.peakmem_transform('arpack')", "last_rev": 34162, "last_value": 582778880.0, "last_err": 104261.81818181818, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.peakmem_transform", "idx": 2, "pretty_name": "decomposition.PCABenchmark.peakmem_transform('randomized')", "last_rev": 34162, "last_value": 582823936.0, "last_err": 199214.54545454544, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_fit", "idx": 0, "pretty_name": "decomposition.PCABenchmark.time_fit('full')", "last_rev": 34162, "last_value": 2.521436789999825, "last_err": 0.031611650718601496, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_fit", "idx": 1, "pretty_name": "decomposition.PCABenchmark.time_fit('arpack')", "last_rev": 34162, "last_value": 1.116302130000122, "last_err": 0.01113547521749386, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_fit", "idx": 2, "pretty_name": "decomposition.PCABenchmark.time_fit('randomized')", "last_rev": 34162, "last_value": 1.096222490000173, "last_err": 0.01936216330927717, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_transform", "idx": 0, "pretty_name": "decomposition.PCABenchmark.time_transform('full')", "last_rev": 34162, "last_value": 0.1595982515000287, "last_err": 0.002211407000113163, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_transform", "idx": 1, "pretty_name": "decomposition.PCABenchmark.time_transform('arpack')", "last_rev": 34162, "last_value": 0.16050076099986654, "last_err": 0.0033931774041660143, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_transform", "idx": 2, "pretty_name": "decomposition.PCABenchmark.time_transform('randomized')", "last_rev": 34162, "last_value": 0.16023792500004674, "last_err": 0.0019148052631305955, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_test_score", "idx": 0, "pretty_name": "decomposition.PCABenchmark.track_test_score('full')", "last_rev": 34162, "last_value": 0.7449418902397156, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_test_score", "idx": 1, "pretty_name": "decomposition.PCABenchmark.track_test_score('arpack')", "last_rev": 34162, "last_value": 0.7449416518211365, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_test_score", "idx": 2, "pretty_name": "decomposition.PCABenchmark.track_test_score('randomized')", "last_rev": 34162, "last_value": 0.7449308037757874, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_train_score", "idx": 0, "pretty_name": "decomposition.PCABenchmark.track_train_score('full')", "last_rev": 34162, "last_value": 0.7445708513259888, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_train_score", "idx": 1, "pretty_name": "decomposition.PCABenchmark.track_train_score('arpack')", "last_rev": 34162, "last_value": 0.7445658445358276, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_train_score", "idx": 2, "pretty_name": "decomposition.PCABenchmark.track_train_score('randomized')", "last_rev": 34162, "last_value": 0.7445555329322815, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('dense')", "last_rev": 34162, "last_value": 92569600.0, "last_err": 376459.63636363635, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('sparse')", "last_rev": 34162, "last_value": 116740096.0, "last_err": 134050.9090909091, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('dense')", "last_rev": 34162, "last_value": 88780800.0, "last_err": 102772.36363636363, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('sparse')", "last_rev": 34162, "last_value": 98451456.0, "last_err": 121018.18181818182, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.time_fit", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.time_fit('dense')", "last_rev": 34162, "last_value": 2.7723530729999766, "last_err": 0.06565145596535218, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.time_fit", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.time_fit('sparse')", "last_rev": 34162, "last_value": 2.3063645810000253, "last_err": 0.06571103447566325, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.time_predict", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.time_predict('dense')", "last_rev": 34162, "last_value": 0.046732778999967195, "last_err": 0.0029049282947861297, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.time_predict", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.time_predict('sparse')", "last_rev": 34162, "last_value": 0.04231454750015473, "last_err": 0.0013460985572397977, "prev_value": 0.0466856689999986, "change_rev": [null, 34141]}, {"name": "ensemble.GradientBoostingClassifierBenchmark.track_test_score", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.track_test_score('dense')", "last_rev": 34162, "last_value": 0.5478068325552989, "last_err": 0.005196979220544528, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.track_test_score", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.track_test_score('sparse')", "last_rev": 34162, "last_value": 0.10409974329281042, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.track_train_score", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.track_train_score('dense')", "last_rev": 34162, "last_value": 0.6296514176013915, "last_err": 0.002915730680344725, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.track_train_score", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.track_train_score('sparse')", "last_rev": 34162, "last_value": 0.15180008167538628, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit", "last_rev": 34162, "last_value": 102899712.0, "last_err": 124369.45454545454, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict", "last_rev": 34162, "last_value": 91103232.0, "last_err": 287092.36363636365, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.time_fit", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.time_fit", "last_rev": 34162, "last_value": 2.44353313900001, "last_err": 0.06870084924502036, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.time_predict", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.time_predict", "last_rev": 34162, "last_value": 0.08462493000001814, "last_err": 0.001603815078990032, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.track_test_score", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.track_test_score", "last_rev": 34162, "last_value": 0.7230709112942986, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.track_train_score", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.track_train_score", "last_rev": 34162, "last_value": 0.9812160155622751, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit('dense', 1)", "last_rev": 34162, "last_value": 179122176.0, "last_err": 270708.36363636365, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit('dense', 4)", "last_rev": 34162, "last_value": 179093504.0, "last_err": 197352.72727272726, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit('sparse', 1)", "last_rev": 34162, "last_value": 402530304.0, "last_err": 146338.9090909091, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit('sparse', 4)", "last_rev": 34162, "last_value": 402624512.0, "last_err": 144477.0909090909, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict('dense', 1)", "last_rev": 34162, "last_value": 182075392.0, "last_err": 138519.27272727274, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict('dense', 4)", "last_rev": 34162, "last_value": 188592128.0, "last_err": 148200.72727272726, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict('sparse', 1)", "last_rev": 34162, "last_value": 402567168.0, "last_err": 141125.81818181818, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict('sparse', 4)", "last_rev": 34162, "last_value": 402677760.0, "last_err": 126976.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_fit", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_fit('dense', 1)", "last_rev": 34162, "last_value": 7.813662172000022, "last_err": 0.3555694201034242, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_fit", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_fit('dense', 4)", "last_rev": 34162, "last_value": 2.631280527999934, "last_err": 0.04314218229782926, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_fit", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_fit('sparse', 1)", "last_rev": 34162, "last_value": 12.425730679000026, "last_err": 1.00728572433086, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_fit", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_fit('sparse', 4)", "last_rev": 34162, "last_value": 3.8722442140001476, "last_err": 0.18107931348335765, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_predict", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_predict('dense', 1)", "last_rev": 34162, "last_value": 0.26201189899984456, "last_err": 0.011136769232258419, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_predict", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_predict('dense', 4)", "last_rev": 34162, "last_value": 0.16428017149996776, "last_err": 0.0026387623512941533, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_predict", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_predict('sparse', 1)", "last_rev": 34162, "last_value": 2.1483221379999122, "last_err": 0.08358498941064361, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_predict", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_predict('sparse', 4)", "last_rev": 34162, "last_value": 0.7737549180001224, "last_err": 0.005023418846541009, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_test_score", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_test_score('dense', 1)", "last_rev": 34162, "last_value": 0.7488528575232659, "last_err": 0.005143903618504323, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_test_score", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_test_score('dense', 4)", "last_rev": 34162, "last_value": 0.7488528575232659, "last_err": 0.005143903618504323, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_test_score", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_test_score('sparse', 1)", "last_rev": 34162, "last_value": 0.8656423941766682, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_test_score", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_test_score('sparse', 4)", "last_rev": 34162, "last_value": 0.8656423941766682, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_train_score", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_train_score('dense', 1)", "last_rev": 34162, "last_value": 0.996908203929455, "last_err": 0.00027985262079545, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_train_score", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_train_score('dense', 4)", "last_rev": 34162, "last_value": 0.996908203929455, "last_err": 0.00027985262079545, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_train_score", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_train_score('sparse', 1)", "last_rev": 34162, "last_value": 0.9996123288718864, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_train_score", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_train_score('sparse', 4)", "last_rev": 34162, "last_value": 0.9996123288718864, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_fit('dense', True)", "last_rev": 34162, "last_value": 852660224.0, "last_err": 111336.72727272728, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_fit('dense', False)", "last_rev": 34162, "last_value": 1208922112.0, "last_err": 116922.18181818182, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_fit", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_fit('sparse', True)", "last_rev": 34162, "last_value": 123682816.0, "last_err": 105378.90909090909, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_fit", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_fit('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_predict('dense', True)", "last_rev": 34162, "last_value": 488431616.0, "last_err": 279645.0909090909, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_predict('dense', False)", "last_rev": 34162, "last_value": 488423424.0, "last_err": 157509.81818181818, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_predict", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_predict('sparse', True)", "last_rev": 34162, "last_value": 96739328.0, "last_err": 113943.27272727272, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_predict", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_predict('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.time_fit('dense', True)", "last_rev": 34162, "last_value": 1.503077243000007, "last_err": 0.014843954396549468, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.time_fit('dense', False)", "last_rev": 34162, "last_value": 1.828222786499964, "last_err": 0.019880329834354185, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_fit", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.time_fit('sparse', True)", "last_rev": 34162, "last_value": 2.6061559649997434, "last_err": 0.14771289079792788, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_fit", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.time_fit('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.time_predict('dense', True)", "last_rev": 34162, "last_value": 0.051866391000203294, "last_err": 0.004119442721528033, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.time_predict('dense', False)", "last_rev": 34162, "last_value": 0.05113379999988865, "last_err": 0.0015332918025328442, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_predict", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.time_predict('sparse', True)", "last_rev": 34162, "last_value": 0.0030675015000269923, "last_err": 0.00027903539270985006, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_predict", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.time_predict('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.track_test_score('dense', True)", "last_rev": 34162, "last_value": 0.9274010856209145, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.track_test_score('dense', False)", "last_rev": 34162, "last_value": 0.9274010850953214, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_test_score", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.track_test_score('sparse', True)", "last_rev": 34162, "last_value": 0.9497792096137744, "last_err": 0.0005585513716672506, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_test_score", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.track_test_score('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.track_train_score('dense', True)", "last_rev": 34162, "last_value": 0.9276022550495941, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.track_train_score('dense', False)", "last_rev": 34162, "last_value": 0.9276022552325599, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_train_score", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.track_train_score('sparse', True)", "last_rev": 34162, "last_value": 0.9562091104795359, "last_err": 0.00022461216069644886, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_train_score", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.track_train_score('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.peakmem_fit('dense', True)", "last_rev": 34162, "last_value": 852664320.0, "last_err": 101282.90909090909, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.peakmem_fit('dense', False)", "last_rev": 34162, "last_value": 1208913920.0, "last_err": 117666.90909090909, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_fit", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.peakmem_fit('sparse', True)", "last_rev": 34162, "last_value": 123674624.0, "last_err": 127348.36363636363, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_fit", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.peakmem_fit('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.peakmem_predict('dense', True)", "last_rev": 34162, "last_value": 488431616.0, "last_err": 311668.36363636365, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.peakmem_predict('dense', False)", "last_rev": 34162, "last_value": 488427520.0, "last_err": 226397.0909090909, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_predict", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.peakmem_predict('sparse', True)", "last_rev": 34162, "last_value": 96755712.0, "last_err": 129210.18181818182, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_predict", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.peakmem_predict('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.time_fit('dense', True)", "last_rev": 34162, "last_value": 1.5131060970002181, "last_err": 0.015563677834600763, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.time_fit('dense', False)", "last_rev": 34162, "last_value": 1.8337169439998888, "last_err": 0.025478206789631655, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_fit", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.time_fit('sparse', True)", "last_rev": 34162, "last_value": 2.4240076305000002, "last_err": 0.16418736212524598, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_fit", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.time_fit('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.time_predict('dense', True)", "last_rev": 34162, "last_value": 0.05168738199972722, "last_err": 0.0017761602162573887, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.time_predict('dense', False)", "last_rev": 34162, "last_value": 0.04877835449997292, "last_err": 0.001250944011182624, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_predict", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.time_predict('sparse', True)", "last_rev": 34162, "last_value": 0.003087816833309868, "last_err": 9.23409141032996e-06, "prev_value": 0.002283395899985408, "change_rev": [34155, 34158]}, {"name": "linear_model.LassoBenchmark.time_predict", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.time_predict('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.track_test_score('dense', True)", "last_rev": 34162, "last_value": 0.9274015024583205, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.track_test_score('dense', False)", "last_rev": 34162, "last_value": 0.9274015028138817, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_test_score", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.track_test_score('sparse', True)", "last_rev": 34162, "last_value": 0.9487190858734746, "last_err": 0.0006481595042771016, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_test_score", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.track_test_score('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.track_train_score('dense', True)", "last_rev": 34162, "last_value": 0.92760249197518, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.track_train_score('dense', False)", "last_rev": 34162, "last_value": 0.9276024919395177, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_train_score", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.track_train_score('sparse', True)", "last_rev": 34162, "last_value": 0.9538195148081864, "last_err": 0.0002434370563241856, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_train_score", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.track_train_score('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.peakmem_fit('dense')", "last_rev": 34162, "last_value": 1214951424.0, "last_err": 92718.54545454546, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.peakmem_fit('sparse')", "last_rev": 34162, "last_value": 236138496.0, "last_err": 164584.72727272726, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.peakmem_predict('dense')", "last_rev": 34162, "last_value": 488456192.0, "last_err": 281134.54545454547, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.peakmem_predict('sparse')", "last_rev": 34162, "last_value": 156499968.0, "last_err": 202193.45454545456, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.time_fit('dense')", "last_rev": 34162, "last_value": 3.1200300549999156, "last_err": 0.018999226476082834, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.time_fit('sparse')", "last_rev": 34162, "last_value": 1.1242004460000317, "last_err": 0.013670159724745345, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.time_predict('dense')", "last_rev": 34162, "last_value": 0.05160755400038397, "last_err": 0.0013435902611902565, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.time_predict('sparse')", "last_rev": 34162, "last_value": 0.03364304449951305, "last_err": 0.0003925523950426968, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.track_test_score('dense')", "last_rev": 34162, "last_value": 0.9274012651798128, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.track_test_score('sparse')", "last_rev": 34162, "last_value": 0.10346956272382513, "last_err": 0.0021357493688620925, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.track_train_score('dense')", "last_rev": 34162, "last_value": 0.927602494829764, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.track_train_score('sparse')", "last_rev": 34162, "last_value": 0.9999999999963929, "last_err": 0.0, "prev_value": 0.9999999999962648, "change_rev": [34160, 34162]}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'lbfgs', 1)", "last_rev": 34162, "last_value": 105373696.0, "last_err": 180224.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'lbfgs', 4)", "last_rev": 34162, "last_value": 98807808.0, "last_err": 150434.9090909091, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 1)", "last_rev": 34162, "last_value": 83296256.0, "last_err": 84526.54545454546, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 4)", "last_rev": 34162, "last_value": 84430848.0, "last_err": 106496.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'lbfgs', 1)", "last_rev": 34162, "last_value": 381874176.0, "last_err": 385768.7272727273, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'lbfgs', 4)", "last_rev": 34162, "last_value": 124952576.0, "last_err": 131072.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 1)", "last_rev": 34162, "last_value": 103944192.0, "last_err": 148573.0909090909, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 4)", "last_rev": 34162, "last_value": 104538112.0, "last_err": 102027.63636363637, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'lbfgs', 1)", "last_rev": 34162, "last_value": 99053568.0, "last_err": 178362.18181818182, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'lbfgs', 4)", "last_rev": 34162, "last_value": 98963456.0, "last_err": 201821.0909090909, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 1)", "last_rev": 34162, "last_value": 86069248.0, "last_err": 125858.90909090909, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 4)", "last_rev": 34162, "last_value": 85995520.0, "last_err": 141125.81818181818, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 1)", "last_rev": 34162, "last_value": 100339712.0, "last_err": 133306.18181818182, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 4)", "last_rev": 34162, "last_value": 100343808.0, "last_err": 154158.54545454544, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 1)", "last_rev": 34162, "last_value": 88096768.0, "last_err": 194001.45454545456, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 4)", "last_rev": 34162, "last_value": 88080384.0, "last_err": 171659.63636363635, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('dense', 'lbfgs', 1)", "last_rev": 34162, "last_value": 0.02250768349995269, "last_err": 0.0009029431650311278, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('dense', 'lbfgs', 4)", "last_rev": 34162, "last_value": 0.18967650499962474, "last_err": 0.0018715577793079524, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('dense', 'saga', 1)", "last_rev": 34162, "last_value": 4.506277077499817, "last_err": 0.3169788933401281, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('dense', 'saga', 4)", "last_rev": 34162, "last_value": 4.935574182499749, "last_err": 0.7981215380986786, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'lbfgs', 1)", "last_rev": 34162, "last_value": 1.0369827390004502, "last_err": 0.048472239699302234, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'lbfgs', 4)", "last_rev": 34162, "last_value": 2.9758953789996667, "last_err": 0.03741090372141409, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 1)", "last_rev": 34162, "last_value": 3.8842646690000038, "last_err": 0.1414335236591501, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 4)", "last_rev": 34162, "last_value": 4.155317227000523, "last_err": 0.27445698689869424, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('dense', 'lbfgs', 1)", "last_rev": 34162, "last_value": 0.0032651716666502275, "last_err": 8.647931450140476e-05, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('dense', 'lbfgs', 4)", "last_rev": 34162, "last_value": 0.0030973771250728532, "last_err": 6.64665304795129e-05, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('dense', 'saga', 1)", "last_rev": 34162, "last_value": 0.0019054025000665813, "last_err": 3.024363271710479e-05, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('dense', 'saga', 4)", "last_rev": 34162, "last_value": 0.0019412794999880134, "last_err": 3.0650203052540764e-05, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'lbfgs', 1)", "last_rev": 34162, "last_value": 0.007595465750000585, "last_err": 0.00038766097348437586, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'lbfgs', 4)", "last_rev": 34162, "last_value": 0.00786672300000646, "last_err": 0.0008872763001305302, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 1)", "last_rev": 34162, "last_value": 0.005045570333398549, "last_err": 0.0014963251893070073, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 4)", "last_rev": 34162, "last_value": 0.006150585500108718, "last_err": 0.0008769187290455965, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('dense', 'lbfgs', 1)", "last_rev": 34162, "last_value": 0.17421305525041922, "last_err": 0.001128193898179669, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('dense', 'lbfgs', 4)", "last_rev": 34162, "last_value": 0.17421305525041922, "last_err": 0.001128193898179669, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('dense', 'saga', 1)", "last_rev": 34162, "last_value": 0.7782283339160001, "last_err": 0.004769972893489713, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('dense', 'saga', 4)", "last_rev": 34162, "last_value": 0.7782283339160001, "last_err": 0.004769972893489713, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('sparse', 'lbfgs', 1)", "last_rev": 34162, "last_value": 0.06538461538461539, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('sparse', 'lbfgs', 4)", "last_rev": 34162, "last_value": 0.06538461538461539, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('sparse', 'saga', 1)", "last_rev": 34162, "last_value": 0.5765140080078162, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('sparse', 'saga', 4)", "last_rev": 34162, "last_value": 0.5765140080078162, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('dense', 'lbfgs', 1)", "last_rev": 34162, "last_value": 0.17918916423043427, "last_err": 0.0007520441386135471, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('dense', 'lbfgs', 4)", "last_rev": 34162, "last_value": 0.17918916423043427, "last_err": 0.0007520441386135471, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('dense', 'saga', 1)", "last_rev": 34162, "last_value": 0.79979023767034, "last_err": 0.001997961484062303, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('dense', 'saga', 4)", "last_rev": 34162, "last_value": 0.79979023767034, "last_err": 0.001997961484062303, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('sparse', 'lbfgs', 1)", "last_rev": 34162, "last_value": 0.0681998556998557, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('sparse', 'lbfgs', 4)", "last_rev": 34162, "last_value": 0.0681998556998557, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('sparse', 'saga', 1)", "last_rev": 34162, "last_value": 0.6908414295256007, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('sparse', 'saga', 4)", "last_rev": 34162, "last_value": 0.6908414295256007, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'auto')", "last_rev": 34162, "last_value": 463544320.0, "last_err": 92718.54545454546, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'svd')", "last_rev": 34162, "last_value": 825061376.0, "last_err": 169797.81818181818, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'cholesky')", "last_rev": 34162, "last_value": 463593472.0, "last_err": 95697.45454545454, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'lsqr')", "last_rev": 34162, "last_value": 472338432.0, "last_err": 82292.36363636363, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'sparse_cg')", "last_rev": 34162, "last_value": 466853888.0, "last_err": 94208.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'sag')", "last_rev": 34162, "last_value": 472276992.0, "last_err": 70376.72727272728, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'saga')", "last_rev": 34162, "last_value": 472281088.0, "last_err": 73355.63636363637, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'auto')", "last_rev": 34162, "last_value": 192503808.0, "last_err": 103517.09090909091, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'cholesky')", "last_rev": 34162, "last_value": 1270849536.0, "last_err": 102027.63636363637, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'lsqr')", "last_rev": 34162, "last_value": 193781760.0, "last_err": 70749.09090909091, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'sparse_cg')", "last_rev": 34162, "last_value": 192475136.0, "last_err": 127348.36363636363, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'sag')", "last_rev": 34162, "last_value": 157974528.0, "last_err": 73355.63636363637, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'saga')", "last_rev": 34162, "last_value": 157958144.0, "last_err": 73728.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'auto')", "last_rev": 34162, "last_value": 282947584.0, "last_err": 166446.54545454544, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'svd')", "last_rev": 34162, "last_value": 282931200.0, "last_err": 214853.81818181818, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'cholesky')", "last_rev": 34162, "last_value": 282955776.0, "last_err": 180224.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'lsqr')", "last_rev": 34162, "last_value": 282947584.0, "last_err": 174638.54545454544, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'sparse_cg')", "last_rev": 34162, "last_value": 282927104.0, "last_err": 157509.81818181818, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'sag')", "last_rev": 34162, "last_value": 282935296.0, "last_err": 199959.27272727274, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'saga')", "last_rev": 34162, "last_value": 282963968.0, "last_err": 174266.18181818182, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'auto')", "last_rev": 34162, "last_value": 118349824.0, "last_err": 523915.63636363635, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'cholesky')", "last_rev": 34162, "last_value": 118349824.0, "last_err": 536576.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'lsqr')", "last_rev": 34162, "last_value": 118349824.0, "last_err": 493009.45454545453, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'sparse_cg')", "last_rev": 34162, "last_value": 118325248.0, "last_err": 464337.45454545453, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'sag')", "last_rev": 34162, "last_value": 118349824.0, "last_err": 484817.45454545453, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'saga')", "last_rev": 34162, "last_value": 118194176.0, "last_err": 447953.45454545453, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'auto')", "last_rev": 34162, "last_value": 0.21205807649994313, "last_err": 0.0018603661621608243, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'svd')", "last_rev": 34162, "last_value": 1.7008452365007543, "last_err": 0.02249660871257914, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'cholesky')", "last_rev": 34162, "last_value": 0.21078016699993896, "last_err": 0.002167001852363307, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'lsqr')", "last_rev": 34162, "last_value": 0.2188873679997414, "last_err": 0.005344983708182634, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'sparse_cg')", "last_rev": 34162, "last_value": 0.25529594299950986, "last_err": 0.006207330063419427, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'sag')", "last_rev": 34162, "last_value": 29.879230076000567, "last_err": 1.696339868397655, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'saga')", "last_rev": 34162, "last_value": 13.622493873999701, "last_err": 0.7969063881188995, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'auto')", "last_rev": 34162, "last_value": 0.15510172350013818, "last_err": 0.005245061900333774, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'cholesky')", "last_rev": 34162, "last_value": 5.48533466400022, "last_err": 0.0861406476627785, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'lsqr')", "last_rev": 34162, "last_value": 0.13863539800013314, "last_err": 0.003817521241117032, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'sparse_cg')", "last_rev": 34162, "last_value": 0.1570656554999914, "last_err": 0.003983508393835867, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'sag')", "last_rev": 34162, "last_value": 2.55703478399937, "last_err": 0.16979926983201554, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'saga')", "last_rev": 34162, "last_value": 2.0900424494998333, "last_err": 0.11631988027745836, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'auto')", "last_rev": 34162, "last_value": 0.02546200550023059, "last_err": 0.0007630070589299979, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'svd')", "last_rev": 34162, "last_value": 0.025584234500001912, "last_err": 0.0008112075763613597, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'cholesky')", "last_rev": 34162, "last_value": 0.025243295000109356, "last_err": 0.0007482462492606552, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'lsqr')", "last_rev": 34162, "last_value": 0.025335637000353017, "last_err": 0.00040838689394622396, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'sparse_cg')", "last_rev": 34162, "last_value": 0.025326453000161564, "last_err": 0.0007914153944474777, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'sag')", "last_rev": 34162, "last_value": 0.025330991500140954, "last_err": 0.0006750659545281653, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'saga')", "last_rev": 34162, "last_value": 0.025620242500281165, "last_err": 0.0006212290993713531, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'auto')", "last_rev": 34162, "last_value": 0.0077384387500387675, "last_err": 0.00032816425554741535, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'cholesky')", "last_rev": 34162, "last_value": 0.007006187999877511, "last_err": 0.00036458462835308776, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'lsqr')", "last_rev": 34162, "last_value": 0.0076984382501450455, "last_err": 0.0003512327838812457, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'sparse_cg')", "last_rev": 34162, "last_value": 0.00765860525007156, "last_err": 0.00028758240100454547, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'sag')", "last_rev": 34162, "last_value": 0.007035577750002631, "last_err": 0.0002643568298174447, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'saga')", "last_rev": 34162, "last_value": 0.007035252000150649, "last_err": 0.0003339738764644004, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'auto')", "last_rev": 34162, "last_value": 0.943399575027382, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'svd')", "last_rev": 34162, "last_value": 0.9433995638980545, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'cholesky')", "last_rev": 34162, "last_value": 0.943399575027382, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'lsqr')", "last_rev": 34162, "last_value": 0.9433995757192792, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'sparse_cg')", "last_rev": 34162, "last_value": 0.9433995989989826, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'sag')", "last_rev": 34162, "last_value": 0.94339933719428, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'saga')", "last_rev": 34162, "last_value": 0.9433995886080997, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'auto')", "last_rev": 34162, "last_value": 0.9564296413459894, "last_err": 0.00041976944075837843, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'cholesky')", "last_rev": 34162, "last_value": 0.9564292115958911, "last_err": 0.00041971103455641266, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'lsqr')", "last_rev": 34162, "last_value": 0.9564296405040651, "last_err": 0.00041976874316251855, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'sparse_cg')", "last_rev": 34162, "last_value": 0.9564296413459894, "last_err": 0.00041976944075837843, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'sag')", "last_rev": 34162, "last_value": 0.9564306494512524, "last_err": 0.00041806067342692825, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'saga')", "last_rev": 34162, "last_value": 0.9564308047541376, "last_err": 0.00041795617104702716, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'auto')", "last_rev": 34162, "last_value": 0.9444001571921127, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'svd')", "last_rev": 34162, "last_value": 0.9444001571502235, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'cholesky')", "last_rev": 34162, "last_value": 0.9444001571921127, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'lsqr')", "last_rev": 34162, "last_value": 0.9444001572131616, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'sparse_cg')", "last_rev": 34162, "last_value": 0.9444001571192623, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'sag')", "last_rev": 34162, "last_value": 0.9444001419121766, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'saga')", "last_rev": 34162, "last_value": 0.9444001543688754, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'auto')", "last_rev": 34162, "last_value": 0.9658271880058364, "last_err": 0.00011450882959635427, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'cholesky')", "last_rev": 34162, "last_value": 0.9658271907352718, "last_err": 0.000114508789061607, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'lsqr')", "last_rev": 34162, "last_value": 0.9658271880698462, "last_err": 0.00011450892017402085, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'sparse_cg')", "last_rev": 34162, "last_value": 0.9658271880058364, "last_err": 0.00011450882959635427, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'sag')", "last_rev": 34162, "last_value": 0.9658236285178574, "last_err": 0.0001145086055172051, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'saga')", "last_rev": 34162, "last_value": 0.9658235966760852, "last_err": 0.00011450809085657784, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.peakmem_fit('dense')", "last_rev": 34162, "last_value": 159371264.0, "last_err": 392843.63636363635, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.peakmem_fit('sparse')", "last_rev": 34162, "last_value": 87830528.0, "last_err": 343691.63636363635, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.peakmem_predict('dense')", "last_rev": 34162, "last_value": 158322688.0, "last_err": 194746.18181818182, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.peakmem_predict('sparse')", "last_rev": 34162, "last_value": 86282240.0, "last_err": 166818.9090909091, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.time_fit('dense')", "last_rev": 34162, "last_value": 5.715017427999555, "last_err": 0.13612365325310477, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.time_fit('sparse')", "last_rev": 34162, "last_value": 4.270766128000105, "last_err": 0.17879044059370489, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.time_predict('dense')", "last_rev": 34162, "last_value": 0.01055697150013657, "last_err": 0.00021461779868163925, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.time_predict('sparse')", "last_rev": 34162, "last_value": 0.002442390800024441, "last_err": 7.228688866203847e-05, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.track_test_score('dense')", "last_rev": 34162, "last_value": 0.9636293915848902, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.track_test_score('sparse')", "last_rev": 34162, "last_value": 0.9618417170356984, "last_err": 0.0005260512093485759, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.track_train_score('dense')", "last_rev": 34162, "last_value": 0.9641785427097553, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.track_train_score('sparse')", "last_rev": 34162, "last_value": 0.9619247755146642, "last_err": 0.00012159444749651723, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.peakmem_fit", "idx": 0, "pretty_name": "manifold.TSNEBenchmark.peakmem_fit('exact')", "last_rev": 34162, "last_value": 89001984.0, "last_err": 131072.0, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.peakmem_fit", "idx": 1, "pretty_name": "manifold.TSNEBenchmark.peakmem_fit('barnes_hut')", "last_rev": 34162, "last_value": 96579584.0, "last_err": 285230.54545454547, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.time_fit", "idx": 0, "pretty_name": "manifold.TSNEBenchmark.time_fit('exact')", "last_rev": 34162, "last_value": 6.458831746500437, "last_err": 0.23584482715692065, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.time_fit", "idx": 1, "pretty_name": "manifold.TSNEBenchmark.time_fit('barnes_hut')", "last_rev": 34162, "last_value": 3.1843909919998623, "last_err": 0.11878792927961959, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.track_test_score", "idx": 0, "pretty_name": "manifold.TSNEBenchmark.track_test_score('exact')", "last_rev": 34162, "last_value": 0.3218818006120378, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.track_test_score", "idx": 1, "pretty_name": "manifold.TSNEBenchmark.track_test_score('barnes_hut')", "last_rev": 34162, "last_value": 0.7243016362190247, "last_err": 0.0, "prev_value": 0.7243015766143799, "change_rev": [34160, 34162]}, {"name": "manifold.TSNEBenchmark.track_train_score", "idx": 0, "pretty_name": "manifold.TSNEBenchmark.track_train_score('exact')", "last_rev": 34162, "last_value": 0.3218818006120378, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.track_train_score", "idx": 1, "pretty_name": "manifold.TSNEBenchmark.track_train_score('barnes_hut')", "last_rev": 34162, "last_value": 0.7243016362190247, "last_err": 0.0, "prev_value": 0.7243015766143799, "change_rev": [34160, 34162]}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 0, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'cosine', 1)", "last_rev": 34162, "last_value": 668495872.0, "last_err": 226024.72727272726, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 1, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'cosine', 4)", "last_rev": 34162, "last_value": 785223680.0, "last_err": 1284654.5454545454, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 2, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'euclidean', 1)", "last_rev": 34162, "last_value": 751386624.0, "last_err": 207778.9090909091, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 3, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'euclidean', 4)", "last_rev": 34162, "last_value": 1055166464.0, "last_err": 34335650.90909091, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 4, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'manhattan', 1)", "last_rev": 34162, "last_value": 254300160.0, "last_err": 141870.54545454544, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 5, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'manhattan', 4)", "last_rev": 34162, "last_value": 337154048.0, "last_err": 8080663.2727272725, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 6, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'correlation', 1)", "last_rev": 34162, "last_value": 247394304.0, "last_err": 141498.18181818182, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 7, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'correlation', 4)", "last_rev": 34162, "last_value": 459751424.0, "last_err": 0.0, "prev_value": 482109440.0, "change_rev": [34160, 34162]}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 8, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'cosine', 1)", "last_rev": 34162, "last_value": 1420025856.0, "last_err": 197352.72727272726, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 9, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'cosine', 4)", "last_rev": 34162, "last_value": 1400074240.0, "last_err": 60277480.72727273, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 10, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'euclidean', 1)", "last_rev": 34162, "last_value": 569806848.0, "last_err": 213736.72727272726, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 11, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'euclidean', 4)", "last_rev": 34162, "last_value": 923725824.0, "last_err": 40791319.27272727, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 12, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'manhattan', 1)", "last_rev": 34162, "last_value": 186806272.0, "last_err": 172404.36363636365, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 13, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'manhattan', 4)", "last_rev": 34162, "last_value": 229142528.0, "last_err": 8009169.454545454, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 14, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'correlation', 1)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 15, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'correlation', 4)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 0, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'cosine', 1)", "last_rev": 34162, "last_value": 1.0948987880001368, "last_err": 0.014927959156243701, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 1, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'cosine', 4)", "last_rev": 34162, "last_value": 1.2531879289999779, "last_err": 0.012028635812422745, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 2, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'euclidean', 1)", "last_rev": 34162, "last_value": 1.73283707399969, "last_err": 0.052703093500497115, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 3, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'euclidean', 4)", "last_rev": 34162, "last_value": 3.059747658499873, "last_err": 0.02903515553858937, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 4, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'manhattan', 1)", "last_rev": 34162, "last_value": 6.330721553499643, "last_err": 0.18446615720957407, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 5, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'manhattan', 4)", "last_rev": 34162, "last_value": 2.6176616529996863, "last_err": 0.01403511594204874, "prev_value": 2.1561904800000775, "change_rev": [34113, 34115]}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 6, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'correlation', 1)", "last_rev": 34162, "last_value": 3.3036505549998765, "last_err": 0.18919458191159524, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 7, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'correlation', 4)", "last_rev": 34162, "last_value": 2.5598424650002016, "last_err": 0.04800928727920854, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 8, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 1)", "last_rev": 34162, "last_value": 4.127793399999973, "last_err": 0.07932543121602367, "prev_value": 3.6725709250004, "change_rev": [null, 34141]}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 9, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 4)", "last_rev": 34162, "last_value": 2.5860535255001196, "last_err": 0.043431763240505634, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 10, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 1)", "last_rev": 34162, "last_value": 2.59981175700068, "last_err": 0.11281936068213061, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 11, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 4)", "last_rev": 34162, "last_value": 2.07176092949976, "last_err": 0.07770147225828282, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 12, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'manhattan', 1)", "last_rev": 34162, "last_value": 1.2255320979998032, "last_err": 0.006669584497198478, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 13, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'manhattan', 4)", "last_rev": 34162, "last_value": 1.3097745579998445, "last_err": 0.011799279539963153, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 14, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'correlation', 1)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 15, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'correlation', 4)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.peakmem_crossval", "idx": 0, "pretty_name": "model_selection.CrossValidationBenchmark.peakmem_crossval(1)", "last_rev": 34162, "last_value": 217960448.0, "last_err": 142987.63636363635, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.peakmem_crossval", "idx": 1, "pretty_name": "model_selection.CrossValidationBenchmark.peakmem_crossval(4)", "last_rev": 34162, "last_value": 118276096.0, "last_err": 165329.45454545456, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.time_crossval", "idx": 0, "pretty_name": "model_selection.CrossValidationBenchmark.time_crossval(1)", "last_rev": 34162, "last_value": 63.216229812000165, "last_err": 6.756808735272648, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.time_crossval", "idx": 1, "pretty_name": "model_selection.CrossValidationBenchmark.time_crossval(4)", "last_rev": 34162, "last_value": 17.233828422999977, "last_err": 0.2389215687293853, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.track_crossval", "idx": 0, "pretty_name": "model_selection.CrossValidationBenchmark.track_crossval(1)", "last_rev": 34162, "last_value": 0.9001555555555555, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.track_crossval", "idx": 1, "pretty_name": "model_selection.CrossValidationBenchmark.track_crossval(4)", "last_rev": 34162, "last_value": 0.9001555555555555, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.peakmem_fit", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.peakmem_fit(1)", "last_rev": 34162, "last_value": 95379456.0, "last_err": 180596.36363636365, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.peakmem_fit", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.peakmem_fit(4)", "last_rev": 34162, "last_value": 92930048.0, "last_err": 173521.45454545456, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.peakmem_predict", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.peakmem_predict(1)", "last_rev": 34162, "last_value": 87748608.0, "last_err": 181713.45454545456, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.peakmem_predict", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.peakmem_predict(4)", "last_rev": 34162, "last_value": 87703552.0, "last_err": 177989.81818181818, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.time_fit", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.time_fit(1)", "last_rev": 34162, "last_value": 346.82019891100026, "last_err": 14.50906068938583, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.time_fit", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.time_fit(4)", "last_rev": 34162, "last_value": 102.37117459599904, "last_err": 0.8113394946675214, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.time_predict", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.time_predict(1)", "last_rev": 34162, "last_value": 0.07095141599984345, "last_err": 0.0006514441521538254, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.time_predict", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.time_predict(4)", "last_rev": 34162, "last_value": 0.07091360399954283, "last_err": 0.0004616244349040294, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.track_test_score", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.track_test_score(1)", "last_rev": 34162, "last_value": 0.8678060899936387, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.track_test_score", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.track_test_score(4)", "last_rev": 34162, "last_value": 0.8678060899936387, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.track_train_score", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.track_train_score(1)", "last_rev": 34162, "last_value": 0.9966662088870577, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.track_train_score", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.track_train_score(4)", "last_rev": 34162, "last_value": 0.9966662088870577, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 1)", "last_rev": 34162, "last_value": 77316096.0, "last_err": 140008.72727272726, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 4)", "last_rev": 34162, "last_value": 77291520.0, "last_err": 136657.45454545456, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 1)", "last_rev": 34162, "last_value": 80805888.0, "last_err": 144104.72727272726, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 4)", "last_rev": 34162, "last_value": 80789504.0, "last_err": 123252.36363636363, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 1)", "last_rev": 34162, "last_value": 80019456.0, "last_err": 231982.54545454544, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 4)", "last_rev": 34162, "last_value": 79953920.0, "last_err": 245015.27272727274, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 1)", "last_rev": 34162, "last_value": 88350720.0, "last_err": 129954.90909090909, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 4)", "last_rev": 34162, "last_value": 88358912.0, "last_err": 129954.90909090909, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 1)", "last_rev": 34162, "last_value": 79970304.0, "last_err": 237195.63636363635, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 4)", "last_rev": 34162, "last_value": 80044032.0, "last_err": 238312.72727272726, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 1)", "last_rev": 34162, "last_value": 88125440.0, "last_err": 130699.63636363637, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 4)", "last_rev": 34162, "last_value": 88125440.0, "last_err": 129582.54545454546, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'low', 1)", "last_rev": 34162, "last_value": 88006656.0, "last_err": 212247.27272727274, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'low', 4)", "last_rev": 34162, "last_value": 88199168.0, "last_err": 234961.45454545456, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'high', 1)", "last_rev": 34162, "last_value": 92938240.0, "last_err": 258048.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'high', 4)", "last_rev": 34162, "last_value": 93036544.0, "last_err": 260654.54545454544, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 1)", "last_rev": 34162, "last_value": 81477632.0, "last_err": 152296.72727272726, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 4)", "last_rev": 34162, "last_value": 83927040.0, "last_err": 252462.54545454544, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 1)", "last_rev": 34162, "last_value": 91095040.0, "last_err": 182830.54545454544, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 4)", "last_rev": 34162, "last_value": 90783744.0, "last_err": 275921.45454545453, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 1)", "last_rev": 34162, "last_value": 81285120.0, "last_err": 156020.36363636365, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 4)", "last_rev": 34162, "last_value": 83734528.0, "last_err": 226024.72727272726, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 1)", "last_rev": 34162, "last_value": 90845184.0, "last_err": 205917.0909090909, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 4)", "last_rev": 34162, "last_value": 90808320.0, "last_err": 192512.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'low', 1)", "last_rev": 34162, "last_value": 0.0015012015714351687, "last_err": 6.660350423762866e-06, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'low', 4)", "last_rev": 34162, "last_value": 0.0010583937999399495, "last_err": 0.00014404029647838845, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'high', 1)", "last_rev": 34162, "last_value": 0.0013467130625031132, "last_err": 0.00011782054979892413, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'high', 4)", "last_rev": 34162, "last_value": 0.001219530888900206, "last_err": 0.00010083534913615241, "prev_value": 0.0017440364999856683, "change_rev": [34115, 34120]}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('kd_tree', 'low', 1)", "last_rev": 34162, "last_value": 0.012145177500315185, "last_err": 0.0014496016914386685, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('kd_tree', 'low', 4)", "last_rev": 34162, "last_value": 0.013822529000208306, "last_err": 0.0020505763610847863, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('kd_tree', 'high', 1)", "last_rev": 34162, "last_value": 0.05890629599980457, "last_err": 0.003980459780463033, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('kd_tree', 'high', 4)", "last_rev": 34162, "last_value": 0.0587864509989231, "last_err": 0.00374908232169657, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'low', 1)", "last_rev": 34162, "last_value": 0.01242584400006308, "last_err": 0.0008780822146723589, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'low', 4)", "last_rev": 34162, "last_value": 0.012252143501427781, "last_err": 0.0003701177961440311, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'high', 1)", "last_rev": 34162, "last_value": 0.03397333799966873, "last_err": 0.0024820135577661604, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'high', 4)", "last_rev": 34162, "last_value": 0.034138146500481525, "last_err": 0.00266350510955441, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('brute', 'low', 1)", "last_rev": 34162, "last_value": 0.09055840200016974, "last_err": 0.00108562618550613, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('brute', 'low', 4)", "last_rev": 34162, "last_value": 0.09047138949972577, "last_err": 0.0014814022138969522, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('brute', 'high', 1)", "last_rev": 34162, "last_value": 0.12946567999915715, "last_err": 0.0026576766679785044, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('brute', 'high', 4)", "last_rev": 34162, "last_value": 0.12964923449999333, "last_err": 0.0010952126616496647, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'low', 1)", "last_rev": 34162, "last_value": 1.2949519209996652, "last_err": 0.05911634334203774, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'low', 4)", "last_rev": 34162, "last_value": 2.8610398105001877, "last_err": 0.07512288052776789, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 1)", "last_rev": 34162, "last_value": 8.30450277500131, "last_err": 0.5435977994952726, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 4)", "last_rev": 34162, "last_value": 8.0518865490003, "last_err": 0.28251103138073935, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'low', 1)", "last_rev": 34162, "last_value": 2.352441653000824, "last_err": 0.17688136159081558, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'low', 4)", "last_rev": 34162, "last_value": 5.639076026998737, "last_err": 0.22167246092919415, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 1)", "last_rev": 34162, "last_value": 8.201274101000308, "last_err": 0.18839957387968417, "prev_value": 7.358123495499967, "change_rev": [34155, 34158]}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 4)", "last_rev": 34162, "last_value": 10.755202964001, "last_err": 0.21895111818438126, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('brute', 'low', 1)", "last_rev": 34162, "last_value": 0.43658423817067005, "last_err": 0.00694867525181955, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('brute', 'low', 4)", "last_rev": 34162, "last_value": 0.43658423817067005, "last_err": 0.00694867525181955, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('brute', 'high', 1)", "last_rev": 34162, "last_value": 0.6616805840891441, "last_err": 0.0057951731478891625, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('brute', 'high', 4)", "last_rev": 34162, "last_value": 0.6616805840891441, "last_err": 0.0057951731478891625, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('kd_tree', 'low', 1)", "last_rev": 34162, "last_value": 0.43658423817067005, "last_err": 0.00694867525181955, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('kd_tree', 'low', 4)", "last_rev": 34162, "last_value": 0.43658423817067005, "last_err": 0.00694867525181955, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('kd_tree', 'high', 1)", "last_rev": 34162, "last_value": 0.6616805840891441, "last_err": 0.0057951731478891625, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('kd_tree', 'high', 4)", "last_rev": 34162, "last_value": 0.6616805840891441, "last_err": 0.0057951731478891625, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('ball_tree', 'low', 1)", "last_rev": 34162, "last_value": 0.43658423817067005, "last_err": 0.00694867525181955, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('ball_tree', 'low', 4)", "last_rev": 34162, "last_value": 0.43658423817067005, "last_err": 0.00694867525181955, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('ball_tree', 'high', 1)", "last_rev": 34162, "last_value": 0.6616805840891441, "last_err": 0.0057951731478891625, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('ball_tree', 'high', 4)", "last_rev": 34162, "last_value": 0.6616805840891441, "last_err": 0.0057951731478891625, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('brute', 'low', 1)", "last_rev": 34162, "last_value": 0.6375753718595948, "last_err": 0.0027710708057752716, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('brute', 'low', 4)", "last_rev": 34162, "last_value": 0.6375753718595948, "last_err": 0.0027710708057752716, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('brute', 'high', 1)", "last_rev": 34162, "last_value": 0.7923535027258366, "last_err": 0.0018076984656294785, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('brute', 'high', 4)", "last_rev": 34162, "last_value": 0.7923535027258366, "last_err": 0.0018076984656294785, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('kd_tree', 'low', 1)", "last_rev": 34162, "last_value": 0.6375753718595948, "last_err": 0.0027710708057752716, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('kd_tree', 'low', 4)", "last_rev": 34162, "last_value": 0.6375753718595948, "last_err": 0.0027710708057752716, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('kd_tree', 'high', 1)", "last_rev": 34162, "last_value": 0.7923535027258366, "last_err": 0.0018076984656294785, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('kd_tree', 'high', 4)", "last_rev": 34162, "last_value": 0.7923535027258366, "last_err": 0.0018076984656294785, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('ball_tree', 'low', 1)", "last_rev": 34162, "last_value": 0.6375753718595948, "last_err": 0.0027710708057752716, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('ball_tree', 'low', 4)", "last_rev": 34162, "last_value": 0.6375753718595948, "last_err": 0.0027710708057752716, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('ball_tree', 'high', 1)", "last_rev": 34162, "last_value": 0.7923535027258366, "last_err": 0.0018076984656294785, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('ball_tree', 'high', 4)", "last_rev": 34162, "last_value": 0.7923535027258366, "last_err": 0.0018076984656294785, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_fit", "idx": 0, "pretty_name": "svm.SVCBenchmark.peakmem_fit('linear')", "last_rev": 34162, "last_value": 276869120.0, "last_err": 134050.9090909091, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_fit", "idx": 1, "pretty_name": "svm.SVCBenchmark.peakmem_fit('poly')", "last_rev": 34162, "last_value": 276889600.0, "last_err": 132561.45454545456, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_fit", "idx": 2, "pretty_name": "svm.SVCBenchmark.peakmem_fit('rbf')", "last_rev": 34162, "last_value": 276885504.0, "last_err": 132189.0909090909, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_fit", "idx": 3, "pretty_name": "svm.SVCBenchmark.peakmem_fit('sigmoid')", "last_rev": 34162, "last_value": 276877312.0, "last_err": 132189.0909090909, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_predict", "idx": 0, "pretty_name": "svm.SVCBenchmark.peakmem_predict('linear')", "last_rev": 34162, "last_value": 204066816.0, "last_err": 262888.7272727273, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_predict", "idx": 1, "pretty_name": "svm.SVCBenchmark.peakmem_predict('poly')", "last_rev": 34162, "last_value": 204066816.0, "last_err": 244642.9090909091, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_predict", "idx": 2, "pretty_name": "svm.SVCBenchmark.peakmem_predict('rbf')", "last_rev": 34162, "last_value": 204066816.0, "last_err": 280762.1818181818, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_predict", "idx": 3, "pretty_name": "svm.SVCBenchmark.peakmem_predict('sigmoid')", "last_rev": 34162, "last_value": 204066816.0, "last_err": 250973.0909090909, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_fit", "idx": 0, "pretty_name": "svm.SVCBenchmark.time_fit('linear')", "last_rev": 34162, "last_value": 1.7080650619991502, "last_err": 0.02595335355228062, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_fit", "idx": 1, "pretty_name": "svm.SVCBenchmark.time_fit('poly')", "last_rev": 34162, "last_value": 1.703582424999695, "last_err": 0.02327995156056946, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_fit", "idx": 2, "pretty_name": "svm.SVCBenchmark.time_fit('rbf')", "last_rev": 34162, "last_value": 1.718418913998903, "last_err": 0.02936679329398746, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_fit", "idx": 3, "pretty_name": "svm.SVCBenchmark.time_fit('sigmoid')", "last_rev": 34162, "last_value": 1.7369195179999224, "last_err": 0.026294338904844224, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_predict", "idx": 0, "pretty_name": "svm.SVCBenchmark.time_predict('linear')", "last_rev": 34162, "last_value": 0.6688483699999779, "last_err": 0.03958830287311826, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_predict", "idx": 1, "pretty_name": "svm.SVCBenchmark.time_predict('poly')", "last_rev": 34162, "last_value": 0.6330361529999209, "last_err": 0.012846309746375913, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_predict", "idx": 2, "pretty_name": "svm.SVCBenchmark.time_predict('rbf')", "last_rev": 34162, "last_value": 1.7370904769995832, "last_err": 0.059995887297261456, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_predict", "idx": 3, "pretty_name": "svm.SVCBenchmark.time_predict('sigmoid')", "last_rev": 34162, "last_value": 0.6335948619998817, "last_err": 0.016471961726224112, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_test_score", "idx": 0, "pretty_name": "svm.SVCBenchmark.track_test_score('linear')", "last_rev": 34162, "last_value": 0.5899537620849096, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_test_score", "idx": 1, "pretty_name": "svm.SVCBenchmark.track_test_score('poly')", "last_rev": 34162, "last_value": 0.5, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_test_score", "idx": 2, "pretty_name": "svm.SVCBenchmark.track_test_score('rbf')", "last_rev": 34162, "last_value": 0.564312736443884, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_test_score", "idx": 3, "pretty_name": "svm.SVCBenchmark.track_test_score('sigmoid')", "last_rev": 34162, "last_value": 0.5710382513661202, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_train_score", "idx": 0, "pretty_name": "svm.SVCBenchmark.track_train_score('linear')", "last_rev": 34162, "last_value": 0.7373393801965231, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_train_score", "idx": 1, "pretty_name": "svm.SVCBenchmark.track_train_score('poly')", "last_rev": 34162, "last_value": 0.6089324618736384, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_train_score", "idx": 2, "pretty_name": "svm.SVCBenchmark.track_train_score('rbf')", "last_rev": 34162, "last_value": 0.7382063936685785, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_train_score", "idx": 3, "pretty_name": "svm.SVCBenchmark.track_train_score('sigmoid')", "last_rev": 34162, "last_value": 0.741296518607443, "last_err": 0.0, "prev_value": null, "change_rev": null}] \ No newline at end of file +[{"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('dense', 'lloyd', 'random')", "last_rev": 34164, "last_value": 103286784.0, "last_err": 195584.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('dense', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 113686528.0, "last_err": 172714.66666666666, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('dense', 'elkan', 'random')", "last_rev": 34164, "last_value": 137228288.0, "last_err": 105813.33333333333, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('dense', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 137596928.0, "last_err": 143360.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('sparse', 'lloyd', 'random')", "last_rev": 34164, "last_value": 254590976.0, "last_err": 157696.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('sparse', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 254595072.0, "last_err": 175786.66666666666, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('sparse', 'elkan', 'random')", "last_rev": 34164, "last_value": 261470208.0, "last_err": 83968.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_fit", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.peakmem_fit('sparse', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 260544512.0, "last_err": 217429.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('dense', 'lloyd', 'random')", "last_rev": 34164, "last_value": 89782272.0, "last_err": 264874.6666666667, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('dense', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 89829376.0, "last_err": 251904.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('dense', 'elkan', 'random')", "last_rev": 34164, "last_value": 89780224.0, "last_err": 246101.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('dense', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 89784320.0, "last_err": 246784.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('sparse', 'lloyd', 'random')", "last_rev": 34164, "last_value": 97452032.0, "last_err": 191829.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('sparse', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 97452032.0, "last_err": 192170.66666666666, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('sparse', 'elkan', 'random')", "last_rev": 34164, "last_value": 97452032.0, "last_err": 191829.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_predict", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.peakmem_predict('sparse', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 97452032.0, "last_err": 191829.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('dense', 'lloyd', 'random')", "last_rev": 34164, "last_value": 120735744.0, "last_err": 142336.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('dense', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 120727552.0, "last_err": 145749.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('dense', 'elkan', 'random')", "last_rev": 34164, "last_value": 120731648.0, "last_err": 139946.66666666666, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('dense', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 120725504.0, "last_err": 144725.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('sparse', 'lloyd', 'random')", "last_rev": 34164, "last_value": 124944384.0, "last_err": 137557.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('sparse', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 124944384.0, "last_err": 137898.66666666666, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('sparse', 'elkan', 'random')", "last_rev": 34164, "last_value": 124944384.0, "last_err": 137557.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.peakmem_transform", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.peakmem_transform('sparse', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 124944384.0, "last_err": 138240.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.time_fit('dense', 'lloyd', 'random')", "last_rev": 34164, "last_value": 0.40211216299996977, "last_err": 0.0020661096837125965, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.time_fit('dense', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 1.1734618240000145, "last_err": 0.022689595273463554, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.time_fit('dense', 'elkan', 'random')", "last_rev": 34164, "last_value": 2.1956100815000354, "last_err": 0.009429868428337835, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.time_fit('dense', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 2.0139847700002065, "last_err": 0.07815693651786672, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.time_fit('sparse', 'lloyd', 'random')", "last_rev": 34164, "last_value": 1.7233169915000417, "last_err": 0.03270287409958725, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.time_fit('sparse', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 4.488032942000018, "last_err": 0.031294624626425384, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.time_fit('sparse', 'elkan', 'random')", "last_rev": 34164, "last_value": 3.469436167500021, "last_err": 0.04182760712630404, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_fit", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.time_fit('sparse', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 5.192366988999993, "last_err": 0.13830691690160465, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.time_predict('dense', 'lloyd', 'random')", "last_rev": 34164, "last_value": 0.005305630999998812, "last_err": 5.3930910804442135e-05, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.time_predict('dense', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 0.005277451000040401, "last_err": 0.00020127879854526048, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.time_predict('dense', 'elkan', 'random')", "last_rev": 34164, "last_value": 0.0050876790000415895, "last_err": 0.00022385661613367772, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.time_predict('dense', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 0.005351551999979165, "last_err": 0.00023492031591053236, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.time_predict('sparse', 'lloyd', 'random')", "last_rev": 34164, "last_value": 0.016569097999877158, "last_err": 0.008125023411725702, "prev_value": 0.027123178999886477, "change_rev": [34141, 34155]}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.time_predict('sparse', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 0.015813256000001275, "last_err": 0.0063982492397086825, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.time_predict('sparse', 'elkan', 'random')", "last_rev": 34164, "last_value": 0.027959162500110324, "last_err": 0.0019408783848688536, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_predict", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.time_predict('sparse', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 0.016581200000132412, "last_err": 0.008460180680328016, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.time_transform('dense', 'lloyd', 'random')", "last_rev": 34164, "last_value": 0.08728195200012578, "last_err": 0.004366218001979567, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.time_transform('dense', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 0.0856344444999877, "last_err": 0.004105273292462157, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'random')", "last_rev": 34164, "last_value": 0.08539509000013368, "last_err": 0.0022048261862235323, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 0.08634586249991116, "last_err": 0.00467014107602201, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'random')", "last_rev": 34164, "last_value": 3.8029851090000193, "last_err": 0.264351758013397, "prev_value": 3.570233304000112, "change_rev": [34120, 34126]}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": 3.8003822919999948, "last_err": 0.426989150928367, "prev_value": 3.5546480730001804, "change_rev": [null, 34141]}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'random')", "last_rev": 34164, "last_value": 3.781139291000045, "last_err": 0.10319967998459419, "prev_value": 3.521388963999925, "change_rev": [null, 34140]}, {"name": "cluster.KMeansBenchmark.time_transform", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": 3.8138180620001094, "last_err": 0.10009800055178408, "prev_value": 3.5410637559998577, "change_rev": [null, 34140]}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'random')", "last_rev": 34164, "last_value": -4.109886169433594, "last_err": 0.0, "prev_value": -4.109885215759277, "change_rev": [34162, 34164]}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": -3.0753684043884277, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'random')", "last_rev": 34164, "last_value": -4.109886169433594, "last_err": 0.0, "prev_value": -4.109885215759277, "change_rev": [34158, 34160]}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": -3.0753684043884277, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.track_test_score('sparse', 'lloyd', 'random')", "last_rev": 34164, "last_value": -0.9266619682312012, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.track_test_score('sparse', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": -0.9249227643013, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.track_test_score('sparse', 'elkan', 'random')", "last_rev": 34164, "last_value": -0.9266619682312012, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_test_score", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.track_test_score('sparse', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": -0.9249262809753418, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 0, "pretty_name": "cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'random')", "last_rev": 34164, "last_value": -4.1075520515441895, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 1, "pretty_name": "cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": -3.0780560970306396, "last_err": 0.0, "prev_value": -3.0780563354492188, "change_rev": [34162, 34164]}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 2, "pretty_name": "cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'random')", "last_rev": 34164, "last_value": -4.1075520515441895, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 3, "pretty_name": "cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": -3.0780560970306396, "last_err": 0.0, "prev_value": -3.0780563354492188, "change_rev": [34162, 34164]}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 4, "pretty_name": "cluster.KMeansBenchmark.track_train_score('sparse', 'lloyd', 'random')", "last_rev": 34164, "last_value": -0.9227071404457092, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 5, "pretty_name": "cluster.KMeansBenchmark.track_train_score('sparse', 'lloyd', 'k-means++')", "last_rev": 34164, "last_value": -0.922096312046051, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 6, "pretty_name": "cluster.KMeansBenchmark.track_train_score('sparse', 'elkan', 'random')", "last_rev": 34164, "last_value": -0.9227071404457092, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.KMeansBenchmark.track_train_score", "idx": 7, "pretty_name": "cluster.KMeansBenchmark.track_train_score('sparse', 'elkan', 'k-means++')", "last_rev": 34164, "last_value": -0.9221000075340271, "last_err": 0.0, "prev_value": -0.9221000671386719, "change_rev": [34113, 34115]}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'random')", "last_rev": 34164, "last_value": 90900480.0, "last_err": 222890.66666666666, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'k-means++')", "last_rev": 34164, "last_value": 91494400.0, "last_err": 252586.66666666666, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit('sparse', 'random')", "last_rev": 34164, "last_value": 173944832.0, "last_err": 236885.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit('sparse', 'k-means++')", "last_rev": 34164, "last_value": 175568896.0, "last_err": 209920.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'random')", "last_rev": 34164, "last_value": 88123392.0, "last_err": 175104.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'k-means++')", "last_rev": 34164, "last_value": 88088576.0, "last_err": 219136.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'random')", "last_rev": 34164, "last_value": 103346176.0, "last_err": 190805.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'k-means++')", "last_rev": 34164, "last_value": 103346176.0, "last_err": 190464.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'random')", "last_rev": 34164, "last_value": 119031808.0, "last_err": 173056.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'k-means++')", "last_rev": 34164, "last_value": 119054336.0, "last_err": 168618.66666666666, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'random')", "last_rev": 34164, "last_value": 124094464.0, "last_err": 149504.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'k-means++')", "last_rev": 34164, "last_value": 124102656.0, "last_err": 140629.33333333334, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_fit", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_fit('dense', 'random')", "last_rev": 34164, "last_value": 0.4785985524999887, "last_err": 0.006051383938733367, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_fit", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_fit('dense', 'k-means++')", "last_rev": 34164, "last_value": 0.48150149399998554, "last_err": 0.00963689051498589, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_fit", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_fit('sparse', 'random')", "last_rev": 34164, "last_value": 0.6201266324999324, "last_err": 0.04830507906069526, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_fit", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_fit('sparse', 'k-means++')", "last_rev": 34164, "last_value": 1.6373085924999486, "last_err": 0.034799677970196695, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_predict", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_predict('dense', 'random')", "last_rev": 34164, "last_value": 0.0053397412500544306, "last_err": 0.00023419885131658181, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_predict", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_predict('dense', 'k-means++')", "last_rev": 34164, "last_value": 0.0053344940000101815, "last_err": 0.0003411604918773482, "prev_value": 0.008202626499951293, "change_rev": [34113, 34115]}, {"name": "cluster.MiniBatchKMeansBenchmark.time_predict", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_predict('sparse', 'random')", "last_rev": 34164, "last_value": 0.03659826950001843, "last_err": 0.0023247549684810224, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_predict", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_predict('sparse', 'k-means++')", "last_rev": 34164, "last_value": 0.036925888000041596, "last_err": 0.0027685714797727884, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_transform", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'random')", "last_rev": 34164, "last_value": 0.09233130500001607, "last_err": 0.004302009244528651, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_transform", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'k-means++')", "last_rev": 34164, "last_value": 0.09256515350011796, "last_err": 0.007273071296538991, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_transform", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_transform('sparse', 'random')", "last_rev": 34164, "last_value": 7.120454630999916, "last_err": 0.2944976904712803, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.time_transform", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.time_transform('sparse', 'k-means++')", "last_rev": 34164, "last_value": 7.153372103500033, "last_err": 0.2125394066993386, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_test_score", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_test_score('dense', 'random')", "last_rev": 34164, "last_value": -4.596621036529541, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_test_score", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_test_score('dense', 'k-means++')", "last_rev": 34164, "last_value": -3.1085314750671387, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_test_score", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_test_score('sparse', 'random')", "last_rev": 34164, "last_value": -0.9366871118545532, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_test_score", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_test_score('sparse', 'k-means++')", "last_rev": 34164, "last_value": -0.9386959075927734, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_train_score", "idx": 0, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_train_score('dense', 'random')", "last_rev": 34164, "last_value": -4.584851264953613, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_train_score", "idx": 1, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_train_score('dense', 'k-means++')", "last_rev": 34164, "last_value": -3.115997314453125, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_train_score", "idx": 2, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_train_score('sparse', 'random')", "last_rev": 34164, "last_value": -0.9323447346687317, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "cluster.MiniBatchKMeansBenchmark.track_train_score", "idx": 3, "pretty_name": "cluster.MiniBatchKMeansBenchmark.track_train_score('sparse', 'k-means++')", "last_rev": 34164, "last_value": -0.934399425983429, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_fit", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_fit('lars', 1)", "last_rev": 34164, "last_value": 109213696.0, "last_err": 185344.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_fit", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_fit('lars', 4)", "last_rev": 34164, "last_value": 130091008.0, "last_err": 262826.6666666667, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_fit", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_fit('cd', 1)", "last_rev": 34164, "last_value": 103284736.0, "last_err": 303445.3333333333, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_fit", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_fit('cd', 4)", "last_rev": 34164, "last_value": 130183168.0, "last_err": 283989.3333333333, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_transform", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 1)", "last_rev": 34164, "last_value": 85084160.0, "last_err": 86016.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_transform", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 4)", "last_rev": 34164, "last_value": 87187456.0, "last_err": 176128.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_transform", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_transform('cd', 1)", "last_rev": 34164, "last_value": 85057536.0, "last_err": 89429.33333333333, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.peakmem_transform", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.peakmem_transform('cd', 4)", "last_rev": 34164, "last_value": 87187456.0, "last_err": 174421.33333333334, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_fit", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_fit('lars', 1)", "last_rev": 34164, "last_value": 18.021907939000357, "last_err": 1.0137284247036837, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_fit", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_fit('lars', 4)", "last_rev": 34164, "last_value": 10.113518836999901, "last_err": 0.29675012884918966, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_fit", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_fit('cd', 1)", "last_rev": 34164, "last_value": 0.7538921509999454, "last_err": 0.02340332833894392, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_fit", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_fit('cd', 4)", "last_rev": 34164, "last_value": 3.3651072499999373, "last_err": 0.15139458612951504, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_transform", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_transform('lars', 1)", "last_rev": 34164, "last_value": 0.23485662950020014, "last_err": 0.015650925191798216, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_transform", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_transform('lars', 4)", "last_rev": 34164, "last_value": 0.29691259550031646, "last_err": 0.011503613937839913, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_transform", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_transform('cd', 1)", "last_rev": 34164, "last_value": 0.24220178549990123, "last_err": 0.009209680686841847, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.time_transform", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.time_transform('cd', 4)", "last_rev": 34164, "last_value": 0.29205190199991193, "last_err": 0.004366670615352861, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_test_score", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_test_score('lars', 1)", "last_rev": 34164, "last_value": -0.07475553452968597, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_test_score", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_test_score('lars', 4)", "last_rev": 34164, "last_value": -0.07475553452713135, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_test_score", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_test_score('cd', 1)", "last_rev": 34164, "last_value": -0.07475554198026657, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_test_score", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_test_score('cd', 4)", "last_rev": 34164, "last_value": -0.07475553814463735, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_train_score", "idx": 0, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_train_score('lars', 1)", "last_rev": 34164, "last_value": -0.07231885939836502, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_train_score", "idx": 1, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_train_score('lars', 4)", "last_rev": 34164, "last_value": -0.07231886142463793, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_train_score", "idx": 2, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_train_score('cd', 1)", "last_rev": 34164, "last_value": -0.07231885939836502, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.DictionaryLearningBenchmark.track_train_score", "idx": 3, "pretty_name": "decomposition.DictionaryLearningBenchmark.track_train_score('cd', 4)", "last_rev": 34164, "last_value": -0.07231886151447059, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('lars', 1)", "last_rev": 34164, "last_value": 97617920.0, "last_err": 185002.66666666666, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('lars', 4)", "last_rev": 34164, "last_value": 107925504.0, "last_err": 443392.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('cd', 1)", "last_rev": 34164, "last_value": 97509376.0, "last_err": 179882.66666666666, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('cd', 4)", "last_rev": 34164, "last_value": 107720704.0, "last_err": 340650.6666666667, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 1)", "last_rev": 34164, "last_value": 86265856.0, "last_err": 122197.33333333333, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 4)", "last_rev": 34164, "last_value": 87992320.0, "last_err": 203434.66666666666, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 1)", "last_rev": 34164, "last_value": 86099968.0, "last_err": 113322.66666666667, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 4)", "last_rev": 34164, "last_value": 87990272.0, "last_err": 202752.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('lars', 1)", "last_rev": 34164, "last_value": 10.678223337999952, "last_err": 0.3371357743092674, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('lars', 4)", "last_rev": 34164, "last_value": 20.457598145000247, "last_err": 1.6960928075458461, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 1)", "last_rev": 34164, "last_value": 3.080503712499876, "last_err": 0.08492059421762888, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 4)", "last_rev": 34164, "last_value": 19.35254050200001, "last_err": 1.1942842547702504, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('lars', 1)", "last_rev": 34164, "last_value": 0.2381800010000461, "last_err": 0.009766153239437936, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('lars', 4)", "last_rev": 34164, "last_value": 0.3009983940000893, "last_err": 0.006047593440997349, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('cd', 1)", "last_rev": 34164, "last_value": 0.22955045300000165, "last_err": 0.010451897324660406, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('cd', 4)", "last_rev": 34164, "last_value": 0.301076135500125, "last_err": 0.004123304383943554, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('lars', 1)", "last_rev": 34164, "last_value": -0.07506909221410751, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('lars', 4)", "last_rev": 34164, "last_value": -0.0750688759007175, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('cd', 1)", "last_rev": 34164, "last_value": -0.0750984251499176, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('cd', 4)", "last_rev": 34164, "last_value": -0.07509369093642158, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score", "idx": 0, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 1)", "last_rev": 34164, "last_value": -0.07244396954774857, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score", "idx": 1, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 4)", "last_rev": 34164, "last_value": -0.072444055250929, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score", "idx": 2, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('cd', 1)", "last_rev": 34164, "last_value": -0.07244586199522018, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score", "idx": 3, "pretty_name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('cd', 4)", "last_rev": 34164, "last_value": -0.07244519704497496, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.peakmem_fit", "idx": 0, "pretty_name": "decomposition.PCABenchmark.peakmem_fit('full')", "last_rev": 34164, "last_value": 907470848.0, "last_err": 498346.6666666667, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.peakmem_fit", "idx": 1, "pretty_name": "decomposition.PCABenchmark.peakmem_fit('arpack')", "last_rev": 34164, "last_value": 605059072.0, "last_err": 191488.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.peakmem_fit", "idx": 2, "pretty_name": "decomposition.PCABenchmark.peakmem_fit('randomized')", "last_rev": 34164, "last_value": 631975936.0, "last_err": 247249.45454545456, "prev_value": 622297088.0, "change_rev": [34113, 34115]}, {"name": "decomposition.PCABenchmark.peakmem_transform", "idx": 0, "pretty_name": "decomposition.PCABenchmark.peakmem_transform('full')", "last_rev": 34164, "last_value": 582707200.0, "last_err": 228693.33333333334, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.peakmem_transform", "idx": 1, "pretty_name": "decomposition.PCABenchmark.peakmem_transform('arpack')", "last_rev": 34164, "last_value": 582770688.0, "last_err": 118101.33333333333, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.peakmem_transform", "idx": 2, "pretty_name": "decomposition.PCABenchmark.peakmem_transform('randomized')", "last_rev": 34164, "last_value": 582758400.0, "last_err": 231424.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_fit", "idx": 0, "pretty_name": "decomposition.PCABenchmark.time_fit('full')", "last_rev": 34164, "last_value": 2.480745754000054, "last_err": 0.03969790459337241, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_fit", "idx": 1, "pretty_name": "decomposition.PCABenchmark.time_fit('arpack')", "last_rev": 34164, "last_value": 1.1125587534997976, "last_err": 0.011657900483220345, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_fit", "idx": 2, "pretty_name": "decomposition.PCABenchmark.time_fit('randomized')", "last_rev": 34164, "last_value": 1.1123904684998251, "last_err": 0.019835461474269307, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_transform", "idx": 0, "pretty_name": "decomposition.PCABenchmark.time_transform('full')", "last_rev": 34164, "last_value": 0.1595982515000287, "last_err": 0.002135206437966457, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_transform", "idx": 1, "pretty_name": "decomposition.PCABenchmark.time_transform('arpack')", "last_rev": 34164, "last_value": 0.16050076099986654, "last_err": 0.0033289971441002124, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.time_transform", "idx": 2, "pretty_name": "decomposition.PCABenchmark.time_transform('randomized')", "last_rev": 34164, "last_value": 0.16022983500010923, "last_err": 0.0015453421158563242, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_test_score", "idx": 0, "pretty_name": "decomposition.PCABenchmark.track_test_score('full')", "last_rev": 34164, "last_value": 0.7449418902397156, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_test_score", "idx": 1, "pretty_name": "decomposition.PCABenchmark.track_test_score('arpack')", "last_rev": 34164, "last_value": 0.7449416518211365, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_test_score", "idx": 2, "pretty_name": "decomposition.PCABenchmark.track_test_score('randomized')", "last_rev": 34164, "last_value": 0.7449308037757874, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_train_score", "idx": 0, "pretty_name": "decomposition.PCABenchmark.track_train_score('full')", "last_rev": 34164, "last_value": 0.7445708513259888, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_train_score", "idx": 1, "pretty_name": "decomposition.PCABenchmark.track_train_score('arpack')", "last_rev": 34164, "last_value": 0.7445658445358276, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "decomposition.PCABenchmark.track_train_score", "idx": 2, "pretty_name": "decomposition.PCABenchmark.track_train_score('randomized')", "last_rev": 34164, "last_value": 0.7445555329322815, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('dense')", "last_rev": 34164, "last_value": 91164672.0, "last_err": 92842.66666666667, "prev_value": 92704768.0, "change_rev": [34158, 34160]}, {"name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('sparse')", "last_rev": 34164, "last_value": 116770816.0, "last_err": 141994.66666666666, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('dense')", "last_rev": 34164, "last_value": 88784896.0, "last_err": 95232.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('sparse')", "last_rev": 34164, "last_value": 98443264.0, "last_err": 112981.33333333333, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.time_fit", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.time_fit('dense')", "last_rev": 34164, "last_value": 2.7723530729999766, "last_err": 0.06351032222421822, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.time_fit", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.time_fit('sparse')", "last_rev": 34164, "last_value": 2.2923448010001266, "last_err": 0.07425902426430557, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.time_predict", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.time_predict('dense')", "last_rev": 34164, "last_value": 0.04937785099991743, "last_err": 0.0028319381780353425, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.time_predict", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.time_predict('sparse')", "last_rev": 34164, "last_value": 0.04498867249981231, "last_err": 0.002059733970927618, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.track_test_score", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.track_test_score('dense')", "last_rev": 34164, "last_value": 0.548255944208701, "last_err": 0.005299757555270336, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.track_test_score", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.track_test_score('sparse')", "last_rev": 34164, "last_value": 0.10409974329281042, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.track_train_score", "idx": 0, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.track_train_score('dense')", "last_rev": 34164, "last_value": 0.6300606823733521, "last_err": 0.002957867024810675, "prev_value": null, "change_rev": null}, {"name": "ensemble.GradientBoostingClassifierBenchmark.track_train_score", "idx": 1, "pretty_name": "ensemble.GradientBoostingClassifierBenchmark.track_train_score('sparse')", "last_rev": 34164, "last_value": 0.15180008167538628, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit", "last_rev": 34164, "last_value": 102912000.0, "last_err": 129365.33333333333, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict", "last_rev": 34164, "last_value": 91125760.0, "last_err": 266922.6666666667, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.time_fit", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.time_fit", "last_rev": 34164, "last_value": 2.4368824595001115, "last_err": 0.07557675232759543, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.time_predict", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.time_predict", "last_rev": 34164, "last_value": 0.08462493000001814, "last_err": 0.0017020201875910708, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.track_test_score", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.track_test_score", "last_rev": 34164, "last_value": 0.7230709112942986, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.HistGradientBoostingClassifierBenchmark.track_train_score", "idx": null, "pretty_name": "ensemble.HistGradientBoostingClassifierBenchmark.track_train_score", "last_rev": 34164, "last_value": 0.9812160155622751, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit('dense', 1)", "last_rev": 34164, "last_value": 179087360.0, "last_err": 284330.6666666667, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit('dense', 4)", "last_rev": 34164, "last_value": 179011584.0, "last_err": 218112.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit('sparse', 1)", "last_rev": 34164, "last_value": 402501632.0, "last_err": 153258.66666666666, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit('sparse', 4)", "last_rev": 34164, "last_value": 402593792.0, "last_err": 139605.33333333334, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict('dense', 1)", "last_rev": 34164, "last_value": 182065152.0, "last_err": 166912.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict('dense', 4)", "last_rev": 34164, "last_value": 188585984.0, "last_err": 181589.33333333334, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict('sparse', 1)", "last_rev": 34164, "last_value": 402538496.0, "last_err": 151893.33333333334, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict('sparse', 4)", "last_rev": 34164, "last_value": 402649088.0, "last_err": 129365.33333333333, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_fit", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_fit('dense', 1)", "last_rev": 34164, "last_value": 7.813662172000022, "last_err": 0.4561080044887691, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_fit", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_fit('dense', 4)", "last_rev": 34164, "last_value": 2.6205434250000508, "last_err": 0.04056419161839598, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_fit", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_fit('sparse', 1)", "last_rev": 34164, "last_value": 12.80511913600003, "last_err": 0.755017350275367, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_fit", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_fit('sparse', 4)", "last_rev": 34164, "last_value": 3.8722442140001476, "last_err": 0.16637572061719993, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_predict", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_predict('dense', 1)", "last_rev": 34164, "last_value": 0.26201189899984456, "last_err": 0.013778986057732034, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_predict", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_predict('dense', 4)", "last_rev": 34164, "last_value": 0.1642423409998628, "last_err": 0.0008688364166421558, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_predict", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_predict('sparse', 1)", "last_rev": 34164, "last_value": 2.1483221379999122, "last_err": 0.0835207004606691, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.time_predict", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.time_predict('sparse', 4)", "last_rev": 34164, "last_value": 0.7737549180001224, "last_err": 0.00508738238697516, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_test_score", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_test_score('dense', 1)", "last_rev": 34164, "last_value": 0.7493806024660377, "last_err": 0.004928549640821113, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_test_score", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_test_score('dense', 4)", "last_rev": 34164, "last_value": 0.7493806024660377, "last_err": 0.004928549640821113, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_test_score", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_test_score('sparse', 1)", "last_rev": 34164, "last_value": 0.8656423941766682, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_test_score", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_test_score('sparse', 4)", "last_rev": 34164, "last_value": 0.8656423941766682, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_train_score", "idx": 0, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_train_score('dense', 1)", "last_rev": 34164, "last_value": 0.9969915371987892, "last_err": 0.0003218946498732833, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_train_score", "idx": 1, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_train_score('dense', 4)", "last_rev": 34164, "last_value": 0.9969915371987892, "last_err": 0.0003218946498732833, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_train_score", "idx": 2, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_train_score('sparse', 1)", "last_rev": 34164, "last_value": 0.9996123288718864, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "ensemble.RandomForestClassifierBenchmark.track_train_score", "idx": 3, "pretty_name": "ensemble.RandomForestClassifierBenchmark.track_train_score('sparse', 4)", "last_rev": 34164, "last_value": 0.9996123288718864, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_fit('dense', True)", "last_rev": 34164, "last_value": 852631552.0, "last_err": 121856.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_fit('dense', False)", "last_rev": 34164, "last_value": 1208907776.0, "last_err": 134485.33333333334, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_fit", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_fit('sparse', True)", "last_rev": 34164, "last_value": 123662336.0, "last_err": 110250.66666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_fit", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_fit('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_predict('dense', True)", "last_rev": 34164, "last_value": 488443904.0, "last_err": 263850.6666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_predict('dense', False)", "last_rev": 34164, "last_value": 488429568.0, "last_err": 157696.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_predict", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_predict('sparse', True)", "last_rev": 34164, "last_value": 96747520.0, "last_err": 105813.33333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.peakmem_predict", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.peakmem_predict('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.time_fit('dense', True)", "last_rev": 34164, "last_value": 1.4946025629997166, "last_err": 0.015214085759278935, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.time_fit('dense', False)", "last_rev": 34164, "last_value": 1.8216339539999353, "last_err": 0.023724308897498797, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_fit", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.time_fit('sparse', True)", "last_rev": 34164, "last_value": 2.6061559649997434, "last_err": 0.17734529959401613, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_fit", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.time_fit('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.time_predict('dense', True)", "last_rev": 34164, "last_value": 0.050347782499784444, "last_err": 0.002583824549374902, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.time_predict('dense', False)", "last_rev": 34164, "last_value": 0.05033106250016317, "last_err": 0.0013251317663702574, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_predict", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.time_predict('sparse', True)", "last_rev": 34164, "last_value": 0.0026252118999764203, "last_err": 0.00029036582385162137, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.time_predict", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.time_predict('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.track_test_score('dense', True)", "last_rev": 34164, "last_value": 0.9274010856209145, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.track_test_score('dense', False)", "last_rev": 34164, "last_value": 0.9274010850953214, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_test_score", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.track_test_score('sparse', True)", "last_rev": 34164, "last_value": 0.9500510999392209, "last_err": 0.0005609850966214655, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_test_score", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.track_test_score('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.ElasticNetBenchmark.track_train_score('dense', True)", "last_rev": 34164, "last_value": 0.9276022550495941, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.ElasticNetBenchmark.track_train_score('dense', False)", "last_rev": 34164, "last_value": 0.9276022552325599, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_train_score", "idx": 2, "pretty_name": "linear_model.ElasticNetBenchmark.track_train_score('sparse', True)", "last_rev": 34164, "last_value": 0.9561562506001142, "last_err": 0.000247527837465622, "prev_value": null, "change_rev": null}, {"name": "linear_model.ElasticNetBenchmark.track_train_score", "idx": 3, "pretty_name": "linear_model.ElasticNetBenchmark.track_train_score('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.peakmem_fit('dense', True)", "last_rev": 34164, "last_value": 852637696.0, "last_err": 112981.33333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.peakmem_fit('dense', False)", "last_rev": 34164, "last_value": 1208901632.0, "last_err": 134826.66666666666, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_fit", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.peakmem_fit('sparse', True)", "last_rev": 34164, "last_value": 123660288.0, "last_err": 127317.33333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_fit", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.peakmem_fit('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.peakmem_predict('dense', True)", "last_rev": 34164, "last_value": 488450048.0, "last_err": 305834.6666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.peakmem_predict('dense', False)", "last_rev": 34164, "last_value": 488482816.0, "last_err": 228352.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_predict", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.peakmem_predict('sparse', True)", "last_rev": 34164, "last_value": 96761856.0, "last_err": 119466.66666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.peakmem_predict", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.peakmem_predict('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.time_fit('dense', True)", "last_rev": 34164, "last_value": 1.5111102109999592, "last_err": 0.01728927568936588, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.time_fit('dense', False)", "last_rev": 34164, "last_value": 1.8104580019999048, "last_err": 0.024753827974596312, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_fit", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.time_fit('sparse', True)", "last_rev": 34164, "last_value": 2.3619796595000935, "last_err": 0.011802238033826398, "prev_value": 2.7018208590006907, "change_rev": [34158, 34160]}, {"name": "linear_model.LassoBenchmark.time_fit", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.time_fit('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.time_predict('dense', True)", "last_rev": 34164, "last_value": 0.05168738199972722, "last_err": 0.0019680856175779467, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.time_predict('dense', False)", "last_rev": 34164, "last_value": 0.049300229500204296, "last_err": 0.0012051726984532733, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.time_predict", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.time_predict('sparse', True)", "last_rev": 34164, "last_value": 0.003087816833309868, "last_err": 1.2032780710215388e-05, "prev_value": 0.002283395899985408, "change_rev": [34155, 34158]}, {"name": "linear_model.LassoBenchmark.time_predict", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.time_predict('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.track_test_score('dense', True)", "last_rev": 34164, "last_value": 0.9274015024583205, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.track_test_score('dense', False)", "last_rev": 34164, "last_value": 0.9274015028138817, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_test_score", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.track_test_score('sparse', True)", "last_rev": 34164, "last_value": 0.9488794424957308, "last_err": 0.0006255764616452109, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_test_score", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.track_test_score('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.LassoBenchmark.track_train_score('dense', True)", "last_rev": 34164, "last_value": 0.92760249197518, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.LassoBenchmark.track_train_score('dense', False)", "last_rev": 34164, "last_value": 0.9276024919395177, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_train_score", "idx": 2, "pretty_name": "linear_model.LassoBenchmark.track_train_score('sparse', True)", "last_rev": 34164, "last_value": 0.9537046902427806, "last_err": 0.00026283958391747536, "prev_value": null, "change_rev": null}, {"name": "linear_model.LassoBenchmark.track_train_score", "idx": 3, "pretty_name": "linear_model.LassoBenchmark.track_train_score('sparse', False)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.peakmem_fit('dense')", "last_rev": 34164, "last_value": 1214941184.0, "last_err": 104789.33333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.peakmem_fit('sparse')", "last_rev": 34164, "last_value": 236109824.0, "last_err": 178858.66666666666, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.peakmem_predict('dense')", "last_rev": 34164, "last_value": 488458240.0, "last_err": 279210.6666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.peakmem_predict('sparse')", "last_rev": 34164, "last_value": 156442624.0, "last_err": 221866.66666666666, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.time_fit('dense')", "last_rev": 34164, "last_value": 3.1200300549999156, "last_err": 0.01807448915655741, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.time_fit('sparse')", "last_rev": 34164, "last_value": 1.119999438999912, "last_err": 0.013934663078795125, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.time_predict('dense')", "last_rev": 34164, "last_value": 0.05160755400038397, "last_err": 0.001400617158000595, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.time_predict('sparse')", "last_rev": 34164, "last_value": 0.03364304449951305, "last_err": 0.00037570617644025364, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.track_test_score('dense')", "last_rev": 34164, "last_value": 0.9274012651798128, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.track_test_score('sparse')", "last_rev": 34164, "last_value": 0.10386656749682988, "last_err": 0.0021272271046887115, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.LinearRegressionBenchmark.track_train_score('dense')", "last_rev": 34164, "last_value": 0.927602494829764, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LinearRegressionBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.LinearRegressionBenchmark.track_train_score('sparse')", "last_rev": 34164, "last_value": 0.9999999999962889, "last_err": 0.0, "prev_value": 0.9999999999963929, "change_rev": [34162, 34164]}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'lbfgs', 1)", "last_rev": 34164, "last_value": 105371648.0, "last_err": 180224.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'lbfgs', 4)", "last_rev": 34164, "last_value": 98799616.0, "last_err": 152917.33333333334, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 1)", "last_rev": 34164, "last_value": 83329024.0, "last_err": 92501.33333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 4)", "last_rev": 34164, "last_value": 84408320.0, "last_err": 102058.66666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'lbfgs', 1)", "last_rev": 34164, "last_value": 381868032.0, "last_err": 413354.6666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'lbfgs', 4)", "last_rev": 34164, "last_value": 124942336.0, "last_err": 135168.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 1)", "last_rev": 34164, "last_value": 103892992.0, "last_err": 144725.33333333334, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 4)", "last_rev": 34164, "last_value": 104552448.0, "last_err": 95914.66666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'lbfgs', 1)", "last_rev": 34164, "last_value": 99049472.0, "last_err": 190464.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'lbfgs', 4)", "last_rev": 34164, "last_value": 98908160.0, "last_err": 209237.33333333334, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 1)", "last_rev": 34164, "last_value": 86063104.0, "last_err": 116394.66666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 4)", "last_rev": 34164, "last_value": 85989376.0, "last_err": 130389.33333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 1)", "last_rev": 34164, "last_value": 100317184.0, "last_err": 139605.33333333334, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 4)", "last_rev": 34164, "last_value": 100319232.0, "last_err": 161450.66666666666, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 1)", "last_rev": 34164, "last_value": 88086528.0, "last_err": 195584.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 4)", "last_rev": 34164, "last_value": 88064000.0, "last_err": 174762.66666666666, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('dense', 'lbfgs', 1)", "last_rev": 34164, "last_value": 0.02202568299981067, "last_err": 0.0008200201171617363, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('dense', 'lbfgs', 4)", "last_rev": 34164, "last_value": 0.18967650499962474, "last_err": 0.00047398073659667725, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('dense', 'saga', 1)", "last_rev": 34164, "last_value": 4.506277077499817, "last_err": 0.3997902447710316, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('dense', 'saga', 4)", "last_rev": 34164, "last_value": 4.935574182499749, "last_err": 0.7838584640531069, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'lbfgs', 1)", "last_rev": 34164, "last_value": 1.092709123000077, "last_err": 0.0485434634616529, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'lbfgs', 4)", "last_rev": 34164, "last_value": 2.9758953789996667, "last_err": 0.04125525332407694, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 1)", "last_rev": 34164, "last_value": 3.8842646690000038, "last_err": 0.151644279113789, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_fit", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 4)", "last_rev": 34164, "last_value": 3.531279477499538, "last_err": 0.0, "prev_value": 4.155317227000523, "change_rev": [34162, 34164]}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('dense', 'lbfgs', 1)", "last_rev": 34164, "last_value": 0.0032651716666502275, "last_err": 8.786161126564988e-05, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('dense', 'lbfgs', 4)", "last_rev": 34164, "last_value": 0.0030973771250728532, "last_err": 6.527172245815068e-05, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('dense', 'saga', 1)", "last_rev": 34164, "last_value": 0.0019054025000665813, "last_err": 2.9861866711848982e-05, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('dense', 'saga', 4)", "last_rev": 34164, "last_value": 0.0019412794999880134, "last_err": 3.87723967748247e-05, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'lbfgs', 1)", "last_rev": 34164, "last_value": 0.007595465750000585, "last_err": 0.00038303500159099334, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'lbfgs', 4)", "last_rev": 34164, "last_value": 0.007776695250186094, "last_err": 0.0008486857025770874, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 1)", "last_rev": 34164, "last_value": 0.005045570333398549, "last_err": 0.001282878369026876, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.time_predict", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 4)", "last_rev": 34164, "last_value": 0.006150585500108718, "last_err": 0.0005327114401413527, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('dense', 'lbfgs', 1)", "last_rev": 34164, "last_value": 0.1742131209282406, "last_err": 0.001034485949150267, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('dense', 'lbfgs', 4)", "last_rev": 34164, "last_value": 0.1742131209282406, "last_err": 0.001034485949150267, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('dense', 'saga', 1)", "last_rev": 34164, "last_value": 0.7786264414834814, "last_err": 0.004630997856243084, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('dense', 'saga', 4)", "last_rev": 34164, "last_value": 0.7786264414834814, "last_err": 0.004630997856243084, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('sparse', 'lbfgs', 1)", "last_rev": 34164, "last_value": 0.06538461538461539, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('sparse', 'lbfgs', 4)", "last_rev": 34164, "last_value": 0.06538461538461539, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('sparse', 'saga', 1)", "last_rev": 34164, "last_value": 0.5765140080078162, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_test_score", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_test_score('sparse', 'saga', 4)", "last_rev": 34164, "last_value": 0.5765140080078162, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('dense', 'lbfgs', 1)", "last_rev": 34164, "last_value": 0.17923985043539467, "last_err": 0.0007130200194349276, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('dense', 'lbfgs', 4)", "last_rev": 34164, "last_value": 0.17923985043539467, "last_err": 0.0007130200194349276, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 2, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('dense', 'saga', 1)", "last_rev": 34164, "last_value": 0.7994965262514242, "last_err": 0.0018804165968764146, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 3, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('dense', 'saga', 4)", "last_rev": 34164, "last_value": 0.7994965262514242, "last_err": 0.0018804165968764146, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 4, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('sparse', 'lbfgs', 1)", "last_rev": 34164, "last_value": 0.0681998556998557, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 5, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('sparse', 'lbfgs', 4)", "last_rev": 34164, "last_value": 0.0681998556998557, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 6, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('sparse', 'saga', 1)", "last_rev": 34164, "last_value": 0.6908414295256007, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.LogisticRegressionBenchmark.track_train_score", "idx": 7, "pretty_name": "linear_model.LogisticRegressionBenchmark.track_train_score('sparse', 'saga', 4)", "last_rev": 34164, "last_value": 0.6908414295256007, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'auto')", "last_rev": 34164, "last_value": 463517696.0, "last_err": 95573.33333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'svd')", "last_rev": 34164, "last_value": 825024512.0, "last_err": 171008.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'cholesky')", "last_rev": 34164, "last_value": 463577088.0, "last_err": 102400.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'lsqr')", "last_rev": 34164, "last_value": 472332288.0, "last_err": 92160.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'sparse_cg')", "last_rev": 34164, "last_value": 466825216.0, "last_err": 95573.33333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'sag')", "last_rev": 34164, "last_value": 472268800.0, "last_err": 71338.66666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('dense', 'saga')", "last_rev": 34164, "last_value": 472266752.0, "last_err": 74752.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'auto')", "last_rev": 34164, "last_value": 192501760.0, "last_err": 95232.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'cholesky')", "last_rev": 34164, "last_value": 1270810624.0, "last_err": 107520.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'lsqr')", "last_rev": 34164, "last_value": 193783808.0, "last_err": 69290.66666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'sparse_cg')", "last_rev": 34164, "last_value": 192485376.0, "last_err": 119808.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'sag')", "last_rev": 34164, "last_value": 157968384.0, "last_err": 83968.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_fit", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.peakmem_fit('sparse', 'saga')", "last_rev": 34164, "last_value": 157954048.0, "last_err": 85333.33333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'auto')", "last_rev": 34164, "last_value": 282955776.0, "last_err": 219477.33333333334, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'svd')", "last_rev": 34164, "last_value": 282937344.0, "last_err": 236885.33333333334, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'cholesky')", "last_rev": 34164, "last_value": 282972160.0, "last_err": 232106.66666666666, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'lsqr')", "last_rev": 34164, "last_value": 282959872.0, "last_err": 209578.66666666666, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'sparse_cg')", "last_rev": 34164, "last_value": 282923008.0, "last_err": 202069.33333333334, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'sag')", "last_rev": 34164, "last_value": 282941440.0, "last_err": 222890.66666666666, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('dense', 'saga')", "last_rev": 34164, "last_value": 282949632.0, "last_err": 215381.33333333334, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'auto')", "last_rev": 34164, "last_value": 118237184.0, "last_err": 507562.6666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'cholesky')", "last_rev": 34164, "last_value": 118249472.0, "last_err": 521898.6666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'lsqr')", "last_rev": 34164, "last_value": 118251520.0, "last_err": 468309.3333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'sparse_cg')", "last_rev": 34164, "last_value": 118245376.0, "last_err": 460117.3333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'sag')", "last_rev": 34164, "last_value": 118224896.0, "last_err": 471722.6666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.peakmem_predict", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.peakmem_predict('sparse', 'saga')", "last_rev": 34164, "last_value": 118159360.0, "last_err": 426666.6666666667, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'auto')", "last_rev": 34164, "last_value": 0.21205807649994313, "last_err": 0.0022928633445258545, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'svd')", "last_rev": 34164, "last_value": 1.7053674980002143, "last_err": 0.02135414993866767, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'cholesky')", "last_rev": 34164, "last_value": 0.2106260020004811, "last_err": 0.0025400014760187813, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'lsqr')", "last_rev": 34164, "last_value": 0.2188873679997414, "last_err": 0.005440104181242835, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'sparse_cg')", "last_rev": 34164, "last_value": 0.25529594299950986, "last_err": 0.006042761633879881, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'sag')", "last_rev": 34164, "last_value": 29.879230076000567, "last_err": 1.701688726453695, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.time_fit('dense', 'saga')", "last_rev": 34164, "last_value": 13.622493873999701, "last_err": 0.7874759322029049, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'auto')", "last_rev": 34164, "last_value": 0.15510172350013818, "last_err": 0.005061923165314105, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'cholesky')", "last_rev": 34164, "last_value": 5.45057535199976, "last_err": 0.0775679064368565, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'lsqr')", "last_rev": 34164, "last_value": 0.13863539800013314, "last_err": 0.00457356041645475, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'sparse_cg')", "last_rev": 34164, "last_value": 0.1570656554999914, "last_err": 0.004460153467248669, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'sag')", "last_rev": 34164, "last_value": 2.55703478399937, "last_err": 0.16038640022455525, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_fit", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.time_fit('sparse', 'saga')", "last_rev": 34164, "last_value": 2.0900424494998333, "last_err": 0.1319181136098845, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'auto')", "last_rev": 34164, "last_value": 0.02546200550023059, "last_err": 0.0008543710759397927, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'svd')", "last_rev": 34164, "last_value": 0.024992409000333282, "last_err": 0.0009342340876127689, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'cholesky')", "last_rev": 34164, "last_value": 0.024916054000186705, "last_err": 0.0008550948572859288, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'lsqr')", "last_rev": 34164, "last_value": 0.025335637000353017, "last_err": 0.0005734498153175732, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'sparse_cg')", "last_rev": 34164, "last_value": 0.025324631999410485, "last_err": 0.0008752109605119064, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'sag')", "last_rev": 34164, "last_value": 0.025330991500140954, "last_err": 0.0007531267179226273, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.time_predict('dense', 'saga')", "last_rev": 34164, "last_value": 0.025355314499847736, "last_err": 0.0006306305124135199, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'auto')", "last_rev": 34164, "last_value": 0.0077384387500387675, "last_err": 0.00035768465730814724, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'cholesky')", "last_rev": 34164, "last_value": 0.006992351000008057, "last_err": 0.0003550096760238223, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'lsqr')", "last_rev": 34164, "last_value": 0.007052425499978199, "last_err": 0.00041438726358550927, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'sparse_cg')", "last_rev": 34164, "last_value": 0.00765860525007156, "last_err": 0.00034885777917412626, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'sag')", "last_rev": 34164, "last_value": 0.007035577750002631, "last_err": 0.0002601732458146553, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.time_predict", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.time_predict('sparse', 'saga')", "last_rev": 34164, "last_value": 0.007035252000150649, "last_err": 0.00033461499224147134, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'auto')", "last_rev": 34164, "last_value": 0.943399575027382, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'svd')", "last_rev": 34164, "last_value": 0.9433995638980545, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'cholesky')", "last_rev": 34164, "last_value": 0.943399575027382, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'lsqr')", "last_rev": 34164, "last_value": 0.9433995757192792, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'sparse_cg')", "last_rev": 34164, "last_value": 0.9433995989989826, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'sag')", "last_rev": 34164, "last_value": 0.94339933719428, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('dense', 'saga')", "last_rev": 34164, "last_value": 0.9433995886080997, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'auto')", "last_rev": 34164, "last_value": 0.9564435181860627, "last_err": 0.00040142949384551946, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'cholesky')", "last_rev": 34164, "last_value": 0.9564434313528715, "last_err": 0.0004014191980032759, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'lsqr')", "last_rev": 34164, "last_value": 0.9564435170497178, "last_err": 0.0004014287626728323, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'sparse_cg')", "last_rev": 34164, "last_value": 0.9564435181860627, "last_err": 0.00040142949384551946, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'sag')", "last_rev": 34164, "last_value": 0.9564444076481264, "last_err": 0.0004000767377506653, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_test_score", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.track_test_score('sparse', 'saga')", "last_rev": 34164, "last_value": 0.9564444706544359, "last_err": 0.00039997824330534337, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'auto')", "last_rev": 34164, "last_value": 0.9444001571921127, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'svd')", "last_rev": 34164, "last_value": 0.9444001571502235, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 2, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'cholesky')", "last_rev": 34164, "last_value": 0.9444001571921127, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 3, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'lsqr')", "last_rev": 34164, "last_value": 0.9444001572131616, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 4, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'sparse_cg')", "last_rev": 34164, "last_value": 0.9444001571192623, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 5, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'sag')", "last_rev": 34164, "last_value": 0.9444001419121766, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 6, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('dense', 'saga')", "last_rev": 34164, "last_value": 0.9444001543688754, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 7, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'auto')", "last_rev": 34164, "last_value": 0.9658124382623725, "last_err": 0.00011228354416142894, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 8, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'svd')", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 9, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'cholesky')", "last_rev": 34164, "last_value": 0.965812441287635, "last_err": 0.00011228346054052245, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 10, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'lsqr')", "last_rev": 34164, "last_value": 0.9658124384220195, "last_err": 0.00011228362568416195, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 11, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'sparse_cg')", "last_rev": 34164, "last_value": 0.9658124382623725, "last_err": 0.00011228354416142894, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 12, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'sag')", "last_rev": 34164, "last_value": 0.9658088779683878, "last_err": 0.00011228279978401738, "prev_value": null, "change_rev": null}, {"name": "linear_model.RidgeBenchmark.track_train_score", "idx": 13, "pretty_name": "linear_model.RidgeBenchmark.track_train_score('sparse', 'saga')", "last_rev": 34164, "last_value": 0.9658088445711772, "last_err": 0.00011228273461718248, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.peakmem_fit", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.peakmem_fit('dense')", "last_rev": 34164, "last_value": 159440896.0, "last_err": 382293.3333333333, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.peakmem_fit", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.peakmem_fit('sparse')", "last_rev": 34164, "last_value": 87832576.0, "last_err": 332800.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.peakmem_predict", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.peakmem_predict('dense')", "last_rev": 34164, "last_value": 158318592.0, "last_err": 194218.66666666666, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.peakmem_predict", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.peakmem_predict('sparse')", "last_rev": 34164, "last_value": 86251520.0, "last_err": 185685.33333333334, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.time_fit", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.time_fit('dense')", "last_rev": 34164, "last_value": 5.715017427999555, "last_err": 0.1279707055497262, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.time_fit", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.time_fit('sparse')", "last_rev": 34164, "last_value": 4.270766128000105, "last_err": 0.2005202030541823, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.time_predict", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.time_predict('dense')", "last_rev": 34164, "last_value": 0.010537201500028459, "last_err": 0.0002294742793305546, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.time_predict", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.time_predict('sparse')", "last_rev": 34164, "last_value": 0.002442390800024441, "last_err": 6.173041732028812e-05, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.track_test_score", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.track_test_score('dense')", "last_rev": 34164, "last_value": 0.9636293915848902, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.track_test_score", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.track_test_score('sparse')", "last_rev": 34164, "last_value": 0.9618757511103795, "last_err": 0.0005177986729509957, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.track_train_score", "idx": 0, "pretty_name": "linear_model.SGDRegressorBenchmark.track_train_score('dense')", "last_rev": 34164, "last_value": 0.9641785427097553, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "linear_model.SGDRegressorBenchmark.track_train_score", "idx": 1, "pretty_name": "linear_model.SGDRegressorBenchmark.track_train_score('sparse')", "last_rev": 34164, "last_value": 0.9619301798247843, "last_err": 0.00013291820598253698, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.peakmem_fit", "idx": 0, "pretty_name": "manifold.TSNEBenchmark.peakmem_fit('exact')", "last_rev": 34164, "last_value": 88983552.0, "last_err": 164522.66666666666, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.peakmem_fit", "idx": 1, "pretty_name": "manifold.TSNEBenchmark.peakmem_fit('barnes_hut')", "last_rev": 34164, "last_value": 96555008.0, "last_err": 310613.3333333333, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.time_fit", "idx": 0, "pretty_name": "manifold.TSNEBenchmark.time_fit('exact')", "last_rev": 34164, "last_value": 6.458831746500437, "last_err": 0.1913504159703946, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.time_fit", "idx": 1, "pretty_name": "manifold.TSNEBenchmark.time_fit('barnes_hut')", "last_rev": 34164, "last_value": 3.1843909919998623, "last_err": 0.1146437229261454, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.track_test_score", "idx": 0, "pretty_name": "manifold.TSNEBenchmark.track_test_score('exact')", "last_rev": 34164, "last_value": 0.3218818006120378, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.track_test_score", "idx": 1, "pretty_name": "manifold.TSNEBenchmark.track_test_score('barnes_hut')", "last_rev": 34164, "last_value": 0.7243016362190247, "last_err": 0.0, "prev_value": 0.7243015766143799, "change_rev": [34160, 34162]}, {"name": "manifold.TSNEBenchmark.track_train_score", "idx": 0, "pretty_name": "manifold.TSNEBenchmark.track_train_score('exact')", "last_rev": 34164, "last_value": 0.3218818006120378, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "manifold.TSNEBenchmark.track_train_score", "idx": 1, "pretty_name": "manifold.TSNEBenchmark.track_train_score('barnes_hut')", "last_rev": 34164, "last_value": 0.7243016362190247, "last_err": 0.0, "prev_value": 0.7243015766143799, "change_rev": [34160, 34162]}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 0, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'cosine', 1)", "last_rev": 34164, "last_value": 668430336.0, "last_err": 244053.33333333334, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 1, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'cosine', 4)", "last_rev": 34164, "last_value": 785244160.0, "last_err": 1181013.3333333333, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 2, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'euclidean', 1)", "last_rev": 34164, "last_value": 751343616.0, "last_err": 225621.33333333334, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 3, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'euclidean', 4)", "last_rev": 34164, "last_value": 1057196032.0, "last_err": 38456661.333333336, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 4, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'manhattan', 1)", "last_rev": 34164, "last_value": 254277632.0, "last_err": 164522.66666666666, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 5, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'manhattan', 4)", "last_rev": 34164, "last_value": 338262016.0, "last_err": 7591936.0, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 6, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'correlation', 1)", "last_rev": 34164, "last_value": 247386112.0, "last_err": 160768.0, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 7, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'correlation', 4)", "last_rev": 34164, "last_value": 482109440.0, "last_err": 3514026.6666666665, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 8, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'cosine', 1)", "last_rev": 34164, "last_value": 1419982848.0, "last_err": 224938.66666666666, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 9, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'cosine', 4)", "last_rev": 34164, "last_value": 1402482688.0, "last_err": 57157632.0, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 10, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'euclidean', 1)", "last_rev": 34164, "last_value": 569698304.0, "last_err": 228693.33333333334, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 11, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'euclidean', 4)", "last_rev": 34164, "last_value": 921309184.0, "last_err": 37956949.333333336, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 12, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'manhattan', 1)", "last_rev": 34164, "last_value": 186800128.0, "last_err": 188757.33333333334, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 13, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'manhattan', 4)", "last_rev": 34164, "last_value": 229574656.0, "last_err": 7937365.333333333, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 14, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'correlation', 1)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "idx": 15, "pretty_name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'correlation', 4)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 0, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'cosine', 1)", "last_rev": 34164, "last_value": 1.096224562000316, "last_err": 0.013848320238094557, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 1, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'cosine', 4)", "last_rev": 34164, "last_value": 1.2531879289999779, "last_err": 0.011881389561645533, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 2, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'euclidean', 1)", "last_rev": 34164, "last_value": 1.73283707399969, "last_err": 0.04827778815817855, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 3, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'euclidean', 4)", "last_rev": 34164, "last_value": 3.059747658499873, "last_err": 0.03170048712954244, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 4, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'manhattan', 1)", "last_rev": 34164, "last_value": 6.330721553499643, "last_err": 0.16632272657839198, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 5, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'manhattan', 4)", "last_rev": 34164, "last_value": 2.623034252999787, "last_err": 0.01672370250106348, "prev_value": 2.1561904800000775, "change_rev": [34113, 34115]}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 6, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'correlation', 1)", "last_rev": 34164, "last_value": 3.6838959485003215, "last_err": 0.2437076232746348, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 7, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'correlation', 4)", "last_rev": 34164, "last_value": 2.5598424650002016, "last_err": 0.05636444950669229, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 8, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 1)", "last_rev": 34164, "last_value": 4.127793399999973, "last_err": 0.10641338333911211, "prev_value": 3.6725709250004, "change_rev": [null, 34141]}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 9, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 4)", "last_rev": 34164, "last_value": 2.5860535255001196, "last_err": 0.0495812139397974, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 10, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 1)", "last_rev": 34164, "last_value": 2.59981175700068, "last_err": 0.10526275253350682, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 11, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 4)", "last_rev": 34164, "last_value": 2.07176092949976, "last_err": 0.0753056884932266, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 12, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'manhattan', 1)", "last_rev": 34164, "last_value": 1.2255320979998032, "last_err": 0.0062985932883327855, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 13, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'manhattan', 4)", "last_rev": 34164, "last_value": 1.313895422999849, "last_err": 0.011138623992474115, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 14, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'correlation', 1)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "idx": 15, "pretty_name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'correlation', 4)", "last_rev": null, "last_value": null, "last_err": null, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.peakmem_crossval", "idx": 0, "pretty_name": "model_selection.CrossValidationBenchmark.peakmem_crossval(1)", "last_rev": 34164, "last_value": 217931776.0, "last_err": 155989.33333333334, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.peakmem_crossval", "idx": 1, "pretty_name": "model_selection.CrossValidationBenchmark.peakmem_crossval(4)", "last_rev": 34164, "last_value": 118222848.0, "last_err": 167936.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.time_crossval", "idx": 0, "pretty_name": "model_selection.CrossValidationBenchmark.time_crossval(1)", "last_rev": 34164, "last_value": 63.216229812000165, "last_err": 6.734300470876044, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.time_crossval", "idx": 1, "pretty_name": "model_selection.CrossValidationBenchmark.time_crossval(4)", "last_rev": 34164, "last_value": 17.233828422999977, "last_err": 0.2480533510585, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.track_crossval", "idx": 0, "pretty_name": "model_selection.CrossValidationBenchmark.track_crossval(1)", "last_rev": 34164, "last_value": 0.9001555555555555, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.CrossValidationBenchmark.track_crossval", "idx": 1, "pretty_name": "model_selection.CrossValidationBenchmark.track_crossval(4)", "last_rev": 34164, "last_value": 0.9001555555555555, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.peakmem_fit", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.peakmem_fit(1)", "last_rev": 34164, "last_value": 95358976.0, "last_err": 189440.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.peakmem_fit", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.peakmem_fit(4)", "last_rev": 34164, "last_value": 92923904.0, "last_err": 186368.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.peakmem_predict", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.peakmem_predict(1)", "last_rev": 34164, "last_value": 87726080.0, "last_err": 193194.66666666666, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.peakmem_predict", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.peakmem_predict(4)", "last_rev": 34164, "last_value": 87703552.0, "last_err": 188416.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.time_fit", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.time_fit(1)", "last_rev": 34164, "last_value": 346.82019891100026, "last_err": 11.250117718916899, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.time_fit", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.time_fit(4)", "last_rev": 34164, "last_value": 102.37117459599904, "last_err": 0.8166434061798715, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.time_predict", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.time_predict(1)", "last_rev": 34164, "last_value": 0.07095141599984345, "last_err": 0.0006213705216826425, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.time_predict", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.time_predict(4)", "last_rev": 34164, "last_value": 0.0708904334996987, "last_err": 0.0004479292335393344, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.track_test_score", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.track_test_score(1)", "last_rev": 34164, "last_value": 0.8678060899936387, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.track_test_score", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.track_test_score(4)", "last_rev": 34164, "last_value": 0.8678060899936387, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.track_train_score", "idx": 0, "pretty_name": "model_selection.GridSearchBenchmark.track_train_score(1)", "last_rev": 34164, "last_value": 0.9966662088870577, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "model_selection.GridSearchBenchmark.track_train_score", "idx": 1, "pretty_name": "model_selection.GridSearchBenchmark.track_train_score(4)", "last_rev": 34164, "last_value": 0.9966662088870577, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 1)", "last_rev": 34164, "last_value": 77301760.0, "last_err": 163498.66666666666, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 4)", "last_rev": 34164, "last_value": 77287424.0, "last_err": 139605.33333333334, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 1)", "last_rev": 34164, "last_value": 80787456.0, "last_err": 166229.33333333334, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 4)", "last_rev": 34164, "last_value": 80787456.0, "last_err": 148138.66666666666, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 1)", "last_rev": 34164, "last_value": 79986688.0, "last_err": 247808.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 4)", "last_rev": 34164, "last_value": 79937536.0, "last_err": 259754.66666666666, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 1)", "last_rev": 34164, "last_value": 88346624.0, "last_err": 147456.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 4)", "last_rev": 34164, "last_value": 88350720.0, "last_err": 148138.66666666666, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 1)", "last_rev": 34164, "last_value": 79929344.0, "last_err": 250538.66666666666, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 4)", "last_rev": 34164, "last_value": 79966208.0, "last_err": 263168.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 1)", "last_rev": 34164, "last_value": 88123392.0, "last_err": 143701.33333333334, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 4)", "last_rev": 34164, "last_value": 88125440.0, "last_err": 142677.33333333334, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'low', 1)", "last_rev": 34164, "last_value": 87998464.0, "last_err": 240298.66666666666, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'low', 4)", "last_rev": 34164, "last_value": 88119296.0, "last_err": 259754.66666666666, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'high', 1)", "last_rev": 34164, "last_value": 92936192.0, "last_err": 237568.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'high', 4)", "last_rev": 34164, "last_value": 92989440.0, "last_err": 273749.3333333333, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 1)", "last_rev": 34164, "last_value": 81467392.0, "last_err": 157696.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 4)", "last_rev": 34164, "last_value": 83912704.0, "last_err": 247466.66666666666, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 1)", "last_rev": 34164, "last_value": 91095040.0, "last_err": 178176.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 4)", "last_rev": 34164, "last_value": 90810368.0, "last_err": 266581.3333333333, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 1)", "last_rev": 34164, "last_value": 81283072.0, "last_err": 160426.66666666666, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 4)", "last_rev": 34164, "last_value": 83720192.0, "last_err": 216064.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 1)", "last_rev": 34164, "last_value": 90793984.0, "last_err": 215040.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 4)", "last_rev": 34164, "last_value": 90793984.0, "last_err": 192512.0, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'low', 1)", "last_rev": 34164, "last_value": 0.0015012015714351687, "last_err": 8.98033334741672e-06, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'low', 4)", "last_rev": 34164, "last_value": 0.0010583937999399495, "last_err": 0.00014795749551420496, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'high', 1)", "last_rev": 34164, "last_value": 0.0012312470000526649, "last_err": 0.00011029365735930548, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'high', 4)", "last_rev": 34164, "last_value": 0.0012185581666320409, "last_err": 8.951171269566788e-05, "prev_value": 0.0017440364999856683, "change_rev": [34115, 34120]}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('kd_tree', 'low', 1)", "last_rev": 34164, "last_value": 0.012145177500315185, "last_err": 0.0011501302866924604, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('kd_tree', 'low', 4)", "last_rev": 34164, "last_value": 0.012227947000610584, "last_err": 0.001554091804228857, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('kd_tree', 'high', 1)", "last_rev": 34164, "last_value": 0.05226113849948888, "last_err": 0.004225611874945194, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('kd_tree', 'high', 4)", "last_rev": 34164, "last_value": 0.0587864509989231, "last_err": 0.0040086083063579515, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'low', 1)", "last_rev": 34164, "last_value": 0.01242584400006308, "last_err": 0.0011038971522483742, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'low', 4)", "last_rev": 34164, "last_value": 0.012252143501427781, "last_err": 0.000649994238728123, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'high', 1)", "last_rev": 34164, "last_value": 0.03397333799966873, "last_err": 0.0017747943352581484, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'high', 4)", "last_rev": 34164, "last_value": 0.03343777349891752, "last_err": 0.0012622375293309563, "prev_value": 0.03714136300004611, "change_rev": [34141, 34155]}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('brute', 'low', 1)", "last_rev": 34164, "last_value": 0.09055840200016974, "last_err": 0.0012338539041801871, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('brute', 'low', 4)", "last_rev": 34164, "last_value": 0.08853839700077515, "last_err": 0.00021936842845892, "prev_value": 0.09047138949972577, "change_rev": [34158, 34160]}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('brute', 'high', 1)", "last_rev": 34164, "last_value": 0.12965472050018434, "last_err": 0.001623003699167106, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('brute', 'high', 4)", "last_rev": 34164, "last_value": 0.12964923449999333, "last_err": 0.0011937193233493004, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'low', 1)", "last_rev": 34164, "last_value": 1.2949519209996652, "last_err": 0.06194658391785258, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'low', 4)", "last_rev": 34164, "last_value": 2.8610398105001877, "last_err": 0.07284087671802852, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 1)", "last_rev": 34164, "last_value": 8.30450277500131, "last_err": 0.6028797754807168, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 4)", "last_rev": 34164, "last_value": 8.0518865490003, "last_err": 0.2447455958719734, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'low', 1)", "last_rev": 34164, "last_value": 2.352441653000824, "last_err": 0.19945199787744503, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'low', 4)", "last_rev": 34164, "last_value": 5.639076026998737, "last_err": 0.2551952597024711, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 1)", "last_rev": 34164, "last_value": 7.526197360000879, "last_err": 0.3379271524315696, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 4)", "last_rev": 34164, "last_value": 10.755202964001, "last_err": 0.25696306180549877, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('brute', 'low', 1)", "last_rev": 34164, "last_value": 0.43663046023833163, "last_err": 0.006457891153945096, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('brute', 'low', 4)", "last_rev": 34164, "last_value": 0.43663046023833163, "last_err": 0.006457891153945096, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('brute', 'high', 1)", "last_rev": 34164, "last_value": 0.6619084120446495, "last_err": 0.005847807885038886, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('brute', 'high', 4)", "last_rev": 34164, "last_value": 0.6619084120446495, "last_err": 0.005847807885038886, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('kd_tree', 'low', 1)", "last_rev": 34164, "last_value": 0.43663046023833163, "last_err": 0.006457891153945096, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('kd_tree', 'low', 4)", "last_rev": 34164, "last_value": 0.43663046023833163, "last_err": 0.006457891153945096, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('kd_tree', 'high', 1)", "last_rev": 34164, "last_value": 0.6619084120446495, "last_err": 0.005847807885038886, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('kd_tree', 'high', 4)", "last_rev": 34164, "last_value": 0.6619084120446495, "last_err": 0.005847807885038886, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('ball_tree', 'low', 1)", "last_rev": 34164, "last_value": 0.43663046023833163, "last_err": 0.006457891153945096, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('ball_tree', 'low', 4)", "last_rev": 34164, "last_value": 0.43663046023833163, "last_err": 0.006457891153945096, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('ball_tree', 'high', 1)", "last_rev": 34164, "last_value": 0.6619084120446495, "last_err": 0.005847807885038886, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_test_score('ball_tree', 'high', 4)", "last_rev": 34164, "last_value": 0.6619084120446495, "last_err": 0.005847807885038886, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 0, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('brute', 'low', 1)", "last_rev": 34164, "last_value": 0.6377015661565248, "last_err": 0.00289029415373269, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 1, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('brute', 'low', 4)", "last_rev": 34164, "last_value": 0.6377015661565248, "last_err": 0.00289029415373269, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 2, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('brute', 'high', 1)", "last_rev": 34164, "last_value": 0.7926996956105352, "last_err": 0.0017147557409434577, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 3, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('brute', 'high', 4)", "last_rev": 34164, "last_value": 0.7926996956105352, "last_err": 0.0017147557409434577, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 4, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('kd_tree', 'low', 1)", "last_rev": 34164, "last_value": 0.6377015661565248, "last_err": 0.00289029415373269, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 5, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('kd_tree', 'low', 4)", "last_rev": 34164, "last_value": 0.6377015661565248, "last_err": 0.00289029415373269, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 6, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('kd_tree', 'high', 1)", "last_rev": 34164, "last_value": 0.7926996956105352, "last_err": 0.0017147557409434577, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 7, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('kd_tree', 'high', 4)", "last_rev": 34164, "last_value": 0.7926996956105352, "last_err": 0.0017147557409434577, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 8, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('ball_tree', 'low', 1)", "last_rev": 34164, "last_value": 0.6377015661565248, "last_err": 0.00289029415373269, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 9, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('ball_tree', 'low', 4)", "last_rev": 34164, "last_value": 0.6377015661565248, "last_err": 0.00289029415373269, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 10, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('ball_tree', 'high', 1)", "last_rev": 34164, "last_value": 0.7926996956105352, "last_err": 0.0017147557409434577, "prev_value": null, "change_rev": null}, {"name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "idx": 11, "pretty_name": "neighbors.KNeighborsClassifierBenchmark.track_train_score('ball_tree', 'high', 4)", "last_rev": 34164, "last_value": 0.7926996956105352, "last_err": 0.0017147557409434577, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_fit", "idx": 0, "pretty_name": "svm.SVCBenchmark.peakmem_fit('linear')", "last_rev": 34164, "last_value": 276867072.0, "last_err": 134144.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_fit", "idx": 1, "pretty_name": "svm.SVCBenchmark.peakmem_fit('poly')", "last_rev": 34164, "last_value": 276869120.0, "last_err": 136192.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_fit", "idx": 2, "pretty_name": "svm.SVCBenchmark.peakmem_fit('rbf')", "last_rev": 34164, "last_value": 276869120.0, "last_err": 134144.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_fit", "idx": 3, "pretty_name": "svm.SVCBenchmark.peakmem_fit('sigmoid')", "last_rev": 34164, "last_value": 276867072.0, "last_err": 135850.66666666666, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_predict", "idx": 0, "pretty_name": "svm.SVCBenchmark.peakmem_predict('linear')", "last_rev": 34164, "last_value": 204083200.0, "last_err": 249856.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_predict", "idx": 1, "pretty_name": "svm.SVCBenchmark.peakmem_predict('poly')", "last_rev": 34164, "last_value": 204083200.0, "last_err": 233130.66666666666, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_predict", "idx": 2, "pretty_name": "svm.SVCBenchmark.peakmem_predict('rbf')", "last_rev": 34164, "last_value": 204083200.0, "last_err": 276821.3333333333, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.peakmem_predict", "idx": 3, "pretty_name": "svm.SVCBenchmark.peakmem_predict('sigmoid')", "last_rev": 34164, "last_value": 204083200.0, "last_err": 238933.33333333334, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_fit", "idx": 0, "pretty_name": "svm.SVCBenchmark.time_fit('linear')", "last_rev": 34164, "last_value": 1.7031090059990674, "last_err": 0.021752203381804548, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_fit", "idx": 1, "pretty_name": "svm.SVCBenchmark.time_fit('poly')", "last_rev": 34164, "last_value": 1.6984569729993382, "last_err": 0.021704049024226835, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_fit", "idx": 2, "pretty_name": "svm.SVCBenchmark.time_fit('rbf')", "last_rev": 34164, "last_value": 1.718418913998903, "last_err": 0.028367634686072115, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_fit", "idx": 3, "pretty_name": "svm.SVCBenchmark.time_fit('sigmoid')", "last_rev": 34164, "last_value": 1.7369195179999224, "last_err": 0.027127652519575215, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_predict", "idx": 0, "pretty_name": "svm.SVCBenchmark.time_predict('linear')", "last_rev": 34164, "last_value": 0.6688483699999779, "last_err": 0.04055270445524685, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_predict", "idx": 1, "pretty_name": "svm.SVCBenchmark.time_predict('poly')", "last_rev": 34164, "last_value": 0.6330361529999209, "last_err": 0.016046005503657722, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_predict", "idx": 2, "pretty_name": "svm.SVCBenchmark.time_predict('rbf')", "last_rev": 34164, "last_value": 1.7370904769995832, "last_err": 0.06257696074961731, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.time_predict", "idx": 3, "pretty_name": "svm.SVCBenchmark.time_predict('sigmoid')", "last_rev": 34164, "last_value": 0.6335948619998817, "last_err": 0.021338267084338173, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_test_score", "idx": 0, "pretty_name": "svm.SVCBenchmark.track_test_score('linear')", "last_rev": 34164, "last_value": 0.5899537620849096, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_test_score", "idx": 1, "pretty_name": "svm.SVCBenchmark.track_test_score('poly')", "last_rev": 34164, "last_value": 0.5, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_test_score", "idx": 2, "pretty_name": "svm.SVCBenchmark.track_test_score('rbf')", "last_rev": 34164, "last_value": 0.564312736443884, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_test_score", "idx": 3, "pretty_name": "svm.SVCBenchmark.track_test_score('sigmoid')", "last_rev": 34164, "last_value": 0.5710382513661202, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_train_score", "idx": 0, "pretty_name": "svm.SVCBenchmark.track_train_score('linear')", "last_rev": 34164, "last_value": 0.7373393801965231, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_train_score", "idx": 1, "pretty_name": "svm.SVCBenchmark.track_train_score('poly')", "last_rev": 34164, "last_value": 0.6089324618736384, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_train_score", "idx": 2, "pretty_name": "svm.SVCBenchmark.track_train_score('rbf')", "last_rev": 34164, "last_value": 0.7382063936685785, "last_err": 0.0, "prev_value": null, "change_rev": null}, {"name": "svm.SVCBenchmark.track_train_score", "idx": 3, "pretty_name": "svm.SVCBenchmark.track_train_score('sigmoid')", "last_rev": 34164, "last_value": 0.741296518607443, "last_err": 0.0, "prev_value": null, "change_rev": null}] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.peakmem_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.peakmem_fit.json index 8eca885365..df8b1ff463 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.peakmem_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[34113, [277004288.0, 277012480.0, 276996096.0, 277000192.0]], [34115, [277037056.0, 277012480.0, 277016576.0, 277037056.0]], [34120, [276529152.0, 276529152.0, 276553728.0, 276537344.0]], [34126, [276869120.0, 276893696.0, 276885504.0, 276877312.0]], [34139, [276897792.0, 276889600.0, 276910080.0, 276897792.0]], [34140, [276742144.0, 276721664.0, 276725760.0, 276729856.0]], [34141, [277114880.0, 277090304.0, 277110784.0, 277098496.0]], [34155, [276865024.0, 276836352.0, 276844544.0, 276848640.0]], [34158, [276652032.0, 276656128.0, 276639744.0, 276652032.0]], [34160, [276852736.0, 276848640.0, 276852736.0, 276856832.0]], [34162, [277061632.0, 277041152.0, 277037056.0, 277045248.0]]] \ No newline at end of file +[[34113, [277004288.0, 277012480.0, 276996096.0, 277000192.0]], [34115, [277037056.0, 277012480.0, 277016576.0, 277037056.0]], [34120, [276529152.0, 276529152.0, 276553728.0, 276537344.0]], [34126, [276869120.0, 276893696.0, 276885504.0, 276877312.0]], [34139, [276897792.0, 276889600.0, 276910080.0, 276897792.0]], [34140, [276742144.0, 276721664.0, 276725760.0, 276729856.0]], [34141, [277114880.0, 277090304.0, 277110784.0, 277098496.0]], [34155, [276865024.0, 276836352.0, 276844544.0, 276848640.0]], [34158, [276652032.0, 276656128.0, 276639744.0, 276652032.0]], [34160, [276852736.0, 276848640.0, 276852736.0, 276856832.0]], [34162, [277061632.0, 277041152.0, 277037056.0, 277045248.0]], [34164, [276733952.0, 276713472.0, 276729856.0, 276701184.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.peakmem_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.peakmem_predict.json index fd0b6d7c03..3390e20ba1 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.peakmem_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[34113, [204685312.0, 204550144.0, 204619776.0, 204619776.0]], [34115, [204054528.0, 204054528.0, 204054528.0, 204054528.0]], [34120, [203673600.0, 203673600.0, 203673600.0, 203673600.0]], [34126, [204017664.0, 204017664.0, 204017664.0, 204017664.0]], [34139, [204066816.0, 204066816.0, 204066816.0, 204066816.0]], [34140, [203698176.0, 203698176.0, 203698176.0, 203698176.0]], [34141, [204312576.0, 204312576.0, 204312576.0, 204312576.0]], [34155, [204828672.0, 204763136.0, 205090816.0, 204763136.0]], [34158, [203718656.0, 203718656.0, 203718656.0, 203718656.0]], [34160, [204128256.0, 204128256.0, 204128256.0, 204128256.0]], [34162, [204099584.0, 204099584.0, 204099584.0, 204099584.0]]] \ No newline at end of file +[[34113, [204685312.0, 204550144.0, 204619776.0, 204619776.0]], [34115, [204054528.0, 204054528.0, 204054528.0, 204054528.0]], [34120, [203673600.0, 203673600.0, 203673600.0, 203673600.0]], [34126, [204017664.0, 204017664.0, 204017664.0, 204017664.0]], [34139, [204066816.0, 204066816.0, 204066816.0, 204066816.0]], [34140, [203698176.0, 203698176.0, 203698176.0, 203698176.0]], [34141, [204312576.0, 204312576.0, 204312576.0, 204312576.0]], [34155, [204828672.0, 204763136.0, 205090816.0, 204763136.0]], [34158, [203718656.0, 203718656.0, 203718656.0, 203718656.0]], [34160, [204128256.0, 204128256.0, 204128256.0, 204128256.0]], [34162, [204099584.0, 204099584.0, 204099584.0, 204099584.0]], [34164, [204173312.0, 204173312.0, 204300288.0, 204173312.0]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.time_fit.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.time_fit.json index 9ccf82610c..05656d1f7f 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.time_fit.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.time_fit.json @@ -1 +1 @@ -[[34113, [1.7159162250009103, 1.7181672899987461, 1.729571676998603, 1.7231541290002497]], [34115, [1.6511249044997385, 1.63720706300046, 1.6507038909994662, 1.6456046390003394]], [34120, [1.7477568390004308, 1.7504446679995453, 1.7694953350001015, 1.764811818000453]], [34126, [1.7031090059990674, 1.703582424999695, 1.7113804680011526, 1.7369195179999224]], [34139, [1.762590504498803, 1.7663567979998334, 1.7754958750001606, 1.7730413379995298]], [34140, [1.687991132001116, 1.690465038000184, 1.7161002379998536, 1.711112167000465]], [34141, [1.759738467999341, 1.7586618160003127, 1.7727079545002198, 1.7673126639992915]], [34155, [1.7002796870001475, 1.697683712000071, 1.718418913998903, 1.7111846859988873]], [34158, [1.7004485329998715, 1.694955201999619, 1.74637978499959, 1.7411723479999637]], [34160, [1.7244063830003142, 1.7259752449990629, 1.7408610179991229, 1.7341962150003383]], [34162, [1.7080650619991502, 1.6954726740004844, 1.7083421039988025, 1.7021789539994643]]] \ No newline at end of file +[[34113, [1.7159162250009103, 1.7181672899987461, 1.729571676998603, 1.7231541290002497]], [34115, [1.6511249044997385, 1.63720706300046, 1.6507038909994662, 1.6456046390003394]], [34120, [1.7477568390004308, 1.7504446679995453, 1.7694953350001015, 1.764811818000453]], [34126, [1.7031090059990674, 1.703582424999695, 1.7113804680011526, 1.7369195179999224]], [34139, [1.762590504498803, 1.7663567979998334, 1.7754958750001606, 1.7730413379995298]], [34140, [1.687991132001116, 1.690465038000184, 1.7161002379998536, 1.711112167000465]], [34141, [1.759738467999341, 1.7586618160003127, 1.7727079545002198, 1.7673126639992915]], [34155, [1.7002796870001475, 1.697683712000071, 1.718418913998903, 1.7111846859988873]], [34158, [1.7004485329998715, 1.694955201999619, 1.74637978499959, 1.7411723479999637]], [34160, [1.7244063830003142, 1.7259752449990629, 1.7408610179991229, 1.7341962150003383]], [34162, [1.7080650619991502, 1.6954726740004844, 1.7083421039988025, 1.7021789539994643]], [34164, [1.6976721889986948, 1.6984569729993382, 1.7061528739995993, 1.7062680270009878]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.time_predict.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.time_predict.json index a73fec314e..9169dea6c6 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.time_predict.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.time_predict.json @@ -1 +1 @@ -[[34113, [0.6355710629995883, 0.6255674369986082, 1.7370904769995832, 0.6335948619998817]], [34115, [0.6014356374998897, 0.6934220550001555, 1.703316574999917, 0.6919075155001337]], [34120, [0.6358298700006344, 0.6353652180005156, 1.7324767180016352, 0.6571160020002935]], [34126, [0.7225243649991171, 0.6339325370008737, 1.7482364710012916, 0.6316703809989122]], [34139, [0.6688483699999779, 0.6199965385003452, 1.7252930520007794, 0.6335936135001248]], [34140, [0.6323693000013009, 0.6804686884997864, 1.9621515549988544, 0.687464081998769]], [34141, [0.7708751179998217, 0.664737740999044, 1.8959190765008316, 0.6765664325002945]], [34155, [0.7018033859985735, 0.6224875539992354, 1.7436108820002119, 0.6321013344995663]], [34158, [0.7844946440000058, 0.6331054920010502, 1.8172078300003704, 0.6366907699994044]], [34160, [0.6811619124991921, 0.6330361529999209, 1.7096972480012482, 0.6833790599994245]], [34162, [0.6766418050001448, 0.6838339860014457, 1.9313398289996258, 0.6201049754999985]]] \ No newline at end of file +[[34113, [0.6355710629995883, 0.6255674369986082, 1.7370904769995832, 0.6335948619998817]], [34115, [0.6014356374998897, 0.6934220550001555, 1.703316574999917, 0.6919075155001337]], [34120, [0.6358298700006344, 0.6353652180005156, 1.7324767180016352, 0.6571160020002935]], [34126, [0.7225243649991171, 0.6339325370008737, 1.7482364710012916, 0.6316703809989122]], [34139, [0.6688483699999779, 0.6199965385003452, 1.7252930520007794, 0.6335936135001248]], [34140, [0.6323693000013009, 0.6804686884997864, 1.9621515549988544, 0.687464081998769]], [34141, [0.7708751179998217, 0.664737740999044, 1.8959190765008316, 0.6765664325002945]], [34155, [0.7018033859985735, 0.6224875539992354, 1.7436108820002119, 0.6321013344995663]], [34158, [0.7844946440000058, 0.6331054920010502, 1.8172078300003704, 0.6366907699994044]], [34160, [0.6811619124991921, 0.6330361529999209, 1.7096972480012482, 0.6833790599994245]], [34162, [0.6766418050001448, 0.6838339860014457, 1.9313398289996258, 0.6201049754999985]], [34164, [0.745480483999927, 0.6766425910009275, 1.7875915775002795, 0.6954930960000638]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.track_test_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.track_test_score.json index 3955c2415e..7bd810670b 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.track_test_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.track_test_score.json @@ -1 +1 @@ -[[34113, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34115, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34120, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34126, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34139, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34140, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34141, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34155, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34158, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34160, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34162, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]]] \ No newline at end of file +[[34113, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34115, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34120, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34126, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34139, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34140, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34141, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34155, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34158, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34160, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34162, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]], [34164, [0.5899537620849096, 0.5, 0.564312736443884, 0.5710382513661202]]] \ No newline at end of file diff --git a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.track_train_score.json b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.track_train_score.json index 278a797b3b..9458308920 100644 --- a/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.track_train_score.json +++ b/graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/svm.SVCBenchmark.track_train_score.json @@ -1 +1 @@ -[[34113, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34115, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34120, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34126, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34139, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34140, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34141, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34155, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34158, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34160, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34162, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]]] \ No newline at end of file +[[34113, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34115, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34120, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34126, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34139, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34140, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34141, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34155, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34158, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34160, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34162, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]], [34164, [0.7373393801965231, 0.6089324618736384, 0.7382063936685785, 0.741296518607443]]] \ No newline at end of file diff --git a/graphs/summary/cluster.KMeansBenchmark.peakmem_fit.json b/graphs/summary/cluster.KMeansBenchmark.peakmem_fit.json index bd0bfcdcb5..79129d27c1 100644 --- a/graphs/summary/cluster.KMeansBenchmark.peakmem_fit.json +++ b/graphs/summary/cluster.KMeansBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 171320862.48599574], [29225, 168517937.7509785], [29239, 168548311.93698648], [29253, 168611403.4328343], [29267, 168341829.3316878], [29281, 168937332.24893337], [29295, 168586668.76434064], [29309, 168620242.54526174], [29323, 168525219.20747873], [29337, 169021212.95511785], [29351, 167649570.066179], [29365, 167405103.02160892], [29379, 167943887.96699423], [29393, 167879190.244753], [29407, 167819401.35104108], [29421, 167788991.60051432], [29435, 168193956.81285134], [29449, 168324302.64585865], [29463, 168250598.41172776], [29477, 168273694.58862713], [29547, 168225997.06656504], [29561, 168351032.71951506], [29575, 167854418.64437887], [29603, 168860357.52339536], [29617, 169064148.9704686], [29631, 169462169.7579461], [29645, 169162597.40237692], [29659, 169142926.92755592], [29673, 169083256.42879304], [29743, 169002427.5154932], [29757, 169122752.53840852], [29771, 168960945.09937432], [29785, 169265545.31387326], [29799, 169255811.35454196], [29813, 169442487.73846304], [29827, 169633172.76086313], [29841, 169381767.42008257], [29855, 169355375.15755546], [29869, 169339009.20787555], [30009, 169510964.15519562], [30023, 169479355.4347341], [30037, 169203999.05215105], [30051, 168902172.155606], [30065, 169077554.87412754], [30079, 169170802.65197754], [30093, 169158894.2373508], [30107, 169113088.2788542], [30121, 169220614.52187946], [30135, 169125272.7087363], [30149, 163034019.37305143], [30163, 156387076.75321805], [30177, 156568756.3426791], [30191, 156592673.54291365], [30205, 156684591.28979552], [30219, 156603976.6233911], [30233, 156318563.37618592], [30247, 156560288.42022485], [30261, 156265714.95821118], [30513, 156818481.20676816], [30527, 156436696.5934415], [30541, 156434536.99509248], [30555, 156320071.77787662], [30569, 156307581.93859988], [30583, 156537325.93048346], [30597, 156230532.0032506], [30625, 156549967.2725116], [30639, 156424776.70879138], [30653, 156376148.12568727], [30667, 156470360.55742854], [30681, 156440116.0525659], [30695, 156611081.9266589], [30709, 156508930.06771815], [30723, 156378404.58165106], [30737, 156510272.2642433], [30751, 156562852.38945508], [30765, 156895878.24677143], [30779, 156284486.8204971], [30793, 156457300.19963345], [30807, 156511332.6150819], [30821, 156690781.2277915], [30835, 156659189.20158583], [30849, 156665085.0501844], [30863, 156618738.0688886], [30877, 156674852.67983666], [30891, 156759013.6847077], [30905, 156739895.59770155], [30919, 156530756.36775598], [30933, 156388716.13095656], [30947, 156397668.92846647], [30961, 156510388.1698568], [30975, 156654161.2024747], [30989, 156549112.86503342], [31003, 156885454.22279584], [31017, 156765143.89751476], [31031, 156525773.48454362], [31045, 156683324.86984658], [32109, 167100599.93803328], [32123, 167132259.2450369], [32137, 167129565.4641703], [32151, 167145092.55482674], [32165, 167096238.41920152], [32179, 167132655.2002804], [32193, 167169133.90713426], [32207, 168473967.77449787], [32221, 169805938.49868205], [32235, 170094417.7183203], [32249, 169680439.58842316], [32263, 169819426.56121993], [32277, 169847427.18418828], [32305, 171301731.65472952], [32319, 174028841.5039296], [32333, 174232686.5858131], [32347, 173999301.57859433], [32361, 174150931.94390002], [32375, 174036162.89603782], [32389, 173897450.8513261], [32403, 174248844.9711644], [32417, 174184147.11380276], [32431, 174237809.5119052], [32445, 174389110.61748493], [32571, 173649001.78569555], [32585, 173534373.3713207], [32599, 173518427.95333633], [32613, 173451175.14970472], [32627, 173722474.65180868], [32641, 173276983.96301812], [32655, 173362822.2419476], [32851, 174446675.54965433], [32865, 174535869.2384755], [32879, 174549020.79077342], [32893, 174548119.47300157], [32907, 174698400.04124007], [32921, 174412672.8835597], [32991, 174500463.8742839], [33005, 174418280.6017181], [33019, 174111103.70853233], [33033, 174399803.53084126], [33047, 174671000.22795278], [33061, 175377245.99330574], [33075, 175708408.29457816], [33089, 190453871.8096993], [33103, 205442873.55770758], [33117, 205564945.64332125], [33131, 205384272.19619387], [33145, 205626201.09062526], [33159, 205683573.09564328], [33187, 176195746.1725592], [33201, 175930507.41665056], [33215, 176667234.95247144], [33229, 178667314.2312767], [33243, 178618129.32377493], [33271, 181075657.38037944], [33299, 181438741.49354297], [33313, 181500442.21572632], [33327, 181897107.44600415], [33341, 181879493.2165296], [33355, 182376760.8926475], [33369, 182747248.23652378], [33383, 183142010.99316213], [33397, 183495790.21342003], [33411, 183366613.69691816], [33425, 183461155.35934955], [33439, 184601485.18844932], [33453, 179505618.0884594], [33467, 179469693.556632], [33523, 179483504.3091854], [33537, 179486732.05279112], [33551, 178752160.69616073], [33649, 178027615.6308032], [33705, 177656673.1170775], [33719, 177689427.48132342], [33733, 177731857.77919492], [33747, 177746819.9897352], [33761, 177426047.01528394], [33775, 177814931.26050884], [33803, 177706801.80871353], [33817, 177436674.8063734], [33831, 177529760.66938248], [33845, 177220553.6004111], [34041, 177194932.90787357], [34055, 177526235.07429194], [34069, 177434383.61087117], [34083, 177338421.0791543], [34125, 177378307.52838862], [34139, 177741790.06428835], [34153, 177409760.00408235], [34167, 177340509.28398347]] \ No newline at end of file +[[28511, 171320862.48599574], [29225, 168517937.7509785], [29239, 168548311.93698648], [29253, 168611403.4328343], [29267, 168341829.3316878], [29281, 168937332.24893337], [29295, 168586668.76434064], [29309, 168620242.54526174], [29323, 168525219.20747873], [29337, 169021212.95511785], [29351, 167649570.066179], [29365, 167405103.02160892], [29379, 167943887.96699423], [29393, 167879190.244753], [29407, 167819401.35104108], [29421, 167788991.60051432], [29435, 168193956.81285134], [29449, 168324302.64585865], [29463, 168250598.41172776], [29477, 168273694.58862713], [29547, 168225997.06656504], [29561, 168351032.71951506], [29575, 167854418.64437887], [29603, 168860357.52339536], [29617, 169064148.9704686], [29631, 169462169.7579461], [29645, 169162597.40237692], [29659, 169142926.92755592], [29673, 169083256.42879304], [29743, 169002427.5154932], [29757, 169122752.53840852], [29771, 168960945.09937432], [29785, 169265545.31387326], [29799, 169255811.35454196], [29813, 169442487.73846304], [29827, 169633172.76086313], [29841, 169381767.42008257], [29855, 169355375.15755546], [29869, 169339009.20787555], [30009, 169510964.15519562], [30023, 169479355.4347341], [30037, 169203999.05215105], [30051, 168902172.155606], [30065, 169077554.87412754], [30079, 169170802.65197754], [30093, 169158894.2373508], [30107, 169113088.2788542], [30121, 169220614.52187946], [30135, 169125272.7087363], [30149, 163034019.37305143], [30163, 156387076.75321805], [30177, 156568756.3426791], [30191, 156592673.54291365], [30205, 156684591.28979552], [30219, 156603976.6233911], [30233, 156318563.37618592], [30247, 156560288.42022485], [30261, 156265714.95821118], [30513, 156818481.20676816], [30527, 156436696.5934415], [30541, 156434536.99509248], [30555, 156320071.77787662], [30569, 156307581.93859988], [30583, 156537325.93048346], [30597, 156230532.0032506], [30625, 156549967.2725116], [30639, 156424776.70879138], [30653, 156376148.12568727], [30667, 156470360.55742854], [30681, 156440116.0525659], [30695, 156611081.9266589], [30709, 156508930.06771815], [30723, 156378404.58165106], [30737, 156510272.2642433], [30751, 156562852.38945508], [30765, 156895878.24677143], [30779, 156284486.8204971], [30793, 156457300.19963345], [30807, 156511332.6150819], [30821, 156690781.2277915], [30835, 156659189.20158583], [30849, 156665085.0501844], [30863, 156618738.0688886], [30877, 156674852.67983666], [30891, 156759013.6847077], [30905, 156739895.59770155], [30919, 156530756.36775598], [30933, 156388716.13095656], [30947, 156397668.92846647], [30961, 156510388.1698568], [30975, 156654161.2024747], [30989, 156549112.86503342], [31003, 156885454.22279584], [31017, 156765143.89751476], [31031, 156525773.48454362], [31045, 156683324.86984658], [32109, 167100599.93803328], [32123, 167132259.2450369], [32137, 167129565.4641703], [32151, 167145092.55482674], [32165, 167096238.41920152], [32179, 167132655.2002804], [32193, 167169133.90713426], [32207, 168473967.77449787], [32221, 169805938.49868205], [32235, 170094417.7183203], [32249, 169680439.58842316], [32263, 169819426.56121993], [32277, 169847427.18418828], [32305, 171301731.65472952], [32319, 174028841.5039296], [32333, 174232686.5858131], [32347, 173999301.57859433], [32361, 174150931.94390002], [32375, 174036162.89603782], [32389, 173897450.8513261], [32403, 174248844.9711644], [32417, 174184147.11380276], [32431, 174237809.5119052], [32445, 174389110.61748493], [32571, 173649001.78569555], [32585, 173534373.3713207], [32599, 173518427.95333633], [32613, 173451175.14970472], [32627, 173722474.65180868], [32641, 173276983.96301812], [32655, 173362822.2419476], [32851, 174446675.54965433], [32865, 174535869.2384755], [32879, 174549020.79077342], [32893, 174548119.47300157], [32907, 174698400.04124007], [32921, 174412672.8835597], [32991, 174500463.8742839], [33005, 174418280.6017181], [33019, 174111103.70853233], [33033, 174399803.53084126], [33047, 174671000.22795278], [33061, 175377245.99330574], [33075, 175708408.29457816], [33089, 190453871.8096993], [33103, 205442873.55770758], [33117, 205564945.64332125], [33131, 205384272.19619387], [33145, 205626201.09062526], [33159, 205683573.09564328], [33187, 176195746.1725592], [33201, 175930507.41665056], [33215, 176667234.95247144], [33229, 178667314.2312767], [33243, 178618129.32377493], [33271, 181075657.38037944], [33299, 181438741.49354297], [33313, 181500442.21572632], [33327, 181897107.44600415], [33341, 181879493.2165296], [33355, 182376760.8926475], [33369, 182747248.23652378], [33383, 183142010.99316213], [33397, 183495790.21342003], [33411, 183366613.69691816], [33425, 183461155.35934955], [33439, 184601485.18844932], [33453, 179505618.0884594], [33467, 179469693.556632], [33523, 179483504.3091854], [33537, 179486732.05279112], [33551, 178752160.69616073], [33649, 178027615.6308032], [33705, 177656673.1170775], [33719, 177689427.48132342], [33733, 177731857.77919492], [33747, 177746819.9897352], [33761, 177426047.01528394], [33775, 177814931.26050884], [33803, 177706801.80871353], [33817, 177436674.8063734], [33831, 177529760.66938248], [33845, 177220553.6004111], [34041, 177194932.90787357], [34055, 177526235.07429194], [34069, 177434383.61087117], [34083, 177338421.0791543], [34125, 177378307.52838862], [34139, 177741790.06428835], [34153, 177409760.00408235], [34167, 177335123.28939977]] \ No newline at end of file diff --git a/graphs/summary/cluster.KMeansBenchmark.peakmem_predict.json b/graphs/summary/cluster.KMeansBenchmark.peakmem_predict.json index 420e12ad77..2656eab08b 100644 --- a/graphs/summary/cluster.KMeansBenchmark.peakmem_predict.json +++ b/graphs/summary/cluster.KMeansBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28511, 92663190.86982237], [29225, 91930062.16389516], [29239, 92084341.11180504], [29253, 92376638.37702157], [29267, 92139890.04667655], [29281, 92345617.45415217], [29295, 92338187.13178135], [29309, 92347172.35836399], [29323, 92209745.40673056], [29337, 92470335.4079359], [29351, 91554320.37338363], [29365, 91608420.19203289], [29379, 91827506.23867452], [29393, 91719157.90655863], [29407, 91556607.47445697], [29421, 91694931.287523], [29435, 91846792.74015887], [29449, 92151085.35082966], [29463, 91863460.33719374], [29477, 91853453.1658382], [29547, 92837721.52355658], [29561, 92235212.13570003], [29575, 91814728.39433663], [29603, 92576479.44601971], [29617, 92579140.60338578], [29631, 92942877.74826175], [29645, 92823817.87235424], [29659, 92736976.37158923], [29673, 92596981.00738747], [29743, 92659772.59814122], [29757, 92769506.99515069], [29771, 92678833.43927519], [29785, 92843483.97294644], [29799, 92698592.63765815], [29813, 92759593.41331217], [29827, 92910972.89980534], [29841, 92876873.9406083], [29855, 92840555.50822735], [29869, 92947214.14655106], [30009, 92736081.01359527], [30023, 92719653.03867465], [30037, 92668255.23371196], [30051, 92725449.56104963], [30065, 92471908.83348578], [30079, 92731472.71617988], [30093, 92890161.41229695], [30107, 92876956.19648159], [30121, 92782445.20595466], [30135, 92691884.51938225], [30149, 92970753.14701176], [30163, 93152896.25529449], [30177, 93325234.58593641], [30191, 93285797.83294317], [30205, 93251804.13880484], [30219, 93403802.07811853], [30233, 93034723.07441469], [30247, 93267951.00375533], [30261, 92924763.07508925], [30513, 93358512.69870341], [30527, 93217514.28802373], [30541, 93073642.8990684], [30555, 92987556.9161223], [30569, 93048801.42464642], [30583, 93424742.10708955], [30597, 92876401.55456667], [30625, 93187629.72882354], [30639, 93259162.99009755], [30653, 93014470.53906488], [30667, 93095702.89759126], [30681, 93097284.85320663], [30695, 93122886.6929894], [30709, 93014741.81536227], [30723, 93127909.68289559], [30737, 93180820.25496453], [30751, 93340633.63294506], [30765, 93504876.91110723], [30779, 92767561.77888906], [30793, 93112278.20015864], [30807, 93239731.0175259], [30821, 93343320.8451173], [30835, 93451780.4505296], [30849, 93170659.30922578], [30863, 93281668.99626651], [30877, 93274320.57824324], [30891, 93366713.24424282], [30905, 93224610.86753607], [30919, 93326905.06547344], [30933, 93153497.51172268], [30947, 93074929.5680491], [30961, 93381769.16039331], [30975, 93443152.48462653], [30989, 93203346.42829007], [31003, 93510627.81915224], [31017, 93349674.41633368], [31031, 93178060.61594903], [31045, 93277162.04123136], [32109, 103649042.73110804], [32123, 103748176.8015397], [32137, 103734200.48229076], [32151, 103665548.61796631], [32165, 103725250.9955228], [32179, 103492842.12244585], [32193, 103802675.40470068], [32207, 105195347.10463661], [32221, 106658718.53029597], [32235, 106820598.4651762], [32249, 106293126.28636025], [32263, 106370640.66704261], [32277, 106316102.14801367], [32305, 107380248.488195], [32319, 109550130.20558475], [32333, 109630182.0675053], [32347, 109705341.03106402], [32361, 109653083.2789524], [32375, 109656313.67418301], [32389, 109638375.06344326], [32403, 109496468.45260674], [32417, 109566088.65518348], [32431, 109606135.17362772], [32445, 109722990.50960237], [32571, 109746482.64349644], [32585, 109771329.83906658], [32599, 109826964.7309656], [32613, 109843574.58017243], [32627, 110085791.02013989], [32641, 109723281.66958773], [32655, 109738537.00777388], [32851, 110639603.36203289], [32865, 110671560.59442875], [32879, 110802381.63117774], [32893, 110900782.93316375], [32907, 110769594.63556635], [32921, 110686274.19589025], [32991, 110789350.40508424], [33005, 110625213.56493047], [33019, 110394285.0167117], [33033, 110679401.55694532], [33047, 110932456.94599165], [33061, 110966913.77044386], [33075, 110789494.79680577], [33089, 125379887.9829568], [33103, 140178578.69880518], [33117, 140462157.1192087], [33131, 140265032.99138868], [33145, 140355350.667221], [33159, 140339646.34763855], [33187, 111143513.52218878], [33201, 111070043.84390709], [33215, 109218443.76998776], [33229, 103935585.26641373], [33243, 103922398.39129464], [33271, 97198196.88028125], [33299, 97522556.1811317], [33313, 97637034.97428428], [33327, 97860469.6204396], [33341, 97858301.73668016], [33355, 97781211.83154303], [33369, 98369602.56094335], [33383, 98611043.26282072], [33397, 98809981.58651774], [33411, 98825578.54310279], [33425, 98934003.72693896], [33439, 100025846.87777081], [33453, 95277610.58984801], [33467, 95113963.6579196], [33523, 95405953.83889647], [33537, 95321166.45786934], [33551, 94641946.66506964], [33649, 94134993.82574077], [33705, 93778286.2139325], [33719, 93779938.64619392], [33733, 93938757.34635064], [33747, 93663903.90896332], [33761, 93695610.49009907], [33775, 93567729.05595389], [33803, 93750044.07695827], [33817, 93585577.41683471], [33831, 93692296.885858], [33845, 93341317.44478604], [34041, 93510417.8246004], [34055, 93655540.34036076], [34069, 93677055.56649207], [34083, 93445291.61134183], [34125, 93521754.5448597], [34139, 94105671.03579547], [34153, 93597958.87648617], [34167, 93427316.66808334]] \ No newline at end of file +[[28511, 92663190.86982237], [29225, 91930062.16389516], [29239, 92084341.11180504], [29253, 92376638.37702157], [29267, 92139890.04667655], [29281, 92345617.45415217], [29295, 92338187.13178135], [29309, 92347172.35836399], [29323, 92209745.40673056], [29337, 92470335.4079359], [29351, 91554320.37338363], [29365, 91608420.19203289], [29379, 91827506.23867452], [29393, 91719157.90655863], [29407, 91556607.47445697], [29421, 91694931.287523], [29435, 91846792.74015887], [29449, 92151085.35082966], [29463, 91863460.33719374], [29477, 91853453.1658382], [29547, 92837721.52355658], [29561, 92235212.13570003], [29575, 91814728.39433663], [29603, 92576479.44601971], [29617, 92579140.60338578], [29631, 92942877.74826175], [29645, 92823817.87235424], [29659, 92736976.37158923], [29673, 92596981.00738747], [29743, 92659772.59814122], [29757, 92769506.99515069], [29771, 92678833.43927519], [29785, 92843483.97294644], [29799, 92698592.63765815], [29813, 92759593.41331217], [29827, 92910972.89980534], [29841, 92876873.9406083], [29855, 92840555.50822735], [29869, 92947214.14655106], [30009, 92736081.01359527], [30023, 92719653.03867465], [30037, 92668255.23371196], [30051, 92725449.56104963], [30065, 92471908.83348578], [30079, 92731472.71617988], [30093, 92890161.41229695], [30107, 92876956.19648159], [30121, 92782445.20595466], [30135, 92691884.51938225], [30149, 92970753.14701176], [30163, 93152896.25529449], [30177, 93325234.58593641], [30191, 93285797.83294317], [30205, 93251804.13880484], [30219, 93403802.07811853], [30233, 93034723.07441469], [30247, 93267951.00375533], [30261, 92924763.07508925], [30513, 93358512.69870341], [30527, 93217514.28802373], [30541, 93073642.8990684], [30555, 92987556.9161223], [30569, 93048801.42464642], [30583, 93424742.10708955], [30597, 92876401.55456667], [30625, 93187629.72882354], [30639, 93259162.99009755], [30653, 93014470.53906488], [30667, 93095702.89759126], [30681, 93097284.85320663], [30695, 93122886.6929894], [30709, 93014741.81536227], [30723, 93127909.68289559], [30737, 93180820.25496453], [30751, 93340633.63294506], [30765, 93504876.91110723], [30779, 92767561.77888906], [30793, 93112278.20015864], [30807, 93239731.0175259], [30821, 93343320.8451173], [30835, 93451780.4505296], [30849, 93170659.30922578], [30863, 93281668.99626651], [30877, 93274320.57824324], [30891, 93366713.24424282], [30905, 93224610.86753607], [30919, 93326905.06547344], [30933, 93153497.51172268], [30947, 93074929.5680491], [30961, 93381769.16039331], [30975, 93443152.48462653], [30989, 93203346.42829007], [31003, 93510627.81915224], [31017, 93349674.41633368], [31031, 93178060.61594903], [31045, 93277162.04123136], [32109, 103649042.73110804], [32123, 103748176.8015397], [32137, 103734200.48229076], [32151, 103665548.61796631], [32165, 103725250.9955228], [32179, 103492842.12244585], [32193, 103802675.40470068], [32207, 105195347.10463661], [32221, 106658718.53029597], [32235, 106820598.4651762], [32249, 106293126.28636025], [32263, 106370640.66704261], [32277, 106316102.14801367], [32305, 107380248.488195], [32319, 109550130.20558475], [32333, 109630182.0675053], [32347, 109705341.03106402], [32361, 109653083.2789524], [32375, 109656313.67418301], [32389, 109638375.06344326], [32403, 109496468.45260674], [32417, 109566088.65518348], [32431, 109606135.17362772], [32445, 109722990.50960237], [32571, 109746482.64349644], [32585, 109771329.83906658], [32599, 109826964.7309656], [32613, 109843574.58017243], [32627, 110085791.02013989], [32641, 109723281.66958773], [32655, 109738537.00777388], [32851, 110639603.36203289], [32865, 110671560.59442875], [32879, 110802381.63117774], [32893, 110900782.93316375], [32907, 110769594.63556635], [32921, 110686274.19589025], [32991, 110789350.40508424], [33005, 110625213.56493047], [33019, 110394285.0167117], [33033, 110679401.55694532], [33047, 110932456.94599165], [33061, 110966913.77044386], [33075, 110789494.79680577], [33089, 125379887.9829568], [33103, 140178578.69880518], [33117, 140462157.1192087], [33131, 140265032.99138868], [33145, 140355350.667221], [33159, 140339646.34763855], [33187, 111143513.52218878], [33201, 111070043.84390709], [33215, 109218443.76998776], [33229, 103935585.26641373], [33243, 103922398.39129464], [33271, 97198196.88028125], [33299, 97522556.1811317], [33313, 97637034.97428428], [33327, 97860469.6204396], [33341, 97858301.73668016], [33355, 97781211.83154303], [33369, 98369602.56094335], [33383, 98611043.26282072], [33397, 98809981.58651774], [33411, 98825578.54310279], [33425, 98934003.72693896], [33439, 100025846.87777081], [33453, 95277610.58984801], [33467, 95113963.6579196], [33523, 95405953.83889647], [33537, 95321166.45786934], [33551, 94641946.66506964], [33649, 94134993.82574077], [33705, 93778286.2139325], [33719, 93779938.64619392], [33733, 93938757.34635064], [33747, 93663903.90896332], [33761, 93695610.49009907], [33775, 93567729.05595389], [33803, 93750044.07695827], [33817, 93585577.41683471], [33831, 93692296.885858], [33845, 93341317.44478604], [34041, 93510417.8246004], [34055, 93655540.34036076], [34069, 93677055.56649207], [34083, 93445291.61134183], [34125, 93521754.5448597], [34139, 94105671.03579547], [34153, 93597958.87648617], [34167, 93455462.92633803]] \ No newline at end of file diff --git a/graphs/summary/cluster.KMeansBenchmark.peakmem_transform.json b/graphs/summary/cluster.KMeansBenchmark.peakmem_transform.json index 6148133f56..36fbcc1936 100644 --- a/graphs/summary/cluster.KMeansBenchmark.peakmem_transform.json +++ b/graphs/summary/cluster.KMeansBenchmark.peakmem_transform.json @@ -1 +1 @@ -[[28511, 120802330.24010743], [29225, 118082903.74277888], [29239, 118070363.8789473], [29253, 118075279.86292957], [29267, 118022675.45829052], [29281, 118257778.17484754], [29295, 118125941.00033565], [29309, 118035354.10604145], [29323, 118127266.68744084], [29337, 118585658.69194491], [29351, 117744372.49743575], [29365, 117691869.66194478], [29379, 118036200.53661384], [29393, 117915101.72318871], [29407, 117826344.62347144], [29421, 117789215.57594956], [29435, 118308202.61710443], [29449, 118353644.25662], [29463, 118236075.95838885], [29477, 118210995.74672404], [29547, 118424791.90053731], [29561, 118355625.61789405], [29575, 117813954.34624289], [29603, 118993199.12461421], [29617, 119059325.67750198], [29631, 119285306.86573192], [29645, 119215739.7921845], [29659, 119106055.12987131], [29673, 119131039.98097138], [29743, 119048335.57068431], [29757, 119169325.38387698], [29771, 119083578.64875492], [29785, 119207646.3526927], [29799, 119203556.575631], [29813, 119307726.34851475], [29827, 119400089.22388676], [29841, 119304251.66028532], [29855, 119287705.55192639], [29869, 119362585.2822308], [30009, 119366673.97455126], [30023, 119333031.69246957], [30037, 119184040.76763482], [30051, 119074664.77877972], [30065, 119260959.82249133], [30079, 119275534.03450201], [30093, 119153466.52929628], [30107, 119095440.07319383], [30121, 119291796.11063524], [30135, 119179992.87773387], [30149, 119603779.61420026], [30163, 119605931.44412534], [30177, 119738782.8664673], [30191, 119808673.3283711], [30205, 119748047.026924], [30219, 119761907.7932667], [30233, 119609025.71950495], [30247, 119754698.89292294], [30261, 119518715.20699653], [30513, 119897837.54730229], [30527, 119664580.38137917], [30541, 119612574.28137289], [30555, 119494542.5127772], [30569, 119405134.15722898], [30583, 119711124.7998581], [30597, 119481079.7775423], [30625, 119613093.73821689], [30639, 119652555.20771125], [30653, 119558671.10358252], [30667, 119563795.41354407], [30681, 119670829.96775977], [30695, 119725869.13649468], [30709, 119627961.830084], [30723, 119581034.8917982], [30737, 119642853.54306039], [30751, 119710871.15842113], [30765, 120058891.69835664], [30779, 119602189.66163461], [30793, 119614868.33582415], [30807, 119552315.24009162], [30821, 119781996.8017978], [30835, 120033498.58209655], [30849, 119766765.81837001], [30863, 119683071.67230517], [30877, 119793293.73284134], [30891, 119858367.46801451], [30905, 119899390.70197564], [30919, 119597257.7814524], [30933, 119610568.64763565], [30947, 119639855.88744308], [30961, 119695382.62447752], [30975, 119692627.97829385], [30989, 119793209.45350264], [31003, 119886618.69894955], [31017, 119885991.94684584], [31031, 119522315.71506312], [31045, 119792843.34645358], [32109, 131539712.36154266], [32123, 131697883.09901872], [32137, 131663678.29564989], [32151, 131631357.83783212], [32165, 131650668.35583709], [32179, 131512286.32407019], [32193, 131675977.23686875], [32207, 132835474.85257581], [32221, 134109630.12086952], [32235, 134356867.02474004], [32249, 134084119.24327068], [32263, 134142650.19571333], [32277, 134190599.70172572], [32305, 136034942.489979], [32319, 139565694.4747124], [32333, 139617497.1000485], [32347, 139525141.1544353], [32361, 139663472.96774638], [32375, 139752183.22406363], [32389, 139522084.02031356], [32403, 139710758.4397933], [32417, 139645533.58989802], [32431, 139845143.0721948], [32445, 139968350.3761459], [32571, 137481704.48719046], [32585, 137535454.6912412], [32599, 137454099.89625984], [32613, 137410912.36700368], [32627, 137574822.65771085], [32641, 137240003.95196006], [32655, 137395277.10226864], [32851, 138342462.69257697], [32865, 138487976.99334526], [32879, 138449824.43319264], [32893, 138617313.73252463], [32907, 140312107.2827195], [32921, 140241938.55148122], [32991, 140361726.7899456], [33005, 140322236.904557], [33019, 140024311.64641353], [33033, 140268520.08394235], [33047, 140426198.90286842], [33061, 140706341.1844009], [33075, 140629981.15197995], [33089, 155205236.83303696], [33103, 170007272.95952484], [33117, 170218165.44463086], [33131, 170020435.90046725], [33145, 170215924.37910944], [33159, 170241990.56397045], [33187, 140795897.23676893], [33201, 140813008.9730573], [33215, 138935104.87955603], [33229, 133839473.81482247], [33243, 133740454.54755159], [33271, 126934662.16220972], [33299, 127160572.7350715], [33313, 127016498.77750044], [33327, 127183037.29346305], [33341, 127297252.0421462], [33355, 127548431.5094666], [33369, 127999892.79141228], [33383, 128199227.7387387], [33397, 128506375.66841185], [33411, 128382685.92839307], [33425, 128451516.09012455], [33439, 129394210.38226357], [33453, 124546390.3418493], [33467, 124584504.17019355], [33523, 124732172.7319255], [33537, 124632193.6437593], [33551, 124106439.93048073], [33649, 123365872.6789478], [33705, 122940882.90605024], [33719, 123175805.01518151], [33733, 123153359.62161453], [33747, 123114471.05338907], [33761, 123097474.23946057], [33775, 122883737.59091415], [33803, 123098453.52084807], [33817, 122936639.30788417], [33831, 122924753.59691769], [33845, 122896807.09120712], [34041, 122708112.7391923], [34055, 122918124.25740246], [34069, 122840249.77461393], [34083, 122682463.75869432], [34125, 122810483.7932138], [34139, 123045962.29161194], [34153, 122784781.73226829], [34167, 122784831.65431887]] \ No newline at end of file +[[28511, 120802330.24010743], [29225, 118082903.74277888], [29239, 118070363.8789473], [29253, 118075279.86292957], [29267, 118022675.45829052], [29281, 118257778.17484754], [29295, 118125941.00033565], [29309, 118035354.10604145], [29323, 118127266.68744084], [29337, 118585658.69194491], [29351, 117744372.49743575], [29365, 117691869.66194478], [29379, 118036200.53661384], [29393, 117915101.72318871], [29407, 117826344.62347144], [29421, 117789215.57594956], [29435, 118308202.61710443], [29449, 118353644.25662], [29463, 118236075.95838885], [29477, 118210995.74672404], [29547, 118424791.90053731], [29561, 118355625.61789405], [29575, 117813954.34624289], [29603, 118993199.12461421], [29617, 119059325.67750198], [29631, 119285306.86573192], [29645, 119215739.7921845], [29659, 119106055.12987131], [29673, 119131039.98097138], [29743, 119048335.57068431], [29757, 119169325.38387698], [29771, 119083578.64875492], [29785, 119207646.3526927], [29799, 119203556.575631], [29813, 119307726.34851475], [29827, 119400089.22388676], [29841, 119304251.66028532], [29855, 119287705.55192639], [29869, 119362585.2822308], [30009, 119366673.97455126], [30023, 119333031.69246957], [30037, 119184040.76763482], [30051, 119074664.77877972], [30065, 119260959.82249133], [30079, 119275534.03450201], [30093, 119153466.52929628], [30107, 119095440.07319383], [30121, 119291796.11063524], [30135, 119179992.87773387], [30149, 119603779.61420026], [30163, 119605931.44412534], [30177, 119738782.8664673], [30191, 119808673.3283711], [30205, 119748047.026924], [30219, 119761907.7932667], [30233, 119609025.71950495], [30247, 119754698.89292294], [30261, 119518715.20699653], [30513, 119897837.54730229], [30527, 119664580.38137917], [30541, 119612574.28137289], [30555, 119494542.5127772], [30569, 119405134.15722898], [30583, 119711124.7998581], [30597, 119481079.7775423], [30625, 119613093.73821689], [30639, 119652555.20771125], [30653, 119558671.10358252], [30667, 119563795.41354407], [30681, 119670829.96775977], [30695, 119725869.13649468], [30709, 119627961.830084], [30723, 119581034.8917982], [30737, 119642853.54306039], [30751, 119710871.15842113], [30765, 120058891.69835664], [30779, 119602189.66163461], [30793, 119614868.33582415], [30807, 119552315.24009162], [30821, 119781996.8017978], [30835, 120033498.58209655], [30849, 119766765.81837001], [30863, 119683071.67230517], [30877, 119793293.73284134], [30891, 119858367.46801451], [30905, 119899390.70197564], [30919, 119597257.7814524], [30933, 119610568.64763565], [30947, 119639855.88744308], [30961, 119695382.62447752], [30975, 119692627.97829385], [30989, 119793209.45350264], [31003, 119886618.69894955], [31017, 119885991.94684584], [31031, 119522315.71506312], [31045, 119792843.34645358], [32109, 131539712.36154266], [32123, 131697883.09901872], [32137, 131663678.29564989], [32151, 131631357.83783212], [32165, 131650668.35583709], [32179, 131512286.32407019], [32193, 131675977.23686875], [32207, 132835474.85257581], [32221, 134109630.12086952], [32235, 134356867.02474004], [32249, 134084119.24327068], [32263, 134142650.19571333], [32277, 134190599.70172572], [32305, 136034942.489979], [32319, 139565694.4747124], [32333, 139617497.1000485], [32347, 139525141.1544353], [32361, 139663472.96774638], [32375, 139752183.22406363], [32389, 139522084.02031356], [32403, 139710758.4397933], [32417, 139645533.58989802], [32431, 139845143.0721948], [32445, 139968350.3761459], [32571, 137481704.48719046], [32585, 137535454.6912412], [32599, 137454099.89625984], [32613, 137410912.36700368], [32627, 137574822.65771085], [32641, 137240003.95196006], [32655, 137395277.10226864], [32851, 138342462.69257697], [32865, 138487976.99334526], [32879, 138449824.43319264], [32893, 138617313.73252463], [32907, 140312107.2827195], [32921, 140241938.55148122], [32991, 140361726.7899456], [33005, 140322236.904557], [33019, 140024311.64641353], [33033, 140268520.08394235], [33047, 140426198.90286842], [33061, 140706341.1844009], [33075, 140629981.15197995], [33089, 155205236.83303696], [33103, 170007272.95952484], [33117, 170218165.44463086], [33131, 170020435.90046725], [33145, 170215924.37910944], [33159, 170241990.56397045], [33187, 140795897.23676893], [33201, 140813008.9730573], [33215, 138935104.87955603], [33229, 133839473.81482247], [33243, 133740454.54755159], [33271, 126934662.16220972], [33299, 127160572.7350715], [33313, 127016498.77750044], [33327, 127183037.29346305], [33341, 127297252.0421462], [33355, 127548431.5094666], [33369, 127999892.79141228], [33383, 128199227.7387387], [33397, 128506375.66841185], [33411, 128382685.92839307], [33425, 128451516.09012455], [33439, 129394210.38226357], [33453, 124546390.3418493], [33467, 124584504.17019355], [33523, 124732172.7319255], [33537, 124632193.6437593], [33551, 124106439.93048073], [33649, 123365872.6789478], [33705, 122940882.90605024], [33719, 123175805.01518151], [33733, 123153359.62161453], [33747, 123114471.05338907], [33761, 123097474.23946057], [33775, 122883737.59091415], [33803, 123098453.52084807], [33817, 122936639.30788417], [33831, 122924753.59691769], [33845, 122896807.09120712], [34041, 122708112.7391923], [34055, 122918124.25740246], [34069, 122840249.77461393], [34083, 122682463.75869432], [34125, 122810483.7932138], [34139, 123045962.29161194], [34153, 122784781.73226829], [34167, 122784833.45481487]] \ No newline at end of file diff --git a/graphs/summary/cluster.KMeansBenchmark.time_fit.json b/graphs/summary/cluster.KMeansBenchmark.time_fit.json index 3b4154614a..5ead6e7da8 100644 --- a/graphs/summary/cluster.KMeansBenchmark.time_fit.json +++ b/graphs/summary/cluster.KMeansBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 3.763175147578693], [29225, 4.1942325767538025], [29239, 4.229288717396807], [29253, 3.890990387598734], [29267, 3.8476661539144805], [29281, 3.6108903970715147], [29295, 3.5501763551154544], [29309, 3.704252690904214], [29323, 3.7051679984379926], [29337, 3.7359919326870394], [29351, 3.6747201045436717], [29365, 3.566538169143622], [29379, 3.6627402955773896], [29393, 3.711241914500062], [29407, 3.5640271075089873], [29421, 3.786027079961798], [29435, 3.667910036683717], [29449, 4.189864402121898], [29463, 4.142284661158902], [29477, 4.068486249768361], [29547, 4.04176794731931], [29561, 3.924980423986263], [29575, 3.494958143722073], [29603, 3.5142717445141476], [29617, 3.5214071450518016], [29631, 3.5523630872275658], [29645, 3.5369245242909284], [29659, 3.4823029019387177], [29673, 3.5243444904218095], [29743, 3.456253321234625], [29757, 3.5042784353518606], [29771, 3.534435539661124], [29785, 4.293254032071866], [29799, 4.1440584564416625], [29813, 4.146371381542714], [29827, 4.135931909751912], [29841, 4.185090805318897], [29855, 4.114538583897038], [29869, 4.153495177679167], [30009, 4.169328870453232], [30023, 4.141857287985173], [30037, 4.164379061424705], [30051, 4.026389706815295], [30065, 4.094769080514271], [30079, 4.058537890747274], [30093, 4.008687818341354], [30107, 3.894144839048708], [30121, 3.933689589856142], [30135, 3.945921260522747], [30149, 3.2134820352879236], [30163, 2.5240603258807837], [30177, 2.5954842825595494], [30191, 2.519138813047762], [30205, 2.6672715683046646], [30219, 2.607556222206946], [30233, 2.589526671684425], [30247, 2.548823376585572], [30261, 2.611375063384058], [30513, 2.6022989038896607], [30527, 2.5539444403128764], [30541, 2.5302777541798256], [30555, 2.6066512062754295], [30569, 2.5217791424245513], [30583, 2.57575040097795], [30597, 2.547358542391075], [30625, 2.6752818308741784], [30639, 2.5740178790746944], [30653, 2.5977086762951758], [30667, 2.5921517822094886], [30681, 2.6335512710465157], [30695, 2.731791543953264], [30709, 2.549551957249472], [30723, 2.6733007572991663], [30737, 2.6372632955558903], [30751, 2.585655043708398], [30765, 2.562079540007698], [30779, 2.5421857459287036], [30793, 2.7014863408421994], [30807, 2.5755594457589712], [30821, 2.5450477071783926], [30835, 2.636639431900751], [30849, 2.5646209882939797], [30863, 2.623241346796106], [30877, 2.5537968310582464], [30891, 2.4967981358844487], [30905, 2.5134757019688503], [30919, 2.598532164505858], [30933, 2.4918555128067954], [30947, 2.546036765028987], [30961, 2.463526880855325], [30975, 2.5344474585864667], [30989, 2.5622402503673762], [31003, 2.6140829955132423], [31017, 2.5859244471580123], [31031, 2.5531522990846436], [31045, 2.6119462359996355], [32109, 2.1799534762378623], [32123, 2.1427574121383244], [32137, 2.209749950302678], [32151, 2.1979228051834836], [32165, 2.231700290947301], [32179, 2.224142640101748], [32193, 2.237876272350308], [32207, 2.2235665990673374], [32221, 2.183967371076575], [32235, 2.1471672464432663], [32249, 2.1764166029692777], [32263, 2.1991558950842967], [32277, 2.277624735693466], [32305, 2.282586509982749], [32319, 2.2041573543528683], [32333, 2.3019561757037916], [32347, 2.238092319748349], [32361, 2.2201421540300603], [32375, 2.176891624438878], [32389, 2.227707893852433], [32403, 2.191732247014003], [32417, 2.320496756063219], [32431, 2.2528529364786887], [32445, 2.21664016317332], [32571, 1.7679930428183204], [32585, 1.8622668754702685], [32599, 1.9254516284479504], [32613, 1.9720613222615686], [32627, 1.897264841817404], [32641, 1.8691752019703818], [32655, 1.8579471383526094], [32851, 1.904653047421913], [32865, 1.92225222650602], [32879, 1.9092155015671668], [32893, 1.9331389945816853], [32907, 1.9047973395107147], [32921, 1.893161192866058], [32991, 1.909555341610433], [33005, 1.8450026819618068], [33019, 1.8608921230635023], [33033, 1.8923498066059792], [33047, 1.8202081269975978], [33061, 1.816690320295833], [33075, 1.7602210808663576], [33089, 1.7587293579425745], [33103, 1.736209394602575], [33117, 1.7266253879209235], [33131, 1.7140809345426942], [33145, 1.7109558912662644], [33159, 1.7233722473741995], [33187, 1.7653427252143739], [33201, 1.7321060908035772], [33215, 1.7705449496777432], [33229, 1.9157582477877164], [33243, 1.9134409235669034], [33271, 2.134463051090202], [33299, 2.2695547122242754], [33313, 2.082634523934238], [33327, 2.082451872622257], [33341, 2.0982931485284766], [33355, 2.128989261218109], [33369, 2.0446568625542265], [33383, 2.1245713363170435], [33397, 2.0991435686022326], [33411, 2.1740101019948432], [33425, 2.079810305871682], [33439, 2.0699880051618695], [33453, 2.1597644358309234], [33467, 2.095893137896759], [33523, 2.0980105170591052], [33537, 2.1137274152552292], [33551, 2.062832606403292], [33649, 2.166232433526393], [33705, 2.0472196319831952], [33719, 2.098427410445254], [33733, 2.0974222599838814], [33747, 2.0856226997605924], [33761, 2.05178405284351], [33775, 2.1229609578518014], [33803, 2.0569952691244597], [33817, 2.101742687776623], [33831, 2.100504681387873], [33845, 2.113863105479707], [34041, 2.081662874523473], [34055, 2.0225649035897164], [34069, 2.0468993526554846], [34083, 2.0361327376161023], [34125, 2.0432723543260387], [34139, 2.0326446176934776], [34153, 2.0179042213659275], [34167, 2.0351300541214874]] \ No newline at end of file +[[28511, 3.763175147578693], [29225, 4.1942325767538025], [29239, 4.229288717396807], [29253, 3.890990387598734], [29267, 3.8476661539144805], [29281, 3.6108903970715147], [29295, 3.5501763551154544], [29309, 3.704252690904214], [29323, 3.7051679984379926], [29337, 3.7359919326870394], [29351, 3.6747201045436717], [29365, 3.566538169143622], [29379, 3.6627402955773896], [29393, 3.711241914500062], [29407, 3.5640271075089873], [29421, 3.786027079961798], [29435, 3.667910036683717], [29449, 4.189864402121898], [29463, 4.142284661158902], [29477, 4.068486249768361], [29547, 4.04176794731931], [29561, 3.924980423986263], [29575, 3.494958143722073], [29603, 3.5142717445141476], [29617, 3.5214071450518016], [29631, 3.5523630872275658], [29645, 3.5369245242909284], [29659, 3.4823029019387177], [29673, 3.5243444904218095], [29743, 3.456253321234625], [29757, 3.5042784353518606], [29771, 3.534435539661124], [29785, 4.293254032071866], [29799, 4.1440584564416625], [29813, 4.146371381542714], [29827, 4.135931909751912], [29841, 4.185090805318897], [29855, 4.114538583897038], [29869, 4.153495177679167], [30009, 4.169328870453232], [30023, 4.141857287985173], [30037, 4.164379061424705], [30051, 4.026389706815295], [30065, 4.094769080514271], [30079, 4.058537890747274], [30093, 4.008687818341354], [30107, 3.894144839048708], [30121, 3.933689589856142], [30135, 3.945921260522747], [30149, 3.2134820352879236], [30163, 2.5240603258807837], [30177, 2.5954842825595494], [30191, 2.519138813047762], [30205, 2.6672715683046646], [30219, 2.607556222206946], [30233, 2.589526671684425], [30247, 2.548823376585572], [30261, 2.611375063384058], [30513, 2.6022989038896607], [30527, 2.5539444403128764], [30541, 2.5302777541798256], [30555, 2.6066512062754295], [30569, 2.5217791424245513], [30583, 2.57575040097795], [30597, 2.547358542391075], [30625, 2.6752818308741784], [30639, 2.5740178790746944], [30653, 2.5977086762951758], [30667, 2.5921517822094886], [30681, 2.6335512710465157], [30695, 2.731791543953264], [30709, 2.549551957249472], [30723, 2.6733007572991663], [30737, 2.6372632955558903], [30751, 2.585655043708398], [30765, 2.562079540007698], [30779, 2.5421857459287036], [30793, 2.7014863408421994], [30807, 2.5755594457589712], [30821, 2.5450477071783926], [30835, 2.636639431900751], [30849, 2.5646209882939797], [30863, 2.623241346796106], [30877, 2.5537968310582464], [30891, 2.4967981358844487], [30905, 2.5134757019688503], [30919, 2.598532164505858], [30933, 2.4918555128067954], [30947, 2.546036765028987], [30961, 2.463526880855325], [30975, 2.5344474585864667], [30989, 2.5622402503673762], [31003, 2.6140829955132423], [31017, 2.5859244471580123], [31031, 2.5531522990846436], [31045, 2.6119462359996355], [32109, 2.1799534762378623], [32123, 2.1427574121383244], [32137, 2.209749950302678], [32151, 2.1979228051834836], [32165, 2.231700290947301], [32179, 2.224142640101748], [32193, 2.237876272350308], [32207, 2.2235665990673374], [32221, 2.183967371076575], [32235, 2.1471672464432663], [32249, 2.1764166029692777], [32263, 2.1991558950842967], [32277, 2.277624735693466], [32305, 2.282586509982749], [32319, 2.2041573543528683], [32333, 2.3019561757037916], [32347, 2.238092319748349], [32361, 2.2201421540300603], [32375, 2.176891624438878], [32389, 2.227707893852433], [32403, 2.191732247014003], [32417, 2.320496756063219], [32431, 2.2528529364786887], [32445, 2.21664016317332], [32571, 1.7679930428183204], [32585, 1.8622668754702685], [32599, 1.9254516284479504], [32613, 1.9720613222615686], [32627, 1.897264841817404], [32641, 1.8691752019703818], [32655, 1.8579471383526094], [32851, 1.904653047421913], [32865, 1.92225222650602], [32879, 1.9092155015671668], [32893, 1.9331389945816853], [32907, 1.9047973395107147], [32921, 1.893161192866058], [32991, 1.909555341610433], [33005, 1.8450026819618068], [33019, 1.8608921230635023], [33033, 1.8923498066059792], [33047, 1.8202081269975978], [33061, 1.816690320295833], [33075, 1.7602210808663576], [33089, 1.7587293579425745], [33103, 1.736209394602575], [33117, 1.7266253879209235], [33131, 1.7140809345426942], [33145, 1.7109558912662644], [33159, 1.7233722473741995], [33187, 1.7653427252143739], [33201, 1.7321060908035772], [33215, 1.7705449496777432], [33229, 1.9157582477877164], [33243, 1.9134409235669034], [33271, 2.134463051090202], [33299, 2.2695547122242754], [33313, 2.082634523934238], [33327, 2.082451872622257], [33341, 2.0982931485284766], [33355, 2.128989261218109], [33369, 2.0446568625542265], [33383, 2.1245713363170435], [33397, 2.0991435686022326], [33411, 2.1740101019948432], [33425, 2.079810305871682], [33439, 2.0699880051618695], [33453, 2.1597644358309234], [33467, 2.095893137896759], [33523, 2.0980105170591052], [33537, 2.1137274152552292], [33551, 2.062832606403292], [33649, 2.166232433526393], [33705, 2.0472196319831952], [33719, 2.098427410445254], [33733, 2.0974222599838814], [33747, 2.0856226997605924], [33761, 2.05178405284351], [33775, 2.1229609578518014], [33803, 2.0569952691244597], [33817, 2.101742687776623], [33831, 2.100504681387873], [33845, 2.113863105479707], [34041, 2.081662874523473], [34055, 2.0225649035897164], [34069, 2.0468993526554846], [34083, 2.0361327376161023], [34125, 2.0432723543260387], [34139, 2.0326446176934776], [34153, 2.0179042213659275], [34167, 2.0395135448322805]] \ No newline at end of file diff --git a/graphs/summary/cluster.KMeansBenchmark.time_predict.json b/graphs/summary/cluster.KMeansBenchmark.time_predict.json index 37b19ccbb0..88a8555297 100644 --- a/graphs/summary/cluster.KMeansBenchmark.time_predict.json +++ b/graphs/summary/cluster.KMeansBenchmark.time_predict.json @@ -1 +1 @@ -[[28511, 0.009811082407641575], [29225, 0.016517316685493742], [29239, 0.018168982696206905], [29253, 0.010726663873928037], [29267, 0.011014280382566372], [29281, 0.010321169940989328], [29295, 0.010340507215935811], [29309, 0.010636278329133091], [29323, 0.0104071161590608], [29337, 0.010379967704103602], [29351, 0.010938407958840761], [29365, 0.010009867526254983], [29379, 0.010818333836067447], [29393, 0.010903376288786043], [29407, 0.010176518731416047], [29421, 0.011380971719070924], [29435, 0.01073149124272823], [29449, 0.019129369077264143], [29463, 0.01858675388922737], [29477, 0.019841314979886213], [29547, 0.020024373393150836], [29561, 0.017273741504494747], [29575, 0.016309167603750833], [29603, 0.015908501690423585], [29617, 0.015001007309587835], [29631, 0.015641545838915655], [29645, 0.0158335526176197], [29659, 0.015155731672438999], [29673, 0.015262840234339116], [29743, 0.015336701651886334], [29757, 0.016260612879970864], [29771, 0.015196973300243805], [29785, 0.017540340432188058], [29799, 0.017182548615460667], [29813, 0.018278495260590135], [29827, 0.017287810696466274], [29841, 0.017131187134094207], [29855, 0.01678982001885212], [29869, 0.016629123028764257], [30009, 0.017503905798074842], [30023, 0.018518970789580216], [30037, 0.01881388695015307], [30051, 0.017936540752620727], [30065, 0.02059299728989988], [30079, 0.018279284100604136], [30093, 0.017132981885010792], [30107, 0.017215958452828833], [30121, 0.01881043498855866], [30135, 0.016640406824443246], [30149, 0.017694589924743792], [30163, 0.019060066428059626], [30177, 0.018489273440273672], [30191, 0.019429078726738658], [30205, 0.017656087955674495], [30219, 0.01866508074915523], [30233, 0.01850663105182577], [30247, 0.016742653868244764], [30261, 0.018258200104989682], [30513, 0.017739257569294946], [30527, 0.017731849048918998], [30541, 0.018714144300193566], [30555, 0.02045834402471782], [30569, 0.018013816422663073], [30583, 0.018268490062014583], [30597, 0.01786085974742665], [30625, 0.02084607091397934], [30639, 0.016485807740428838], [30653, 0.01826822739913519], [30667, 0.017563161523893686], [30681, 0.017600988075981316], [30695, 0.019523217959411848], [30709, 0.018102718531876116], [30723, 0.020785259340924046], [30737, 0.017784984057665945], [30751, 0.019196503825954704], [30765, 0.019566713037253384], [30779, 0.019468751225369816], [30793, 0.01948594560651315], [30807, 0.0195882931808737], [30821, 0.01671080512686251], [30835, 0.01824320260893887], [30849, 0.01890740906494452], [30863, 0.018586607426086962], [30877, 0.017602193097862456], [30891, 0.019903177151300175], [30905, 0.01932823071746341], [30919, 0.018457627195159185], [30933, 0.019451175300638356], [30947, 0.019489153419016685], [30961, 0.01877012553984669], [30975, 0.019632399954230086], [30989, 0.01892486473794796], [31003, 0.019490641887675235], [31017, 0.018641376822156296], [31031, 0.02066179703971465], [31045, 0.01812054095653629], [32109, 0.012371127562644597], [32123, 0.01291423646889269], [32137, 0.012768560220908847], [32151, 0.012446509976506596], [32165, 0.01264910369018217], [32179, 0.013383848576706384], [32193, 0.012798023117578125], [32207, 0.012896133090704354], [32221, 0.012841112983295716], [32235, 0.01335566073861078], [32249, 0.012884190186511213], [32263, 0.011881423461991074], [32277, 0.0121355554328326], [32305, 0.012213686002166262], [32319, 0.012081501044405793], [32333, 0.012794950455494468], [32347, 0.01299012957674542], [32361, 0.013110539055293677], [32375, 0.013979344913715934], [32389, 0.012546755396080638], [32403, 0.014954485953686723], [32417, 0.01427225500314224], [32431, 0.012609953651494199], [32445, 0.013215477236007585], [32571, 0.012238973009956876], [32585, 0.013156415917349078], [32599, 0.013763568357699903], [32613, 0.012847546435221069], [32627, 0.014184368960402384], [32641, 0.012450671728957037], [32655, 0.01358559605148475], [32851, 0.011157416978726497], [32865, 0.011243549729945946], [32879, 0.011097188708365797], [32893, 0.011377032149510196], [32907, 0.011343738021284818], [32921, 0.011212233516085284], [32991, 0.0112370482405111], [33005, 0.011957441053047363], [33019, 0.010178868288482364], [33033, 0.01085083858037552], [33047, 0.011343648574796205], [33061, 0.01172177728770138], [33075, 0.01222208337612235], [33089, 0.011565452659412428], [33103, 0.012188057025702644], [33117, 0.011813960837946875], [33131, 0.01252415726868503], [33145, 0.012604553928647854], [33159, 0.011757862930442285], [33187, 0.011842854208418059], [33201, 0.011655711430910123], [33215, 0.012177039246605199], [33229, 0.011880722072234357], [33243, 0.01171342271073332], [33271, 0.01188359928406686], [33299, 0.013853760591417344], [33313, 0.01247400045566308], [33327, 0.012137874274194924], [33341, 0.012305935488803314], [33355, 0.013421077727167184], [33369, 0.012497868941032775], [33383, 0.012761295685000418], [33397, 0.012797244341793168], [33411, 0.011673943919881172], [33425, 0.012199220249889526], [33439, 0.01190613732362657], [33453, 0.011962204943442729], [33467, 0.012631395348668726], [33523, 0.012125669438820385], [33537, 0.012616835077140981], [33551, 0.01250257767193929], [33649, 0.013262687238864207], [33705, 0.012482846983602292], [33719, 0.011808982138509387], [33733, 0.01234615212581301], [33747, 0.013392240225125793], [33761, 0.013016274467781266], [33775, 0.014689581060730917], [33803, 0.012482083240406476], [33817, 0.012675208077913384], [33831, 0.01190140722410491], [33845, 0.013222791133391178], [34041, 0.011970489914911547], [34055, 0.01203961917498861], [34069, 0.011581200724495035], [34083, 0.011591141576424428], [34125, 0.011615653828975598], [34139, 0.011342963198657841], [34153, 0.011252155468935182], [34167, 0.01151909629362967]] \ No newline at end of file +[[28511, 0.009811082407641575], [29225, 0.016517316685493742], [29239, 0.018168982696206905], [29253, 0.010726663873928037], [29267, 0.011014280382566372], [29281, 0.010321169940989328], [29295, 0.010340507215935811], [29309, 0.010636278329133091], [29323, 0.0104071161590608], [29337, 0.010379967704103602], [29351, 0.010938407958840761], [29365, 0.010009867526254983], [29379, 0.010818333836067447], [29393, 0.010903376288786043], [29407, 0.010176518731416047], [29421, 0.011380971719070924], [29435, 0.01073149124272823], [29449, 0.019129369077264143], [29463, 0.01858675388922737], [29477, 0.019841314979886213], [29547, 0.020024373393150836], [29561, 0.017273741504494747], [29575, 0.016309167603750833], [29603, 0.015908501690423585], [29617, 0.015001007309587835], [29631, 0.015641545838915655], [29645, 0.0158335526176197], [29659, 0.015155731672438999], [29673, 0.015262840234339116], [29743, 0.015336701651886334], [29757, 0.016260612879970864], [29771, 0.015196973300243805], [29785, 0.017540340432188058], [29799, 0.017182548615460667], [29813, 0.018278495260590135], [29827, 0.017287810696466274], [29841, 0.017131187134094207], [29855, 0.01678982001885212], [29869, 0.016629123028764257], [30009, 0.017503905798074842], [30023, 0.018518970789580216], [30037, 0.01881388695015307], [30051, 0.017936540752620727], [30065, 0.02059299728989988], [30079, 0.018279284100604136], [30093, 0.017132981885010792], [30107, 0.017215958452828833], [30121, 0.01881043498855866], [30135, 0.016640406824443246], [30149, 0.017694589924743792], [30163, 0.019060066428059626], [30177, 0.018489273440273672], [30191, 0.019429078726738658], [30205, 0.017656087955674495], [30219, 0.01866508074915523], [30233, 0.01850663105182577], [30247, 0.016742653868244764], [30261, 0.018258200104989682], [30513, 0.017739257569294946], [30527, 0.017731849048918998], [30541, 0.018714144300193566], [30555, 0.02045834402471782], [30569, 0.018013816422663073], [30583, 0.018268490062014583], [30597, 0.01786085974742665], [30625, 0.02084607091397934], [30639, 0.016485807740428838], [30653, 0.01826822739913519], [30667, 0.017563161523893686], [30681, 0.017600988075981316], [30695, 0.019523217959411848], [30709, 0.018102718531876116], [30723, 0.020785259340924046], [30737, 0.017784984057665945], [30751, 0.019196503825954704], [30765, 0.019566713037253384], [30779, 0.019468751225369816], [30793, 0.01948594560651315], [30807, 0.0195882931808737], [30821, 0.01671080512686251], [30835, 0.01824320260893887], [30849, 0.01890740906494452], [30863, 0.018586607426086962], [30877, 0.017602193097862456], [30891, 0.019903177151300175], [30905, 0.01932823071746341], [30919, 0.018457627195159185], [30933, 0.019451175300638356], [30947, 0.019489153419016685], [30961, 0.01877012553984669], [30975, 0.019632399954230086], [30989, 0.01892486473794796], [31003, 0.019490641887675235], [31017, 0.018641376822156296], [31031, 0.02066179703971465], [31045, 0.01812054095653629], [32109, 0.012371127562644597], [32123, 0.01291423646889269], [32137, 0.012768560220908847], [32151, 0.012446509976506596], [32165, 0.01264910369018217], [32179, 0.013383848576706384], [32193, 0.012798023117578125], [32207, 0.012896133090704354], [32221, 0.012841112983295716], [32235, 0.01335566073861078], [32249, 0.012884190186511213], [32263, 0.011881423461991074], [32277, 0.0121355554328326], [32305, 0.012213686002166262], [32319, 0.012081501044405793], [32333, 0.012794950455494468], [32347, 0.01299012957674542], [32361, 0.013110539055293677], [32375, 0.013979344913715934], [32389, 0.012546755396080638], [32403, 0.014954485953686723], [32417, 0.01427225500314224], [32431, 0.012609953651494199], [32445, 0.013215477236007585], [32571, 0.012238973009956876], [32585, 0.013156415917349078], [32599, 0.013763568357699903], [32613, 0.012847546435221069], [32627, 0.014184368960402384], [32641, 0.012450671728957037], [32655, 0.01358559605148475], [32851, 0.011157416978726497], [32865, 0.011243549729945946], [32879, 0.011097188708365797], [32893, 0.011377032149510196], [32907, 0.011343738021284818], [32921, 0.011212233516085284], [32991, 0.0112370482405111], [33005, 0.011957441053047363], [33019, 0.010178868288482364], [33033, 0.01085083858037552], [33047, 0.011343648574796205], [33061, 0.01172177728770138], [33075, 0.01222208337612235], [33089, 0.011565452659412428], [33103, 0.012188057025702644], [33117, 0.011813960837946875], [33131, 0.01252415726868503], [33145, 0.012604553928647854], [33159, 0.011757862930442285], [33187, 0.011842854208418059], [33201, 0.011655711430910123], [33215, 0.012177039246605199], [33229, 0.011880722072234357], [33243, 0.01171342271073332], [33271, 0.01188359928406686], [33299, 0.013853760591417344], [33313, 0.01247400045566308], [33327, 0.012137874274194924], [33341, 0.012305935488803314], [33355, 0.013421077727167184], [33369, 0.012497868941032775], [33383, 0.012761295685000418], [33397, 0.012797244341793168], [33411, 0.011673943919881172], [33425, 0.012199220249889526], [33439, 0.01190613732362657], [33453, 0.011962204943442729], [33467, 0.012631395348668726], [33523, 0.012125669438820385], [33537, 0.012616835077140981], [33551, 0.01250257767193929], [33649, 0.013262687238864207], [33705, 0.012482846983602292], [33719, 0.011808982138509387], [33733, 0.01234615212581301], [33747, 0.013392240225125793], [33761, 0.013016274467781266], [33775, 0.014689581060730917], [33803, 0.012482083240406476], [33817, 0.012675208077913384], [33831, 0.01190140722410491], [33845, 0.013222791133391178], [34041, 0.011970489914911547], [34055, 0.01203961917498861], [34069, 0.011581200724495035], [34083, 0.011591141576424428], [34125, 0.011615653828975598], [34139, 0.011342963198657841], [34153, 0.011252155468935182], [34167, 0.011557769719601568]] \ No newline at end of file diff --git a/graphs/summary/cluster.KMeansBenchmark.time_transform.json b/graphs/summary/cluster.KMeansBenchmark.time_transform.json index 055e290de2..ddedc7d739 100644 --- a/graphs/summary/cluster.KMeansBenchmark.time_transform.json +++ b/graphs/summary/cluster.KMeansBenchmark.time_transform.json @@ -1 +1 @@ -[[28511, 0.4589108436639611], [29225, 0.5837735592870249], [29239, 0.581735879729818], [29253, 0.4561679708003093], [29267, 0.4646848887144182], [29281, 0.4694569811659092], [29295, 0.4621471500905432], [29309, 0.45552457690685344], [29323, 0.46055369191961665], [29337, 0.45368865894692073], [29351, 0.4815113145323555], [29365, 0.45051864303827655], [29379, 0.4596718400270289], [29393, 0.4694467765203902], [29407, 0.4857924715606907], [29421, 0.4741738777846114], [29435, 0.4585324863843263], [29449, 0.6948552043119959], [29463, 0.6800939696888603], [29477, 0.652520172816539], [29547, 0.7722514552047471], [29561, 0.6290438387886325], [29575, 0.5782556074392212], [29603, 0.5649574164288846], [29617, 0.5593511843570302], [29631, 0.5672118852428548], [29645, 0.5730397645063061], [29659, 0.5711941469404471], [29673, 0.5669149681042677], [29743, 0.5789878377923974], [29757, 0.5890132704288253], [29771, 0.5852128484813581], [29785, 0.6618664907727975], [29799, 0.5828937743850975], [29813, 0.6053209245858835], [29827, 0.5899484714930624], [29841, 0.5936157997282566], [29855, 0.6130188180675208], [29869, 0.5970407670204877], [30009, 0.6067796916128092], [30023, 0.6056086733177068], [30037, 0.6035014503595271], [30051, 0.599501864958465], [30065, 0.5931679361903869], [30079, 0.6093639434923747], [30093, 0.6086315295999288], [30107, 0.5867012665846908], [30121, 0.597437315519613], [30135, 0.5770210817528412], [30149, 0.5944174169356486], [30163, 0.613351172520487], [30177, 0.5985878591406216], [30191, 0.6074794646899604], [30205, 0.6052387877685904], [30219, 0.6119579836340027], [30233, 0.6144740777977566], [30247, 0.602274777171871], [30261, 0.6047097943721484], [30513, 0.5978966227167225], [30527, 0.6017019451878217], [30541, 0.5984779865462765], [30555, 0.6078135895763175], [30569, 0.6050114063815923], [30583, 0.6065459169918829], [30597, 0.6069583314359943], [30625, 0.6054858262142088], [30639, 0.6024805286616868], [30653, 0.6123599482019951], [30667, 0.6012085786350453], [30681, 0.6131753364996194], [30695, 0.6035458873736128], [30709, 0.6042384324503846], [30723, 0.5855692715772662], [30737, 0.6087001744602681], [30751, 0.6130428438437543], [30765, 0.623546927078503], [30779, 0.5970626572887054], [30793, 0.6031011256383915], [30807, 0.6033020440998501], [30821, 0.6040595930905239], [30835, 0.5935478132942501], [30849, 0.5932439002181108], [30863, 0.5962821875786125], [30877, 0.6171406834225615], [30891, 0.6191711740548371], [30905, 0.6053002598668841], [30919, 0.5926534974473058], [30933, 0.6162074827951812], [30947, 0.6183848717357714], [30961, 0.6116662799706039], [30975, 0.5944656422342138], [30989, 0.5977482691235577], [31003, 0.6132099035235877], [31017, 0.5828081577572547], [31031, 0.6301498844679152], [31045, 0.5921726566415635], [32109, 0.6241572539835314], [32123, 0.6042372448848873], [32137, 0.6284851662862851], [32151, 0.6174423532518172], [32165, 0.621480446838839], [32179, 0.6119568394153454], [32193, 0.6238779726427327], [32207, 0.6176714927439781], [32221, 0.6608852182799522], [32235, 0.6027889933090735], [32249, 0.6085216086946402], [32263, 0.5816811730775097], [32277, 0.5964319591504861], [32305, 0.5911962810599833], [32319, 0.6011698230648609], [32333, 0.6017442250978753], [32347, 0.5963593758108151], [32361, 0.5868467401647255], [32375, 0.5656846831379795], [32389, 0.5968374303811317], [32403, 0.5869434007531407], [32417, 0.5940332640353803], [32431, 0.5790088104905106], [32445, 0.6063272614348497], [32571, 0.5793485729679091], [32585, 0.5937962369171298], [32599, 0.6662323902075902], [32613, 0.5994666581870941], [32627, 0.5948179532299175], [32641, 0.5930814796958677], [32655, 0.7028978404832028], [32851, 0.600183522862256], [32865, 0.5911656832422054], [32879, 0.5850261979712447], [32893, 0.5949503705119504], [32907, 0.6187838021826866], [32921, 0.6117776057550043], [32991, 0.6098573723835363], [33005, 0.6239820516789125], [33019, 0.6118968026943254], [33033, 0.619678698050605], [33047, 0.6959003138715774], [33061, 0.7142271649739259], [33075, 0.7268937598010435], [33089, 0.7434230354391544], [33103, 0.7280942362225672], [33117, 0.7347518085915626], [33131, 0.7298324868671948], [33145, 0.7203472242274849], [33159, 0.7267455866809079], [33187, 0.7162816034513187], [33201, 0.7231315545453664], [33215, 0.7323629902703475], [33229, 0.6954952671401329], [33243, 0.6876410762627467], [33271, 0.6583532628131495], [33299, 0.6392287476932519], [33313, 0.6788833893185151], [33327, 0.6684731180880077], [33341, 0.6607458939733548], [33355, 0.6844579500745179], [33369, 0.6791405144971397], [33383, 0.7472748206282221], [33397, 0.7791722307154113], [33411, 0.698774404024086], [33425, 0.6742851157074815], [33439, 0.6036377217510996], [33453, 0.5660172816571037], [33467, 0.5736468273479872], [33523, 0.5639442351594774], [33537, 0.5807810793905367], [33551, 0.5911316558739655], [33649, 0.5489944554524694], [33705, 0.6315029735642429], [33719, 0.5830679740259671], [33733, 0.6621226784497712], [33747, 0.565264077441902], [33761, 0.6428011494619105], [33775, 0.6615582632271385], [33803, 0.5791057695317563], [33817, 0.6097947483457535], [33831, 0.6287100517248404], [33845, 0.5932483444820855], [34041, 0.5934217286289727], [34055, 0.5857625291264875], [34069, 0.5681262345887366], [34083, 0.5881978594566932], [34125, 0.5566658208314799], [34139, 0.593604857060764], [34153, 0.5765420983915104], [34167, 0.5582004258176388]] \ No newline at end of file +[[28511, 0.4589108436639611], [29225, 0.5837735592870249], [29239, 0.581735879729818], [29253, 0.4561679708003093], [29267, 0.4646848887144182], [29281, 0.4694569811659092], [29295, 0.4621471500905432], [29309, 0.45552457690685344], [29323, 0.46055369191961665], [29337, 0.45368865894692073], [29351, 0.4815113145323555], [29365, 0.45051864303827655], [29379, 0.4596718400270289], [29393, 0.4694467765203902], [29407, 0.4857924715606907], [29421, 0.4741738777846114], [29435, 0.4585324863843263], [29449, 0.6948552043119959], [29463, 0.6800939696888603], [29477, 0.652520172816539], [29547, 0.7722514552047471], [29561, 0.6290438387886325], [29575, 0.5782556074392212], [29603, 0.5649574164288846], [29617, 0.5593511843570302], [29631, 0.5672118852428548], [29645, 0.5730397645063061], [29659, 0.5711941469404471], [29673, 0.5669149681042677], [29743, 0.5789878377923974], [29757, 0.5890132704288253], [29771, 0.5852128484813581], [29785, 0.6618664907727975], [29799, 0.5828937743850975], [29813, 0.6053209245858835], [29827, 0.5899484714930624], [29841, 0.5936157997282566], [29855, 0.6130188180675208], [29869, 0.5970407670204877], [30009, 0.6067796916128092], [30023, 0.6056086733177068], [30037, 0.6035014503595271], [30051, 0.599501864958465], [30065, 0.5931679361903869], [30079, 0.6093639434923747], [30093, 0.6086315295999288], [30107, 0.5867012665846908], [30121, 0.597437315519613], [30135, 0.5770210817528412], [30149, 0.5944174169356486], [30163, 0.613351172520487], [30177, 0.5985878591406216], [30191, 0.6074794646899604], [30205, 0.6052387877685904], [30219, 0.6119579836340027], [30233, 0.6144740777977566], [30247, 0.602274777171871], [30261, 0.6047097943721484], [30513, 0.5978966227167225], [30527, 0.6017019451878217], [30541, 0.5984779865462765], [30555, 0.6078135895763175], [30569, 0.6050114063815923], [30583, 0.6065459169918829], [30597, 0.6069583314359943], [30625, 0.6054858262142088], [30639, 0.6024805286616868], [30653, 0.6123599482019951], [30667, 0.6012085786350453], [30681, 0.6131753364996194], [30695, 0.6035458873736128], [30709, 0.6042384324503846], [30723, 0.5855692715772662], [30737, 0.6087001744602681], [30751, 0.6130428438437543], [30765, 0.623546927078503], [30779, 0.5970626572887054], [30793, 0.6031011256383915], [30807, 0.6033020440998501], [30821, 0.6040595930905239], [30835, 0.5935478132942501], [30849, 0.5932439002181108], [30863, 0.5962821875786125], [30877, 0.6171406834225615], [30891, 0.6191711740548371], [30905, 0.6053002598668841], [30919, 0.5926534974473058], [30933, 0.6162074827951812], [30947, 0.6183848717357714], [30961, 0.6116662799706039], [30975, 0.5944656422342138], [30989, 0.5977482691235577], [31003, 0.6132099035235877], [31017, 0.5828081577572547], [31031, 0.6301498844679152], [31045, 0.5921726566415635], [32109, 0.6241572539835314], [32123, 0.6042372448848873], [32137, 0.6284851662862851], [32151, 0.6174423532518172], [32165, 0.621480446838839], [32179, 0.6119568394153454], [32193, 0.6238779726427327], [32207, 0.6176714927439781], [32221, 0.6608852182799522], [32235, 0.6027889933090735], [32249, 0.6085216086946402], [32263, 0.5816811730775097], [32277, 0.5964319591504861], [32305, 0.5911962810599833], [32319, 0.6011698230648609], [32333, 0.6017442250978753], [32347, 0.5963593758108151], [32361, 0.5868467401647255], [32375, 0.5656846831379795], [32389, 0.5968374303811317], [32403, 0.5869434007531407], [32417, 0.5940332640353803], [32431, 0.5790088104905106], [32445, 0.6063272614348497], [32571, 0.5793485729679091], [32585, 0.5937962369171298], [32599, 0.6662323902075902], [32613, 0.5994666581870941], [32627, 0.5948179532299175], [32641, 0.5930814796958677], [32655, 0.7028978404832028], [32851, 0.600183522862256], [32865, 0.5911656832422054], [32879, 0.5850261979712447], [32893, 0.5949503705119504], [32907, 0.6187838021826866], [32921, 0.6117776057550043], [32991, 0.6098573723835363], [33005, 0.6239820516789125], [33019, 0.6118968026943254], [33033, 0.619678698050605], [33047, 0.6959003138715774], [33061, 0.7142271649739259], [33075, 0.7268937598010435], [33089, 0.7434230354391544], [33103, 0.7280942362225672], [33117, 0.7347518085915626], [33131, 0.7298324868671948], [33145, 0.7203472242274849], [33159, 0.7267455866809079], [33187, 0.7162816034513187], [33201, 0.7231315545453664], [33215, 0.7323629902703475], [33229, 0.6954952671401329], [33243, 0.6876410762627467], [33271, 0.6583532628131495], [33299, 0.6392287476932519], [33313, 0.6788833893185151], [33327, 0.6684731180880077], [33341, 0.6607458939733548], [33355, 0.6844579500745179], [33369, 0.6791405144971397], [33383, 0.7472748206282221], [33397, 0.7791722307154113], [33411, 0.698774404024086], [33425, 0.6742851157074815], [33439, 0.6036377217510996], [33453, 0.5660172816571037], [33467, 0.5736468273479872], [33523, 0.5639442351594774], [33537, 0.5807810793905367], [33551, 0.5911316558739655], [33649, 0.5489944554524694], [33705, 0.6315029735642429], [33719, 0.5830679740259671], [33733, 0.6621226784497712], [33747, 0.565264077441902], [33761, 0.6428011494619105], [33775, 0.6615582632271385], [33803, 0.5791057695317563], [33817, 0.6097947483457535], [33831, 0.6287100517248404], [33845, 0.5932483444820855], [34041, 0.5934217286289727], [34055, 0.5857625291264875], [34069, 0.5681262345887366], [34083, 0.5881978594566932], [34125, 0.5566658208314799], [34139, 0.593604857060764], [34153, 0.5765420983915104], [34167, 0.5733042100384406]] \ No newline at end of file diff --git a/graphs/summary/cluster.KMeansBenchmark.track_test_score.json b/graphs/summary/cluster.KMeansBenchmark.track_test_score.json index 463d4a758f..619be42564 100644 --- a/graphs/summary/cluster.KMeansBenchmark.track_test_score.json +++ b/graphs/summary/cluster.KMeansBenchmark.track_test_score.json @@ -1 +1 @@ -[[28511, -1.915294922833897], [29225, -1.915294922833897], [29239, -1.915294922833897], [29253, -1.915294922833897], [29267, -1.915294922833897], [29281, -1.915294922833897], [29295, -1.9152952499399027], [29309, -1.9152948772725695], [29323, -1.915294922833897], [29337, -1.915294922833897], [29351, -1.915294922833897], [29365, -1.915294922833897], [29379, -1.915294922833897], [29393, -1.915294922833897], [29407, -1.915294922833897], [29421, -1.9152951681634012], [29435, -1.915294922833897], [29449, -1.915294922833897], [29463, -1.915294922833897], [29477, -1.915294922833897], [29547, -1.915294922833897], [29561, -1.915294922833897], [29575, -1.915294922833897], [29603, -1.915294922833897], [29617, -1.915294922833897], [29631, -1.915294922833897], [29645, -1.915294922833897], [29659, -1.915294922833897], [29673, -1.915294922833897], [29743, -1.915294922833897], [29757, -1.915294922833897], [29771, -1.915294922833897], [29785, -1.915294922833897], [29799, -1.915294922833897], [29813, -1.915294922833897], [29827, -1.915294922833897], [29841, -1.915294922833897], [29855, -1.915294922833897], [29869, -1.915294922833897], [30009, -1.915294922833897], [30023, -1.915294922833897], [30037, -1.915294922833897], [30051, -1.915294922833897], [30065, -1.915294922833897], [30079, -1.9152949228338971], [30093, -1.915294922833897], [30107, -1.915294922833897], [30121, -1.915294922833897], [30135, -1.915294922833897], [30149, -1.9152949228338971], [30163, -1.915294922833897], [30177, -1.9152946950271803], [30191, -1.9152949228338971], [30205, -1.915294922833897], [30219, -1.9152948954970956], [30233, -1.9152949228338971], [30247, -1.9152949228338971], [30261, -1.9152950341083015], [30513, -1.9152949137216315], [30527, -1.915294877272554], [30541, -1.915294922833897], [30555, -1.9152947975400834], [30569, -1.9152949228338971], [30583, -1.9152949228338971], [30597, -1.9152949228338971], [30625, -1.915294922833897], [30639, -1.9152949228338971], [30653, -1.9152949000532296], [30667, -1.9152945469524552], [30681, -1.915294922833897], [30695, -1.9152949228338971], [30709, -1.9152948089305388], [30723, -1.9152949228338971], [30737, -1.915294900053231], [30751, -1.9152950454986337], [30765, -1.915294922833897], [30779, -1.9152949228338971], [30793, -1.915294922833897], [30807, -1.9152949228338971], [30821, -1.9152949228338971], [30835, -1.9152947861498897], [30849, -1.9152948772725689], [30863, -1.9152949228338971], [30877, -1.9152949228338971], [30891, -1.9152949228338971], [30905, -1.9152949228338971], [30919, -1.915294922833897], [30933, -1.9152949228338971], [30947, -1.9152949228338971], [30961, -1.9152947633691226], [30975, -1.9152948089305388], [30989, -1.915294922833897], [31003, -1.9152949228338971], [31017, -1.9152949228338971], [31031, -1.9152949228338971], [31045, -1.9152949228338971], [32109, -1.9152949228338971], [32123, -1.9152949228338971], [32137, -1.915294922833897], [32151, -1.9152949228338971], [32165, -1.9152950113276317], [32179, -1.9152949228338971], [32193, -1.915294846898325], [32207, -1.9152949228338971], [32221, -1.915294922833897], [32235, -1.9152949228338971], [32249, -1.9152949228338971], [32263, -1.9152949228338971], [32277, -1.9152948772725615], [32305, -1.915294922833897], [32319, -1.915294922833897], [32333, -1.9152949228338971], [32347, -1.9152949228338971], [32361, -1.9152949228338971], [32375, -1.9152949228338971], [32389, -1.9152949228338971], [32403, -1.9152949228338971], [32417, -1.915295081275853], [32431, -1.9152948089305388], [32445, -1.9152941710710132], [32571, -1.9152949228338971], [32585, -1.915294922833897], [32599, -1.915294922833897], [32613, -1.915294922833897], [32627, -1.9152949228338971], [32641, -1.9152949228338971], [32655, -1.915294922833897], [32851, -1.915294922833897], [32865, -1.9152949228338971], [32879, -1.915294922833897], [32893, -1.9152949228338971], [32907, -1.915294907646788], [32921, -1.9152949228338971], [32991, -1.9152949228338971], [33005, -1.9152949228338971], [33019, -1.9152949228338971], [33033, -1.91529516816337], [33047, -1.9152949228338971], [33061, -1.864938204060858], [33075, -1.814581502780157], [33089, -1.8145815729832546], [33103, -1.8145815027801582], [33117, -1.8145815466668322], [33131, -1.8145815729832546], [33145, -1.8145815554130014], [33159, -1.8145815379206662], [33187, -1.814581590553508], [33201, -1.8145815290965794], [33215, -1.8145356380479536], [33229, -1.8143980153291177], [33243, -1.814397991221154], [33271, -1.814214515709774], [33299, -1.814214515709774], [33313, -1.8142145288653224], [33327, -1.8142144893986758], [33341, -1.8142145025542238], [33355, -1.8142145157097727], [33369, -1.8142144981690402], [33383, -1.814214506939406], [33397, -1.8142145157097738], [33411, -1.8142145157097738], [33425, -1.8142144762431247], [33439, -1.8142145025542238], [33453, -1.814214489398673], [33467, -1.814214542020872], [33523, -1.8142145025542238], [33537, -1.814214515709774], [33551, -1.8142144806283074], [33649, -1.814214542020872], [33705, -1.814214542020872], [33719, -1.814214495976449], [33733, -1.8142144630875754], [33747, -1.8142144762431245], [33761, -1.814214515709774], [33775, -1.814214489398673], [33803, -1.814214542020872], [33817, -1.8142145025542233], [33831, -1.814214524480139], [33845, -1.814214542020872], [34041, -1.8142145157097724], [34055, -1.8142145157097727], [34069, -1.8142145157097727], [34083, -1.8142144630875752], [34125, -1.814214533250506], [34139, -1.814214542020872], [34153, -1.8142144630875745], [34167, -1.814214502554223]] \ No newline at end of file +[[28511, -1.915294922833897], [29225, -1.915294922833897], [29239, -1.915294922833897], [29253, -1.915294922833897], [29267, -1.915294922833897], [29281, -1.915294922833897], [29295, -1.9152952499399027], [29309, -1.9152948772725695], [29323, -1.915294922833897], [29337, -1.915294922833897], [29351, -1.915294922833897], [29365, -1.915294922833897], [29379, -1.915294922833897], [29393, -1.915294922833897], [29407, -1.915294922833897], [29421, -1.9152951681634012], [29435, -1.915294922833897], [29449, -1.915294922833897], [29463, -1.915294922833897], [29477, -1.915294922833897], [29547, -1.915294922833897], [29561, -1.915294922833897], [29575, -1.915294922833897], [29603, -1.915294922833897], [29617, -1.915294922833897], [29631, -1.915294922833897], [29645, -1.915294922833897], [29659, -1.915294922833897], [29673, -1.915294922833897], [29743, -1.915294922833897], [29757, -1.915294922833897], [29771, -1.915294922833897], [29785, -1.915294922833897], [29799, -1.915294922833897], [29813, -1.915294922833897], [29827, -1.915294922833897], [29841, -1.915294922833897], [29855, -1.915294922833897], [29869, -1.915294922833897], [30009, -1.915294922833897], [30023, -1.915294922833897], [30037, -1.915294922833897], [30051, -1.915294922833897], [30065, -1.915294922833897], [30079, -1.9152949228338971], [30093, -1.915294922833897], [30107, -1.915294922833897], [30121, -1.915294922833897], [30135, -1.915294922833897], [30149, -1.9152949228338971], [30163, -1.915294922833897], [30177, -1.9152946950271803], [30191, -1.9152949228338971], [30205, -1.915294922833897], [30219, -1.9152948954970956], [30233, -1.9152949228338971], [30247, -1.9152949228338971], [30261, -1.9152950341083015], [30513, -1.9152949137216315], [30527, -1.915294877272554], [30541, -1.915294922833897], [30555, -1.9152947975400834], [30569, -1.9152949228338971], [30583, -1.9152949228338971], [30597, -1.9152949228338971], [30625, -1.915294922833897], [30639, -1.9152949228338971], [30653, -1.9152949000532296], [30667, -1.9152945469524552], [30681, -1.915294922833897], [30695, -1.9152949228338971], [30709, -1.9152948089305388], [30723, -1.9152949228338971], [30737, -1.915294900053231], [30751, -1.9152950454986337], [30765, -1.915294922833897], [30779, -1.9152949228338971], [30793, -1.915294922833897], [30807, -1.9152949228338971], [30821, -1.9152949228338971], [30835, -1.9152947861498897], [30849, -1.9152948772725689], [30863, -1.9152949228338971], [30877, -1.9152949228338971], [30891, -1.9152949228338971], [30905, -1.9152949228338971], [30919, -1.915294922833897], [30933, -1.9152949228338971], [30947, -1.9152949228338971], [30961, -1.9152947633691226], [30975, -1.9152948089305388], [30989, -1.915294922833897], [31003, -1.9152949228338971], [31017, -1.9152949228338971], [31031, -1.9152949228338971], [31045, -1.9152949228338971], [32109, -1.9152949228338971], [32123, -1.9152949228338971], [32137, -1.915294922833897], [32151, -1.9152949228338971], [32165, -1.9152950113276317], [32179, -1.9152949228338971], [32193, -1.915294846898325], [32207, -1.9152949228338971], [32221, -1.915294922833897], [32235, -1.9152949228338971], [32249, -1.9152949228338971], [32263, -1.9152949228338971], [32277, -1.9152948772725615], [32305, -1.915294922833897], [32319, -1.915294922833897], [32333, -1.9152949228338971], [32347, -1.9152949228338971], [32361, -1.9152949228338971], [32375, -1.9152949228338971], [32389, -1.9152949228338971], [32403, -1.9152949228338971], [32417, -1.915295081275853], [32431, -1.9152948089305388], [32445, -1.9152941710710132], [32571, -1.9152949228338971], [32585, -1.915294922833897], [32599, -1.915294922833897], [32613, -1.915294922833897], [32627, -1.9152949228338971], [32641, -1.9152949228338971], [32655, -1.915294922833897], [32851, -1.915294922833897], [32865, -1.9152949228338971], [32879, -1.915294922833897], [32893, -1.9152949228338971], [32907, -1.915294907646788], [32921, -1.9152949228338971], [32991, -1.9152949228338971], [33005, -1.9152949228338971], [33019, -1.9152949228338971], [33033, -1.91529516816337], [33047, -1.9152949228338971], [33061, -1.864938204060858], [33075, -1.814581502780157], [33089, -1.8145815729832546], [33103, -1.8145815027801582], [33117, -1.8145815466668322], [33131, -1.8145815729832546], [33145, -1.8145815554130014], [33159, -1.8145815379206662], [33187, -1.814581590553508], [33201, -1.8145815290965794], [33215, -1.8145356380479536], [33229, -1.8143980153291177], [33243, -1.814397991221154], [33271, -1.814214515709774], [33299, -1.814214515709774], [33313, -1.8142145288653224], [33327, -1.8142144893986758], [33341, -1.8142145025542238], [33355, -1.8142145157097727], [33369, -1.8142144981690402], [33383, -1.814214506939406], [33397, -1.8142145157097738], [33411, -1.8142145157097738], [33425, -1.8142144762431247], [33439, -1.8142145025542238], [33453, -1.814214489398673], [33467, -1.814214542020872], [33523, -1.8142145025542238], [33537, -1.814214515709774], [33551, -1.8142144806283074], [33649, -1.814214542020872], [33705, -1.814214542020872], [33719, -1.814214495976449], [33733, -1.8142144630875754], [33747, -1.8142144762431245], [33761, -1.814214515709774], [33775, -1.814214489398673], [33803, -1.814214542020872], [33817, -1.8142145025542233], [33831, -1.814214524480139], [33845, -1.814214542020872], [34041, -1.8142145157097724], [34055, -1.8142145157097727], [34069, -1.8142145157097727], [34083, -1.8142144630875752], [34125, -1.814214533250506], [34139, -1.814214542020872], [34153, -1.8142144630875745], [34167, -1.8142145104475529]] \ No newline at end of file diff --git a/graphs/summary/cluster.KMeansBenchmark.track_train_score.json b/graphs/summary/cluster.KMeansBenchmark.track_train_score.json index 9aa1365b2c..9f41bf7635 100644 --- a/graphs/summary/cluster.KMeansBenchmark.track_train_score.json +++ b/graphs/summary/cluster.KMeansBenchmark.track_train_score.json @@ -1 +1 @@ -[[28511, -1.9085452144895736], [29225, -1.9085452144895736], [29239, -1.9085452273569807], [29253, -1.908545240415206], [29267, -1.908545222531703], [29281, -1.9085451688811972], [29295, -1.9085452969088401], [29309, -1.908545222531703], [29323, -1.9085452339337978], [29337, -1.9085451894454089], [29351, -1.9085451840839893], [29365, -1.9085452144895736], [29379, -1.9085452144895736], [29393, -1.9085452404152052], [29407, -1.908545222531703], [29421, -1.9085452877061178], [29435, -1.9085452198509936], [29449, -1.908545225212413], [29463, -1.90854520858475], [29477, -1.9085452144895736], [29547, -1.9085451688811972], [29561, -1.9085452609794176], [29575, -1.9085452305738322], [29603, -1.9085452533780212], [29617, -1.9085452225317037], [29631, -1.9085452144895736], [29645, -1.9085452144895736], [29659, -1.9085452111296088], [29673, -1.9085452457766248], [29743, -1.9085452453358918], [29757, -1.9085452225317037], [29771, -1.9085452273569807], [29785, -1.908545222531703], [29799, -1.9085452332618047], [29813, -1.908545211129609], [29827, -1.9085452144895736], [29841, -1.9085451916853855], [29855, -1.9085452144895736], [29869, -1.9085451688811972], [30009, -1.9085452144895736], [30023, -1.9085451688811972], [30037, -1.9085452609794176], [30051, -1.9085450776644337], [30065, -1.9085452144895736], [30079, -1.9085452037563602], [30093, -1.9085452453358918], [30107, -1.9085451840839893], [30121, -1.9085451992867817], [30135, -1.9085452225317037], [30149, -1.9085452339337978], [30163, -1.9085452404152055], [30177, -1.9085451313149286], [30191, -1.908545226222218], [30205, -1.9085452404152055], [30219, -1.9085452040239115], [30233, -1.908545260759051], [30247, -1.9085452148201238], [30261, -1.9085452303041857], [30513, -1.9085452085847503], [30527, -1.908545201071498], [30541, -1.9085452149303066], [30555, -1.9085452160502954], [30569, -1.9085452071085443], [30583, -1.9085452379548622], [30597, -1.9085452030874794], [30625, -1.9085452350537857], [30639, -1.9085452379548622], [30653, -1.9085451981667925], [30667, -1.9085451802832911], [30681, -1.9085452301330996], [30695, -1.908545168881197], [30709, -1.908545134674909], [30723, -1.9085451769233195], [30737, -1.9085452131401397], [30751, -1.908545226283123], [30765, -1.9085452225317028], [30779, -1.908545222531703], [30793, -1.9085452328138093], [30807, -1.9085451843043555], [30821, -1.908545222531703], [30835, -1.9085451232728152], [30849, -1.908545222531703], [30863, -1.9085452339337974], [30877, -1.9085452379548622], [30891, -1.9085451916853853], [30905, -1.9085452144895738], [30919, -1.9085452301330994], [30933, -1.9085452299127328], [30947, -1.9085452185106386], [30961, -1.9085451970468028], [30975, -1.908545192346478], [30989, -1.9085452225317028], [31003, -1.9085452533780214], [31017, -1.908545199727514], [31031, -1.908545222531703], [31045, -1.908545220521171], [32109, -1.9085452265527674], [32123, -1.9085452339337978], [32137, -1.9085452046482008], [32151, -1.9085452071085443], [32165, -1.9085452323147183], [32179, -1.9085452761822104], [32193, -1.9085451894454044], [32207, -1.9085452205211706], [32221, -1.9085452533780212], [32235, -1.9085452453358918], [32249, -1.9085451916853853], [32263, -1.9085452225317028], [32277, -1.9085452149303048], [32305, -1.9085452019674911], [32319, -1.9085452328138093], [32333, -1.908545222531703], [32347, -1.9085452339337976], [32361, -1.9085452302432828], [32375, -1.9085452453358918], [32389, -1.9085451957064499], [32403, -1.9085451916853853], [32417, -1.9085452633006017], [32431, -1.908545188325414], [32445, -1.908545222531703], [32571, -1.908545168881197], [32585, -1.9085451970468046], [32599, -1.9085452149303066], [32613, -1.9085452149303068], [32627, -1.9085452144895738], [32641, -1.9085452339337976], [32655, -1.9085452404152055], [32851, -1.9085452225317032], [32865, -1.9085452379548622], [32879, -1.9085452404152055], [32893, -1.9085452453358918], [32907, -1.9085452149303073], [32921, -1.9085452493569566], [32991, -1.908545222531703], [33005, -1.9085452453358918], [33019, -1.908545199727514], [33033, -1.9085453031292743], [33047, -1.9085452761822104], [33061, -1.859740438826365], [33075, -1.8109356551210267], [33089, -1.810935655121027], [33103, -1.810935666812626], [33117, -1.8109356463523278], [33131, -1.810935663889726], [33145, -1.8109356726584251], [33159, -1.8109356726584251], [33187, -1.810935655121027], [33201, -1.810935663889726], [33215, -1.8109472090437435], [33229, -1.8109818324494218], [33243, -1.8109818379306688], [33271, -1.8110279999961023], [33299, -1.8110279824613869], [33313, -1.8110279912287446], [33327, -1.8110279912287446], [33341, -1.8110279956124233], [33355, -1.8110280058410078], [33369, -1.811027988306292], [33383, -1.811027994151197], [33397, -1.8110280087634603], [33411, -1.8110279824613869], [33425, -1.8110279824613869], [33439, -1.8110279912287446], [33453, -1.8110279999961025], [33467, -1.8110279999961023], [33523, -1.8110279956124236], [33537, -1.8110279999961028], [33551, -1.8110279941511973], [33649, -1.8110279824613869], [33705, -1.8110280175308182], [33719, -1.8110279912287446], [33733, -1.8110279824613869], [33747, -1.8110279912287446], [33761, -1.8110279999961025], [33775, -1.8110279824613869], [33803, -1.8110279999961025], [33817, -1.8110279999961025], [33831, -1.8110279785508319], [33845, -1.8110279824613869], [34041, -1.8110279999961025], [34055, -1.8110280058410078], [34069, -1.8110279941511973], [34083, -1.8110279912287446], [34125, -1.8110279873390969], [34139, -1.8110279999961023], [34153, -1.811027994151197], [34167, -1.8110280087634603]] \ No newline at end of file +[[28511, -1.9085452144895736], [29225, -1.9085452144895736], [29239, -1.9085452273569807], [29253, -1.908545240415206], [29267, -1.908545222531703], [29281, -1.9085451688811972], [29295, -1.9085452969088401], [29309, -1.908545222531703], [29323, -1.9085452339337978], [29337, -1.9085451894454089], [29351, -1.9085451840839893], [29365, -1.9085452144895736], [29379, -1.9085452144895736], [29393, -1.9085452404152052], [29407, -1.908545222531703], [29421, -1.9085452877061178], [29435, -1.9085452198509936], [29449, -1.908545225212413], [29463, -1.90854520858475], [29477, -1.9085452144895736], [29547, -1.9085451688811972], [29561, -1.9085452609794176], [29575, -1.9085452305738322], [29603, -1.9085452533780212], [29617, -1.9085452225317037], [29631, -1.9085452144895736], [29645, -1.9085452144895736], [29659, -1.9085452111296088], [29673, -1.9085452457766248], [29743, -1.9085452453358918], [29757, -1.9085452225317037], [29771, -1.9085452273569807], [29785, -1.908545222531703], [29799, -1.9085452332618047], [29813, -1.908545211129609], [29827, -1.9085452144895736], [29841, -1.9085451916853855], [29855, -1.9085452144895736], [29869, -1.9085451688811972], [30009, -1.9085452144895736], [30023, -1.9085451688811972], [30037, -1.9085452609794176], [30051, -1.9085450776644337], [30065, -1.9085452144895736], [30079, -1.9085452037563602], [30093, -1.9085452453358918], [30107, -1.9085451840839893], [30121, -1.9085451992867817], [30135, -1.9085452225317037], [30149, -1.9085452339337978], [30163, -1.9085452404152055], [30177, -1.9085451313149286], [30191, -1.908545226222218], [30205, -1.9085452404152055], [30219, -1.9085452040239115], [30233, -1.908545260759051], [30247, -1.9085452148201238], [30261, -1.9085452303041857], [30513, -1.9085452085847503], [30527, -1.908545201071498], [30541, -1.9085452149303066], [30555, -1.9085452160502954], [30569, -1.9085452071085443], [30583, -1.9085452379548622], [30597, -1.9085452030874794], [30625, -1.9085452350537857], [30639, -1.9085452379548622], [30653, -1.9085451981667925], [30667, -1.9085451802832911], [30681, -1.9085452301330996], [30695, -1.908545168881197], [30709, -1.908545134674909], [30723, -1.9085451769233195], [30737, -1.9085452131401397], [30751, -1.908545226283123], [30765, -1.9085452225317028], [30779, -1.908545222531703], [30793, -1.9085452328138093], [30807, -1.9085451843043555], [30821, -1.908545222531703], [30835, -1.9085451232728152], [30849, -1.908545222531703], [30863, -1.9085452339337974], [30877, -1.9085452379548622], [30891, -1.9085451916853853], [30905, -1.9085452144895738], [30919, -1.9085452301330994], [30933, -1.9085452299127328], [30947, -1.9085452185106386], [30961, -1.9085451970468028], [30975, -1.908545192346478], [30989, -1.9085452225317028], [31003, -1.9085452533780214], [31017, -1.908545199727514], [31031, -1.908545222531703], [31045, -1.908545220521171], [32109, -1.9085452265527674], [32123, -1.9085452339337978], [32137, -1.9085452046482008], [32151, -1.9085452071085443], [32165, -1.9085452323147183], [32179, -1.9085452761822104], [32193, -1.9085451894454044], [32207, -1.9085452205211706], [32221, -1.9085452533780212], [32235, -1.9085452453358918], [32249, -1.9085451916853853], [32263, -1.9085452225317028], [32277, -1.9085452149303048], [32305, -1.9085452019674911], [32319, -1.9085452328138093], [32333, -1.908545222531703], [32347, -1.9085452339337976], [32361, -1.9085452302432828], [32375, -1.9085452453358918], [32389, -1.9085451957064499], [32403, -1.9085451916853853], [32417, -1.9085452633006017], [32431, -1.908545188325414], [32445, -1.908545222531703], [32571, -1.908545168881197], [32585, -1.9085451970468046], [32599, -1.9085452149303066], [32613, -1.9085452149303068], [32627, -1.9085452144895738], [32641, -1.9085452339337976], [32655, -1.9085452404152055], [32851, -1.9085452225317032], [32865, -1.9085452379548622], [32879, -1.9085452404152055], [32893, -1.9085452453358918], [32907, -1.9085452149303073], [32921, -1.9085452493569566], [32991, -1.908545222531703], [33005, -1.9085452453358918], [33019, -1.908545199727514], [33033, -1.9085453031292743], [33047, -1.9085452761822104], [33061, -1.859740438826365], [33075, -1.8109356551210267], [33089, -1.810935655121027], [33103, -1.810935666812626], [33117, -1.8109356463523278], [33131, -1.810935663889726], [33145, -1.8109356726584251], [33159, -1.8109356726584251], [33187, -1.810935655121027], [33201, -1.810935663889726], [33215, -1.8109472090437435], [33229, -1.8109818324494218], [33243, -1.8109818379306688], [33271, -1.8110279999961023], [33299, -1.8110279824613869], [33313, -1.8110279912287446], [33327, -1.8110279912287446], [33341, -1.8110279956124233], [33355, -1.8110280058410078], [33369, -1.811027988306292], [33383, -1.811027994151197], [33397, -1.8110280087634603], [33411, -1.8110279824613869], [33425, -1.8110279824613869], [33439, -1.8110279912287446], [33453, -1.8110279999961025], [33467, -1.8110279999961023], [33523, -1.8110279956124236], [33537, -1.8110279999961028], [33551, -1.8110279941511973], [33649, -1.8110279824613869], [33705, -1.8110280175308182], [33719, -1.8110279912287446], [33733, -1.8110279824613869], [33747, -1.8110279912287446], [33761, -1.8110279999961025], [33775, -1.8110279824613869], [33803, -1.8110279999961025], [33817, -1.8110279999961025], [33831, -1.8110279785508319], [33845, -1.8110279824613869], [34041, -1.8110279999961025], [34055, -1.8110280058410078], [34069, -1.8110279941511973], [34083, -1.8110279912287446], [34125, -1.8110279873390969], [34139, -1.8110279999961023], [34153, -1.811027994151197], [34167, -1.8110280035030457]] \ No newline at end of file diff --git a/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json b/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json index 7b772516eb..3cddda26f8 100644 --- a/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json +++ b/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 116020284.71364021], [29225, 122814825.29751827], [29239, 123172752.56147626], [29253, 122814476.3973601], [29267, 122782320.42129979], [29281, 123119565.67536525], [29295, 123123518.56851077], [29309, 122926693.13140112], [29323, 122794083.76598373], [29337, 123358646.64485614], [29351, 122272242.1574893], [29365, 121877367.6336086], [29379, 122177960.27409059], [29393, 122198825.65576279], [29407, 122179174.15551272], [29421, 122256190.24178688], [29435, 122811545.20615695], [29449, 122655782.89958005], [29463, 122740927.36847094], [29477, 122779756.41361399], [29547, 122805546.22547108], [29561, 122679516.84807748], [29575, 122705631.1204809], [29603, 123873821.6051448], [29617, 124061803.05089673], [29631, 124143275.6941465], [29645, 124364386.66148055], [29659, 124243600.30127129], [29673, 123900644.66051686], [29743, 124030071.87431386], [29757, 124343746.34124073], [29771, 124049029.94836554], [29785, 124030449.67960696], [29799, 123877616.38369076], [29813, 124146034.7227544], [29827, 124386952.45694183], [29841, 124490095.70429964], [29855, 124122248.25266817], [29869, 124492007.41300946], [30009, 124441216.17709251], [30023, 124187963.5218087], [30037, 124234948.81180374], [30051, 124000518.8719675], [30065, 123523534.4744294], [30079, 124107967.66060996], [30093, 123979529.77932864], [30107, 124271736.79909424], [30121, 124245084.14796495], [30135, 124108333.90356624], [30149, 124445524.9790462], [30163, 124664615.65791899], [30177, 124600905.16630043], [30191, 124601897.90556043], [30205, 124759399.48133682], [30219, 124774876.50184138], [30233, 124423800.09395893], [30247, 124468567.24362233], [30261, 124320851.97959177], [30513, 124856624.4922446], [30527, 124398452.1686498], [30541, 124204739.34345494], [30555, 124291808.77281444], [30569, 123913768.13963151], [30583, 124338707.57965195], [30597, 124328566.76544648], [30625, 124397876.28358053], [30639, 124852951.95643535], [30653, 124374305.89885204], [30667, 124490284.12170497], [30681, 124379054.05390535], [30695, 124748323.06545661], [30709, 124337802.46842545], [30723, 124551576.61882608], [30737, 124293865.4386621], [30751, 124333763.06321365], [30765, 124955247.05382979], [30779, 124040440.12309715], [30793, 124635855.93679301], [30807, 124146091.00037512], [30821, 124896310.61826755], [30835, 124588183.72210254], [30849, 124485767.48655933], [30863, 124477219.50198546], [30877, 124749956.5060558], [30891, 124803508.28529404], [30905, 124574215.9889211], [30919, 124507393.37519842], [30933, 124421870.38518858], [30947, 124685188.32566291], [30961, 124446696.08681107], [30975, 124757010.14574519], [30989, 124522588.28228109], [31003, 124728294.97057286], [31017, 124635760.80616859], [31031, 124243191.7567655], [31045, 124499494.37761706], [32095, 137281265.6941088], [32109, 137121570.48806357], [32123, 136902186.76497078], [32137, 137139195.96018842], [32151, 136963266.22517872], [32165, 137095125.6252002], [32179, 136903176.19611922], [32193, 137197898.0329809], [32207, 138254975.82455778], [32221, 139788403.54995427], [32235, 140183710.02892935], [32249, 139708421.0678039], [32263, 139730938.20244437], [32277, 139639940.66182774], [32305, 141162476.07235083], [32319, 143727930.34112683], [32333, 144136440.91528746], [32347, 143789573.06160444], [32361, 143951431.0061637], [32375, 143959855.40357244], [32389, 143813642.6382227], [32403, 143600574.62760478], [32417, 144227238.32384324], [32431, 143999792.83135295], [32445, 144520231.43359062], [32571, 143807158.51718038], [32585, 143477732.97993124], [32599, 143131670.79206488], [32613, 143204807.8561863], [32627, 144022884.9049899], [32641, 143211975.41543314], [32655, 143511519.05314216], [32851, 144241813.43174675], [32865, 144257482.36497787], [32879, 144630864.7973417], [32893, 144680284.27666286], [32907, 144567726.4479386], [32921, 144253914.19480342], [32991, 144436793.82433638], [33005, 144016105.1216285], [33019, 144074831.23588297], [33033, 143886762.7437048], [33047, 144068952.48188707], [33061, 144853433.97358763], [33075, 144821043.12664062], [33089, 160161335.36778948], [33103, 175082072.6707502], [33117, 175473134.27140695], [33131, 175241033.726546], [33145, 175278629.24905667], [33159, 175237273.6174968], [33187, 145009671.66222608], [33201, 145155143.05583262], [33215, 143223996.24503648], [33229, 137643680.9035939], [33243, 137460638.16190794], [33271, 129993344.15043472], [33285, 130676272.54044114], [33299, 130229450.811125], [33313, 129295459.68516983], [33327, 130762711.93085013], [33341, 130741415.64570633], [33355, 130872256.43941729], [33369, 131228010.25267625], [33383, 131517685.7797256], [33397, 131966740.61930372], [33411, 131923868.54917994], [33425, 132040897.34636247], [33439, 133350080.70458099], [33453, 128275820.07870372], [33467, 127983851.2900168], [33523, 128123609.47189155], [33537, 128113159.9410761], [33551, 127465426.83029126], [33649, 127025348.37266289], [33705, 126573104.93919267], [33719, 126577974.48109981], [33733, 126690715.74264716], [33747, 126653480.96661645], [33761, 126421063.1022701], [33775, 126590931.98248875], [33803, 126714089.70844404], [33817, 126325602.14655098], [33831, 126337794.48836775], [33845, 125997973.646327], [34041, 126300655.9982802], [34055, 126525086.63319367], [34069, 126545119.64095068], [34083, 126232361.28406511], [34125, 126390362.40690891], [34139, 126856585.7816898], [34153, 126288944.5948938], [34167, 126194785.45206954]] \ No newline at end of file +[[28511, 116020284.71364021], [29225, 122814825.29751827], [29239, 123172752.56147626], [29253, 122814476.3973601], [29267, 122782320.42129979], [29281, 123119565.67536525], [29295, 123123518.56851077], [29309, 122926693.13140112], [29323, 122794083.76598373], [29337, 123358646.64485614], [29351, 122272242.1574893], [29365, 121877367.6336086], [29379, 122177960.27409059], [29393, 122198825.65576279], [29407, 122179174.15551272], [29421, 122256190.24178688], [29435, 122811545.20615695], [29449, 122655782.89958005], [29463, 122740927.36847094], [29477, 122779756.41361399], [29547, 122805546.22547108], [29561, 122679516.84807748], [29575, 122705631.1204809], [29603, 123873821.6051448], [29617, 124061803.05089673], [29631, 124143275.6941465], [29645, 124364386.66148055], [29659, 124243600.30127129], [29673, 123900644.66051686], [29743, 124030071.87431386], [29757, 124343746.34124073], [29771, 124049029.94836554], [29785, 124030449.67960696], [29799, 123877616.38369076], [29813, 124146034.7227544], [29827, 124386952.45694183], [29841, 124490095.70429964], [29855, 124122248.25266817], [29869, 124492007.41300946], [30009, 124441216.17709251], [30023, 124187963.5218087], [30037, 124234948.81180374], [30051, 124000518.8719675], [30065, 123523534.4744294], [30079, 124107967.66060996], [30093, 123979529.77932864], [30107, 124271736.79909424], [30121, 124245084.14796495], [30135, 124108333.90356624], [30149, 124445524.9790462], [30163, 124664615.65791899], [30177, 124600905.16630043], [30191, 124601897.90556043], [30205, 124759399.48133682], [30219, 124774876.50184138], [30233, 124423800.09395893], [30247, 124468567.24362233], [30261, 124320851.97959177], [30513, 124856624.4922446], [30527, 124398452.1686498], [30541, 124204739.34345494], [30555, 124291808.77281444], [30569, 123913768.13963151], [30583, 124338707.57965195], [30597, 124328566.76544648], [30625, 124397876.28358053], [30639, 124852951.95643535], [30653, 124374305.89885204], [30667, 124490284.12170497], [30681, 124379054.05390535], [30695, 124748323.06545661], [30709, 124337802.46842545], [30723, 124551576.61882608], [30737, 124293865.4386621], [30751, 124333763.06321365], [30765, 124955247.05382979], [30779, 124040440.12309715], [30793, 124635855.93679301], [30807, 124146091.00037512], [30821, 124896310.61826755], [30835, 124588183.72210254], [30849, 124485767.48655933], [30863, 124477219.50198546], [30877, 124749956.5060558], [30891, 124803508.28529404], [30905, 124574215.9889211], [30919, 124507393.37519842], [30933, 124421870.38518858], [30947, 124685188.32566291], [30961, 124446696.08681107], [30975, 124757010.14574519], [30989, 124522588.28228109], [31003, 124728294.97057286], [31017, 124635760.80616859], [31031, 124243191.7567655], [31045, 124499494.37761706], [32095, 137281265.6941088], [32109, 137121570.48806357], [32123, 136902186.76497078], [32137, 137139195.96018842], [32151, 136963266.22517872], [32165, 137095125.6252002], [32179, 136903176.19611922], [32193, 137197898.0329809], [32207, 138254975.82455778], [32221, 139788403.54995427], [32235, 140183710.02892935], [32249, 139708421.0678039], [32263, 139730938.20244437], [32277, 139639940.66182774], [32305, 141162476.07235083], [32319, 143727930.34112683], [32333, 144136440.91528746], [32347, 143789573.06160444], [32361, 143951431.0061637], [32375, 143959855.40357244], [32389, 143813642.6382227], [32403, 143600574.62760478], [32417, 144227238.32384324], [32431, 143999792.83135295], [32445, 144520231.43359062], [32571, 143807158.51718038], [32585, 143477732.97993124], [32599, 143131670.79206488], [32613, 143204807.8561863], [32627, 144022884.9049899], [32641, 143211975.41543314], [32655, 143511519.05314216], [32851, 144241813.43174675], [32865, 144257482.36497787], [32879, 144630864.7973417], [32893, 144680284.27666286], [32907, 144567726.4479386], [32921, 144253914.19480342], [32991, 144436793.82433638], [33005, 144016105.1216285], [33019, 144074831.23588297], [33033, 143886762.7437048], [33047, 144068952.48188707], [33061, 144853433.97358763], [33075, 144821043.12664062], [33089, 160161335.36778948], [33103, 175082072.6707502], [33117, 175473134.27140695], [33131, 175241033.726546], [33145, 175278629.24905667], [33159, 175237273.6174968], [33187, 145009671.66222608], [33201, 145155143.05583262], [33215, 143223996.24503648], [33229, 137643680.9035939], [33243, 137460638.16190794], [33271, 129993344.15043472], [33285, 130676272.54044114], [33299, 130229450.811125], [33313, 129295459.68516983], [33327, 130762711.93085013], [33341, 130741415.64570633], [33355, 130872256.43941729], [33369, 131228010.25267625], [33383, 131517685.7797256], [33397, 131966740.61930372], [33411, 131923868.54917994], [33425, 132040897.34636247], [33439, 133350080.70458099], [33453, 128275820.07870372], [33467, 127983851.2900168], [33523, 128123609.47189155], [33537, 128113159.9410761], [33551, 127465426.83029126], [33649, 127025348.37266289], [33705, 126573104.93919267], [33719, 126577974.48109981], [33733, 126690715.74264716], [33747, 126653480.96661645], [33761, 126421063.1022701], [33775, 126590931.98248875], [33803, 126714089.70844404], [33817, 126325602.14655098], [33831, 126337794.48836775], [33845, 125997973.646327], [34041, 126300655.9982802], [34055, 126525086.63319367], [34069, 126545119.64095068], [34083, 126232361.28406511], [34125, 126390362.40690891], [34139, 126856585.7816898], [34153, 126288944.5948938], [34167, 126177032.68279915]] \ No newline at end of file diff --git a/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json b/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json index 25dca3bc59..9f0395f650 100644 --- a/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json +++ b/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28511, 115572133.71767321], [29225, 93833570.25273748], [29239, 94071593.81694934], [29253, 93980271.35310566], [29267, 93996665.03412965], [29281, 94212448.32696804], [29295, 94070135.47346471], [29309, 94074468.91000298], [29323, 94106713.25394443], [29337, 94439481.00965126], [29351, 93555170.66490458], [29365, 93216139.86535886], [29379, 93489237.71745858], [29393, 93415077.24480808], [29407, 93408956.39852953], [29421, 93360208.56772739], [29435, 93699128.20365912], [29449, 93998558.25984459], [29463, 93958290.22230259], [29477, 94174985.39100602], [29547, 93894171.11181729], [29561, 94393315.15181671], [29575, 93624409.40814072], [29603, 94484031.27198437], [29617, 94510324.37484266], [29631, 94799903.78202276], [29645, 94728245.27094628], [29659, 94631915.16799833], [29673, 94531867.2598716], [29743, 94466325.39816076], [29757, 94660131.93272841], [29771, 94587479.21032321], [29785, 94820098.76793557], [29799, 94569020.65655315], [29813, 94607641.74719177], [29827, 94762290.84208098], [29841, 94769933.93973564], [29855, 95182151.95419821], [29869, 94799062.21137759], [30009, 94600611.48932135], [30023, 94586613.4477444], [30037, 94512355.43658686], [30051, 94602492.84224729], [30065, 94303206.99129109], [30079, 94795682.70714357], [30093, 94558809.10236578], [30107, 94987857.35243504], [30121, 94607430.47511579], [30135, 94545761.33787945], [30149, 95332157.32259493], [30163, 95039340.0422396], [30177, 95157852.52967152], [30191, 95176628.38025872], [30205, 95246473.66613317], [30219, 95211006.80457799], [30233, 94780622.66699623], [30247, 95327664.93644011], [30261, 94813871.85275644], [30513, 95224706.80350989], [30527, 95077386.02837612], [30541, 94844918.17303431], [30555, 94940880.9239465], [30569, 94980002.9054957], [30583, 95175593.1479392], [30597, 94725417.5017794], [30625, 95043733.31430233], [30639, 95149422.70097584], [30653, 94955364.02450442], [30667, 95449033.48249465], [30681, 94946902.06163657], [30695, 94974379.40542981], [30709, 94862219.40272538], [30723, 94732958.85753468], [30737, 95314693.83290501], [30751, 95057934.0296508], [30765, 95834309.93722856], [30779, 94614455.69147752], [30793, 95133173.41154547], [30807, 95088486.81160685], [30821, 95463055.1592159], [30835, 95296318.49953935], [30849, 96091835.25264817], [30863, 95126287.0773332], [30877, 95121874.0301409], [30891, 95237486.7973319], [30905, 95074793.13559201], [30919, 95365228.64672469], [30933, 95024516.01297453], [30947, 94944256.80612528], [30961, 95355716.6750765], [30975, 95171539.02155595], [30989, 95051747.97294617], [31003, 95393686.50873381], [31017, 95774105.33751135], [31031, 95022844.72226363], [31045, 95319624.54193437], [32095, 105692276.9723731], [32109, 105771043.26778753], [32123, 105594565.54995848], [32137, 105639673.64384313], [32151, 105507636.54464462], [32165, 105562375.97668092], [32179, 105322534.84775761], [32193, 105635878.33428133], [32207, 107165613.51793769], [32221, 108684499.67364149], [32235, 108382119.43686032], [32249, 108138378.16682342], [32263, 108215381.78644459], [32277, 108148950.80030008], [32305, 109202369.44795257], [32319, 111369083.72755533], [32333, 111440792.68160866], [32347, 111419147.80085514], [32361, 111446644.91282481], [32375, 111471927.7316947], [32389, 111384309.1873119], [32403, 111309884.85064708], [32417, 111378905.61099686], [32431, 111693047.25276671], [32445, 111573236.93344873], [32571, 111562258.66528216], [32585, 111604698.27702172], [32599, 111655466.85026294], [32613, 111664238.46912761], [32627, 111936465.28490631], [32641, 111551706.05353697], [32655, 111549904.549455], [32851, 112495701.87394361], [32865, 112516090.89833301], [32879, 112654036.77919386], [32893, 112768621.27317953], [32907, 112622318.68591122], [32921, 112555875.76977849], [32991, 112611445.0263823], [33005, 112486112.22488973], [33019, 112233632.8784008], [33033, 112436910.55689299], [33047, 112707223.07910158], [33061, 112823736.38666442], [33075, 112631474.03950778], [33089, 127351419.94542398], [33103, 142084667.85073876], [33117, 142242281.5919716], [33131, 142055664.02042735], [33145, 142104906.02846944], [33159, 142412127.79547158], [33187, 113364911.1303102], [33201, 113022704.33994403], [33215, 111035557.75351232], [33229, 105716470.75875734], [33243, 105730801.13065717], [33271, 98989888.80089118], [33285, 99080869.00809282], [33299, 99114194.94298652], [33313, 98205462.91679728], [33327, 99621034.89535578], [33341, 99576657.28600977], [33355, 99665931.40935971], [33369, 100195497.28341238], [33383, 100451225.73533213], [33397, 100712246.6184651], [33411, 100884425.24525532], [33425, 100655393.27309269], [33439, 101928049.10671347], [33453, 96957314.6147201], [33467, 96875050.90749216], [33523, 97114426.92153683], [33537, 97113205.5359128], [33551, 96460820.47934373], [33649, 96188955.7417941], [33705, 95479532.01753297], [33719, 95587511.26165302], [33733, 95908963.15580858], [33747, 95527538.1941467], [33761, 95738903.26035328], [33775, 95484417.79268458], [33803, 95778125.36984037], [33817, 95472281.40042296], [33831, 95617319.39976661], [33845, 95355351.88336848], [34041, 95193774.52835628], [34055, 95553221.84622501], [34069, 95619045.00201999], [34083, 95112913.49185458], [34125, 95393496.0541721], [34139, 95908502.54735915], [34153, 95390260.61304843], [34167, 95356829.47139952]] \ No newline at end of file +[[28511, 115572133.71767321], [29225, 93833570.25273748], [29239, 94071593.81694934], [29253, 93980271.35310566], [29267, 93996665.03412965], [29281, 94212448.32696804], [29295, 94070135.47346471], [29309, 94074468.91000298], [29323, 94106713.25394443], [29337, 94439481.00965126], [29351, 93555170.66490458], [29365, 93216139.86535886], [29379, 93489237.71745858], [29393, 93415077.24480808], [29407, 93408956.39852953], [29421, 93360208.56772739], [29435, 93699128.20365912], [29449, 93998558.25984459], [29463, 93958290.22230259], [29477, 94174985.39100602], [29547, 93894171.11181729], [29561, 94393315.15181671], [29575, 93624409.40814072], [29603, 94484031.27198437], [29617, 94510324.37484266], [29631, 94799903.78202276], [29645, 94728245.27094628], [29659, 94631915.16799833], [29673, 94531867.2598716], [29743, 94466325.39816076], [29757, 94660131.93272841], [29771, 94587479.21032321], [29785, 94820098.76793557], [29799, 94569020.65655315], [29813, 94607641.74719177], [29827, 94762290.84208098], [29841, 94769933.93973564], [29855, 95182151.95419821], [29869, 94799062.21137759], [30009, 94600611.48932135], [30023, 94586613.4477444], [30037, 94512355.43658686], [30051, 94602492.84224729], [30065, 94303206.99129109], [30079, 94795682.70714357], [30093, 94558809.10236578], [30107, 94987857.35243504], [30121, 94607430.47511579], [30135, 94545761.33787945], [30149, 95332157.32259493], [30163, 95039340.0422396], [30177, 95157852.52967152], [30191, 95176628.38025872], [30205, 95246473.66613317], [30219, 95211006.80457799], [30233, 94780622.66699623], [30247, 95327664.93644011], [30261, 94813871.85275644], [30513, 95224706.80350989], [30527, 95077386.02837612], [30541, 94844918.17303431], [30555, 94940880.9239465], [30569, 94980002.9054957], [30583, 95175593.1479392], [30597, 94725417.5017794], [30625, 95043733.31430233], [30639, 95149422.70097584], [30653, 94955364.02450442], [30667, 95449033.48249465], [30681, 94946902.06163657], [30695, 94974379.40542981], [30709, 94862219.40272538], [30723, 94732958.85753468], [30737, 95314693.83290501], [30751, 95057934.0296508], [30765, 95834309.93722856], [30779, 94614455.69147752], [30793, 95133173.41154547], [30807, 95088486.81160685], [30821, 95463055.1592159], [30835, 95296318.49953935], [30849, 96091835.25264817], [30863, 95126287.0773332], [30877, 95121874.0301409], [30891, 95237486.7973319], [30905, 95074793.13559201], [30919, 95365228.64672469], [30933, 95024516.01297453], [30947, 94944256.80612528], [30961, 95355716.6750765], [30975, 95171539.02155595], [30989, 95051747.97294617], [31003, 95393686.50873381], [31017, 95774105.33751135], [31031, 95022844.72226363], [31045, 95319624.54193437], [32095, 105692276.9723731], [32109, 105771043.26778753], [32123, 105594565.54995848], [32137, 105639673.64384313], [32151, 105507636.54464462], [32165, 105562375.97668092], [32179, 105322534.84775761], [32193, 105635878.33428133], [32207, 107165613.51793769], [32221, 108684499.67364149], [32235, 108382119.43686032], [32249, 108138378.16682342], [32263, 108215381.78644459], [32277, 108148950.80030008], [32305, 109202369.44795257], [32319, 111369083.72755533], [32333, 111440792.68160866], [32347, 111419147.80085514], [32361, 111446644.91282481], [32375, 111471927.7316947], [32389, 111384309.1873119], [32403, 111309884.85064708], [32417, 111378905.61099686], [32431, 111693047.25276671], [32445, 111573236.93344873], [32571, 111562258.66528216], [32585, 111604698.27702172], [32599, 111655466.85026294], [32613, 111664238.46912761], [32627, 111936465.28490631], [32641, 111551706.05353697], [32655, 111549904.549455], [32851, 112495701.87394361], [32865, 112516090.89833301], [32879, 112654036.77919386], [32893, 112768621.27317953], [32907, 112622318.68591122], [32921, 112555875.76977849], [32991, 112611445.0263823], [33005, 112486112.22488973], [33019, 112233632.8784008], [33033, 112436910.55689299], [33047, 112707223.07910158], [33061, 112823736.38666442], [33075, 112631474.03950778], [33089, 127351419.94542398], [33103, 142084667.85073876], [33117, 142242281.5919716], [33131, 142055664.02042735], [33145, 142104906.02846944], [33159, 142412127.79547158], [33187, 113364911.1303102], [33201, 113022704.33994403], [33215, 111035557.75351232], [33229, 105716470.75875734], [33243, 105730801.13065717], [33271, 98989888.80089118], [33285, 99080869.00809282], [33299, 99114194.94298652], [33313, 98205462.91679728], [33327, 99621034.89535578], [33341, 99576657.28600977], [33355, 99665931.40935971], [33369, 100195497.28341238], [33383, 100451225.73533213], [33397, 100712246.6184651], [33411, 100884425.24525532], [33425, 100655393.27309269], [33439, 101928049.10671347], [33453, 96957314.6147201], [33467, 96875050.90749216], [33523, 97114426.92153683], [33537, 97113205.5359128], [33551, 96460820.47934373], [33649, 96188955.7417941], [33705, 95479532.01753297], [33719, 95587511.26165302], [33733, 95908963.15580858], [33747, 95527538.1941467], [33761, 95738903.26035328], [33775, 95484417.79268458], [33803, 95778125.36984037], [33817, 95472281.40042296], [33831, 95617319.39976661], [33845, 95355351.88336848], [34041, 95193774.52835628], [34055, 95553221.84622501], [34069, 95619045.00201999], [34083, 95112913.49185458], [34125, 95393496.0541721], [34139, 95908502.54735915], [34153, 95390260.61304843], [34167, 95348677.76667897]] \ No newline at end of file diff --git a/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json b/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json index f51e61ad4d..155ce4b72d 100644 --- a/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json +++ b/graphs/summary/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json @@ -1 +1 @@ -[[28511, 119392618.44421901], [29225, 116847664.4262998], [29239, 116826689.42662717], [29253, 116759580.73119773], [29267, 116763135.20443648], [29281, 116896170.2669805], [29295, 116919775.80293305], [29309, 116794281.72384158], [29323, 116842945.38822782], [29337, 117265724.45989524], [29351, 116356229.01020575], [29365, 116326350.69920829], [29379, 116673325.87150455], [29393, 116558361.90437062], [29407, 116610686.81119043], [29421, 116523897.0545817], [29435, 116991177.61676168], [29449, 117019651.35965978], [29463, 116865813.4737947], [29477, 116868793.57914206], [29547, 116977317.56270702], [29561, 117106979.00101425], [29575, 116502561.1904805], [29603, 117743020.55062744], [29617, 117698605.41927937], [29631, 117893757.49124242], [29645, 117932272.22659096], [29659, 117838195.17010781], [29673, 117758569.52398534], [29743, 117750396.37051326], [29757, 117873590.61693758], [29771, 117759083.52484651], [29785, 117975086.52539599], [29799, 117883840.34427378], [29813, 117986880.14426863], [29827, 118099901.87072596], [29841, 117970135.57517841], [29855, 117933511.43854968], [29869, 118014999.49777295], [30009, 117968393.81353995], [30023, 118052493.71548024], [30037, 117919408.91932766], [30051, 117762184.2432193], [30065, 117958844.00964232], [30079, 117981719.25924785], [30093, 117854092.86249447], [30107, 117818378.14924566], [30121, 118000684.59192717], [30135, 117967832.03870371], [30149, 118295531.02411285], [30163, 118323374.76663911], [30177, 118541355.93026629], [30191, 118506003.8156645], [30205, 118424636.12644787], [30219, 118444027.25385804], [30233, 118282625.57381469], [30247, 118481309.16382524], [30261, 118219474.34622404], [30513, 118566140.11441322], [30527, 118361357.08959743], [30541, 118305259.45050573], [30555, 118243678.91650288], [30569, 118145625.27963275], [30583, 118454542.17631716], [30597, 118189733.90003695], [30625, 118236149.54244089], [30639, 118266595.96966082], [30653, 118182624.62583087], [30667, 118308584.49927595], [30681, 118334692.03638677], [30695, 118432616.2065056], [30709, 118340255.0364696], [30723, 118337834.50531733], [30737, 118355143.43890887], [30751, 118436786.25424981], [30765, 118789454.36051686], [30779, 118307814.45298098], [30793, 118361131.37376238], [30807, 118286858.86482021], [30821, 118496135.02017784], [30835, 118752145.83696799], [30849, 118469279.88958254], [30863, 118381790.56149806], [30877, 118523055.56233746], [30891, 118630832.99974376], [30905, 118593766.25352278], [30919, 118375136.38237317], [30933, 118317994.32107869], [30947, 118342458.6624524], [30961, 118424119.24260657], [30975, 118441694.89727603], [30989, 118490851.60946262], [31003, 118616044.0072371], [31017, 118591755.64122199], [31031, 118209692.54374976], [31045, 118536004.9760179], [32095, 130520351.32051608], [32109, 130303003.49475175], [32123, 130377065.54506756], [32137, 130328342.93277036], [32151, 130352041.12957084], [32165, 130310033.90545855], [32179, 130157809.45437181], [32193, 130332075.99513994], [32207, 131479302.06080501], [32221, 132799037.79580754], [32235, 133077146.67388168], [32249, 132699151.83146623], [32263, 132818961.04305454], [32277, 132837546.08732025], [32305, 134653843.74370387], [32319, 138240133.18855956], [32333, 138259832.6890016], [32347, 138158367.5016459], [32361, 138269720.1704919], [32375, 138314495.28304166], [32389, 138235304.04897952], [32403, 138443754.12643006], [32417, 138321858.2390305], [32431, 138466306.51662892], [32445, 138574416.6876778], [32571, 136151000.1203221], [32585, 136245040.16547757], [32599, 136126560.07080653], [32613, 136106443.75847426], [32627, 136257969.59709767], [32641, 135911935.06575233], [32655, 136121656.28231403], [32851, 137019246.97521934], [32865, 137149919.33469144], [32879, 137061593.25332686], [32893, 137275276.74105936], [32907, 138944191.38469005], [32921, 139044713.0286346], [32991, 139082374.72384334], [33005, 139091591.57576793], [33019, 138651780.32577732], [33033, 138998614.53096423], [33047, 139208993.84305033], [33061, 139423089.82242644], [33075, 139352126.810706], [33089, 154032884.26201758], [33103, 168732734.28029093], [33117, 168931900.75548914], [33131, 168831683.83165723], [33145, 168993548.4224284], [33159, 169023042.71177095], [33187, 139499499.85955793], [33201, 139558499.7793885], [33215, 137661299.12373704], [33229, 132630310.43618035], [33243, 132529325.67634955], [33271, 125673492.49193491], [33285, 125899689.2706669], [33299, 125734592.98010962], [33313, 124576552.89339659], [33327, 125906528.72209892], [33341, 125889994.2510986], [33355, 126195247.50733589], [33369, 126643848.9618532], [33383, 126810608.2424894], [33397, 127119291.29465088], [33411, 127224301.59890647], [33425, 127114384.50048792], [33439, 128015218.46943976], [33453, 123243237.87177993], [33467, 123291053.63786004], [33523, 123400190.2814168], [33537, 123358814.57950853], [33551, 122792309.61389373], [33649, 122113399.11205745], [33705, 121702191.51727994], [33719, 121801264.7383039], [33733, 121884979.08324514], [33747, 121763797.74889722], [33761, 121871648.43293758], [33775, 121652205.4369249], [33803, 121820972.85779606], [33817, 121635111.84042668], [33831, 121695373.74865158], [33845, 121694911.07743756], [34041, 121376480.9326448], [34055, 121611981.87391357], [34069, 121582231.94990097], [34083, 121350242.5940921], [34125, 121566467.66384898], [34139, 121734877.21264], [34153, 121577886.52499278], [34167, 121469420.61874808]] \ No newline at end of file +[[28511, 119392618.44421901], [29225, 116847664.4262998], [29239, 116826689.42662717], [29253, 116759580.73119773], [29267, 116763135.20443648], [29281, 116896170.2669805], [29295, 116919775.80293305], [29309, 116794281.72384158], [29323, 116842945.38822782], [29337, 117265724.45989524], [29351, 116356229.01020575], [29365, 116326350.69920829], [29379, 116673325.87150455], [29393, 116558361.90437062], [29407, 116610686.81119043], [29421, 116523897.0545817], [29435, 116991177.61676168], [29449, 117019651.35965978], [29463, 116865813.4737947], [29477, 116868793.57914206], [29547, 116977317.56270702], [29561, 117106979.00101425], [29575, 116502561.1904805], [29603, 117743020.55062744], [29617, 117698605.41927937], [29631, 117893757.49124242], [29645, 117932272.22659096], [29659, 117838195.17010781], [29673, 117758569.52398534], [29743, 117750396.37051326], [29757, 117873590.61693758], [29771, 117759083.52484651], [29785, 117975086.52539599], [29799, 117883840.34427378], [29813, 117986880.14426863], [29827, 118099901.87072596], [29841, 117970135.57517841], [29855, 117933511.43854968], [29869, 118014999.49777295], [30009, 117968393.81353995], [30023, 118052493.71548024], [30037, 117919408.91932766], [30051, 117762184.2432193], [30065, 117958844.00964232], [30079, 117981719.25924785], [30093, 117854092.86249447], [30107, 117818378.14924566], [30121, 118000684.59192717], [30135, 117967832.03870371], [30149, 118295531.02411285], [30163, 118323374.76663911], [30177, 118541355.93026629], [30191, 118506003.8156645], [30205, 118424636.12644787], [30219, 118444027.25385804], [30233, 118282625.57381469], [30247, 118481309.16382524], [30261, 118219474.34622404], [30513, 118566140.11441322], [30527, 118361357.08959743], [30541, 118305259.45050573], [30555, 118243678.91650288], [30569, 118145625.27963275], [30583, 118454542.17631716], [30597, 118189733.90003695], [30625, 118236149.54244089], [30639, 118266595.96966082], [30653, 118182624.62583087], [30667, 118308584.49927595], [30681, 118334692.03638677], [30695, 118432616.2065056], [30709, 118340255.0364696], [30723, 118337834.50531733], [30737, 118355143.43890887], [30751, 118436786.25424981], [30765, 118789454.36051686], [30779, 118307814.45298098], [30793, 118361131.37376238], [30807, 118286858.86482021], [30821, 118496135.02017784], [30835, 118752145.83696799], [30849, 118469279.88958254], [30863, 118381790.56149806], [30877, 118523055.56233746], [30891, 118630832.99974376], [30905, 118593766.25352278], [30919, 118375136.38237317], [30933, 118317994.32107869], [30947, 118342458.6624524], [30961, 118424119.24260657], [30975, 118441694.89727603], [30989, 118490851.60946262], [31003, 118616044.0072371], [31017, 118591755.64122199], [31031, 118209692.54374976], [31045, 118536004.9760179], [32095, 130520351.32051608], [32109, 130303003.49475175], [32123, 130377065.54506756], [32137, 130328342.93277036], [32151, 130352041.12957084], [32165, 130310033.90545855], [32179, 130157809.45437181], [32193, 130332075.99513994], [32207, 131479302.06080501], [32221, 132799037.79580754], [32235, 133077146.67388168], [32249, 132699151.83146623], [32263, 132818961.04305454], [32277, 132837546.08732025], [32305, 134653843.74370387], [32319, 138240133.18855956], [32333, 138259832.6890016], [32347, 138158367.5016459], [32361, 138269720.1704919], [32375, 138314495.28304166], [32389, 138235304.04897952], [32403, 138443754.12643006], [32417, 138321858.2390305], [32431, 138466306.51662892], [32445, 138574416.6876778], [32571, 136151000.1203221], [32585, 136245040.16547757], [32599, 136126560.07080653], [32613, 136106443.75847426], [32627, 136257969.59709767], [32641, 135911935.06575233], [32655, 136121656.28231403], [32851, 137019246.97521934], [32865, 137149919.33469144], [32879, 137061593.25332686], [32893, 137275276.74105936], [32907, 138944191.38469005], [32921, 139044713.0286346], [32991, 139082374.72384334], [33005, 139091591.57576793], [33019, 138651780.32577732], [33033, 138998614.53096423], [33047, 139208993.84305033], [33061, 139423089.82242644], [33075, 139352126.810706], [33089, 154032884.26201758], [33103, 168732734.28029093], [33117, 168931900.75548914], [33131, 168831683.83165723], [33145, 168993548.4224284], [33159, 169023042.71177095], [33187, 139499499.85955793], [33201, 139558499.7793885], [33215, 137661299.12373704], [33229, 132630310.43618035], [33243, 132529325.67634955], [33271, 125673492.49193491], [33285, 125899689.2706669], [33299, 125734592.98010962], [33313, 124576552.89339659], [33327, 125906528.72209892], [33341, 125889994.2510986], [33355, 126195247.50733589], [33369, 126643848.9618532], [33383, 126810608.2424894], [33397, 127119291.29465088], [33411, 127224301.59890647], [33425, 127114384.50048792], [33439, 128015218.46943976], [33453, 123243237.87177993], [33467, 123291053.63786004], [33523, 123400190.2814168], [33537, 123358814.57950853], [33551, 122792309.61389373], [33649, 122113399.11205745], [33705, 121702191.51727994], [33719, 121801264.7383039], [33733, 121884979.08324514], [33747, 121763797.74889722], [33761, 121871648.43293758], [33775, 121652205.4369249], [33803, 121820972.85779606], [33817, 121635111.84042668], [33831, 121695373.74865158], [33845, 121694911.07743756], [34041, 121376480.9326448], [34055, 121611981.87391357], [34069, 121582231.94990097], [34083, 121350242.5940921], [34125, 121566467.66384898], [34139, 121734877.21264], [34153, 121577886.52499278], [34167, 121456044.75923829]] \ No newline at end of file diff --git a/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_fit.json b/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_fit.json index 942cf544b3..85d888ffb0 100644 --- a/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_fit.json +++ b/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 0.885506538347481], [29225, 0.6076158120537472], [29239, 0.6054927370172347], [29253, 0.441125848674717], [29267, 0.4496634091577718], [29281, 0.4339901080449629], [29295, 0.44562305113964923], [29309, 0.4377872702256269], [29323, 0.4352942075338885], [29337, 0.4518328636138893], [29351, 0.45510150698901136], [29365, 0.4458124612238611], [29379, 0.45965610390239875], [29393, 0.44326743722334333], [29407, 0.4512367534738735], [29421, 0.45404393020753536], [29435, 0.4196164403938989], [29449, 0.6071794454591924], [29463, 0.6241113793168507], [29477, 0.5764539795020159], [29547, 0.62661042711336], [29561, 0.5983719160023275], [29575, 0.5398025991420735], [29603, 0.5265095436920147], [29617, 0.5518292089667086], [29631, 0.5334566413060402], [29645, 0.542510664290786], [29659, 0.5243102506778955], [29673, 0.5251724124022675], [29743, 0.5341932176262036], [29757, 0.5384960701570904], [29771, 0.5334232757449577], [29785, 0.6375464792374821], [29799, 0.5947470116700316], [29813, 0.6140355844996213], [29827, 0.592116077630215], [29841, 0.5918685316495329], [29855, 0.596432255699458], [29869, 0.6141716953781563], [30009, 0.6089166152042844], [30023, 0.6053187409980375], [30037, 0.6116758559335574], [30051, 0.6123253179335376], [30065, 0.6054099199766011], [30079, 0.608482789749304], [30093, 0.6118490176861575], [30107, 0.5892422846981632], [30121, 0.5999354773067368], [30135, 0.5841440161494638], [30149, 0.608011593564757], [30163, 0.6067594411907352], [30177, 0.6162548849085893], [30191, 0.606192627732622], [30205, 0.6212874800394627], [30219, 0.6140304083217842], [30233, 0.6275004453122192], [30247, 0.6073046816132871], [30261, 0.612624676920466], [30513, 0.6088603324142806], [30527, 0.6126684648776282], [30541, 0.6127422690301275], [30555, 0.6130121445423089], [30569, 0.6120900619829901], [30583, 0.607246525268871], [30597, 0.5916876529282491], [30625, 0.6147115137289191], [30639, 0.6099444729539714], [30653, 0.6090848897311648], [30667, 0.6081133149830736], [30681, 0.6103856645566729], [30695, 0.6281510910684105], [30709, 0.5875047369567507], [30723, 0.5978085700996052], [30737, 0.6100235750573187], [30751, 0.5874393397647893], [30765, 0.5949391762967076], [30779, 0.5840213080598546], [30793, 0.6028794320092611], [30807, 0.6204066598670464], [30821, 0.6017034853360491], [30835, 0.58974238620714], [30849, 0.5871240114188152], [30863, 0.6067078745013084], [30877, 0.5959486371513991], [30891, 0.6085599169624726], [30905, 0.6054386229545224], [30919, 0.5963624110382741], [30933, 0.611959122271921], [30947, 0.6026108367130407], [30961, 0.5982764932658936], [30975, 0.5981430870693593], [30989, 0.6031971235551961], [31003, 0.5952324809483924], [31017, 0.58818522541935], [31031, 0.6049103681528616], [31045, 0.5929022877876917], [32095, 0.5481733931854431], [32109, 0.5658060734035157], [32123, 0.5613055506563521], [32137, 0.5695035905707306], [32151, 0.5619070217173671], [32165, 0.5724019648282643], [32179, 0.58526840947721], [32193, 0.5678105475653997], [32207, 0.5679844246336003], [32221, 0.5568027029884042], [32235, 0.5425157312433875], [32249, 0.5486216185264525], [32263, 0.5678562027103244], [32277, 0.5667595091742222], [32305, 0.5613545165211243], [32319, 0.5712797668416131], [32333, 0.5894656680803674], [32347, 0.5413770589102561], [32361, 0.5642286182801042], [32375, 0.5580158427004399], [32389, 0.5551859831198607], [32403, 0.5912085337937247], [32417, 0.5804743857123735], [32431, 0.5721959254316233], [32445, 0.5431579997317765], [32571, 0.4997484253163827], [32585, 0.5278028940547886], [32599, 0.5412736358819564], [32613, 0.5547350878589227], [32627, 0.5329290087245766], [32641, 0.545218594456647], [32655, 0.518068504547617], [32851, 0.5529720306281045], [32865, 0.5481899631420928], [32879, 0.5700586010171228], [32893, 0.5311955444626151], [32907, 0.5500572901164141], [32921, 0.542364639754101], [32991, 0.5442493376630649], [33005, 0.5506286905719312], [33019, 0.555475216152934], [33033, 0.5526820522190086], [33047, 0.5374688762916281], [33061, 0.5450944271090348], [33075, 0.5635693745034955], [33089, 0.5624314499666669], [33103, 0.5720026177802369], [33117, 0.5751224152614218], [33131, 0.5479457090876718], [33145, 0.5412882073305431], [33159, 0.5561514342806394], [33187, 0.5628387529727051], [33201, 0.5627927686058118], [33215, 0.5792477317115279], [33229, 0.6383053396865739], [33243, 0.6250983848061611], [33271, 0.7047601236901687], [33285, 0.7310139646678205], [33299, 0.7176903237195156], [33313, 0.7192978347015178], [33327, 0.7224737651769257], [33341, 0.7219522712441333], [33355, 0.732824127294536], [33369, 0.7157612131712323], [33383, 0.7417924195050287], [33397, 0.6939517010314147], [33411, 0.6924982435394675], [33425, 0.716969428684626], [33439, 0.7080219852036466], [33453, 0.7211268808105921], [33467, 0.7405038821402706], [33523, 0.7233121810368506], [33537, 0.7121448508737277], [33551, 0.7273171642152905], [33649, 0.7546383377267453], [33705, 0.7208062702383584], [33719, 0.7496767809650192], [33733, 0.7456601848568434], [33747, 0.7401343195203481], [33761, 0.7506222104552746], [33775, 0.7353221402206743], [33803, 0.734045846740302], [33817, 0.7046861468010809], [33831, 0.7055412385289505], [33845, 0.7134755827655636], [34041, 0.7318327464502881], [34055, 0.7438673694433509], [34069, 0.7087780722507494], [34083, 0.6902409641578369], [34125, 0.6914867119522591], [34139, 0.7081804195746296], [34153, 0.692414056937194], [34167, 0.6850817942063772]] \ No newline at end of file +[[28511, 0.885506538347481], [29225, 0.6076158120537472], [29239, 0.6054927370172347], [29253, 0.441125848674717], [29267, 0.4496634091577718], [29281, 0.4339901080449629], [29295, 0.44562305113964923], [29309, 0.4377872702256269], [29323, 0.4352942075338885], [29337, 0.4518328636138893], [29351, 0.45510150698901136], [29365, 0.4458124612238611], [29379, 0.45965610390239875], [29393, 0.44326743722334333], [29407, 0.4512367534738735], [29421, 0.45404393020753536], [29435, 0.4196164403938989], [29449, 0.6071794454591924], [29463, 0.6241113793168507], [29477, 0.5764539795020159], [29547, 0.62661042711336], [29561, 0.5983719160023275], [29575, 0.5398025991420735], [29603, 0.5265095436920147], [29617, 0.5518292089667086], [29631, 0.5334566413060402], [29645, 0.542510664290786], [29659, 0.5243102506778955], [29673, 0.5251724124022675], [29743, 0.5341932176262036], [29757, 0.5384960701570904], [29771, 0.5334232757449577], [29785, 0.6375464792374821], [29799, 0.5947470116700316], [29813, 0.6140355844996213], [29827, 0.592116077630215], [29841, 0.5918685316495329], [29855, 0.596432255699458], [29869, 0.6141716953781563], [30009, 0.6089166152042844], [30023, 0.6053187409980375], [30037, 0.6116758559335574], [30051, 0.6123253179335376], [30065, 0.6054099199766011], [30079, 0.608482789749304], [30093, 0.6118490176861575], [30107, 0.5892422846981632], [30121, 0.5999354773067368], [30135, 0.5841440161494638], [30149, 0.608011593564757], [30163, 0.6067594411907352], [30177, 0.6162548849085893], [30191, 0.606192627732622], [30205, 0.6212874800394627], [30219, 0.6140304083217842], [30233, 0.6275004453122192], [30247, 0.6073046816132871], [30261, 0.612624676920466], [30513, 0.6088603324142806], [30527, 0.6126684648776282], [30541, 0.6127422690301275], [30555, 0.6130121445423089], [30569, 0.6120900619829901], [30583, 0.607246525268871], [30597, 0.5916876529282491], [30625, 0.6147115137289191], [30639, 0.6099444729539714], [30653, 0.6090848897311648], [30667, 0.6081133149830736], [30681, 0.6103856645566729], [30695, 0.6281510910684105], [30709, 0.5875047369567507], [30723, 0.5978085700996052], [30737, 0.6100235750573187], [30751, 0.5874393397647893], [30765, 0.5949391762967076], [30779, 0.5840213080598546], [30793, 0.6028794320092611], [30807, 0.6204066598670464], [30821, 0.6017034853360491], [30835, 0.58974238620714], [30849, 0.5871240114188152], [30863, 0.6067078745013084], [30877, 0.5959486371513991], [30891, 0.6085599169624726], [30905, 0.6054386229545224], [30919, 0.5963624110382741], [30933, 0.611959122271921], [30947, 0.6026108367130407], [30961, 0.5982764932658936], [30975, 0.5981430870693593], [30989, 0.6031971235551961], [31003, 0.5952324809483924], [31017, 0.58818522541935], [31031, 0.6049103681528616], [31045, 0.5929022877876917], [32095, 0.5481733931854431], [32109, 0.5658060734035157], [32123, 0.5613055506563521], [32137, 0.5695035905707306], [32151, 0.5619070217173671], [32165, 0.5724019648282643], [32179, 0.58526840947721], [32193, 0.5678105475653997], [32207, 0.5679844246336003], [32221, 0.5568027029884042], [32235, 0.5425157312433875], [32249, 0.5486216185264525], [32263, 0.5678562027103244], [32277, 0.5667595091742222], [32305, 0.5613545165211243], [32319, 0.5712797668416131], [32333, 0.5894656680803674], [32347, 0.5413770589102561], [32361, 0.5642286182801042], [32375, 0.5580158427004399], [32389, 0.5551859831198607], [32403, 0.5912085337937247], [32417, 0.5804743857123735], [32431, 0.5721959254316233], [32445, 0.5431579997317765], [32571, 0.4997484253163827], [32585, 0.5278028940547886], [32599, 0.5412736358819564], [32613, 0.5547350878589227], [32627, 0.5329290087245766], [32641, 0.545218594456647], [32655, 0.518068504547617], [32851, 0.5529720306281045], [32865, 0.5481899631420928], [32879, 0.5700586010171228], [32893, 0.5311955444626151], [32907, 0.5500572901164141], [32921, 0.542364639754101], [32991, 0.5442493376630649], [33005, 0.5506286905719312], [33019, 0.555475216152934], [33033, 0.5526820522190086], [33047, 0.5374688762916281], [33061, 0.5450944271090348], [33075, 0.5635693745034955], [33089, 0.5624314499666669], [33103, 0.5720026177802369], [33117, 0.5751224152614218], [33131, 0.5479457090876718], [33145, 0.5412882073305431], [33159, 0.5561514342806394], [33187, 0.5628387529727051], [33201, 0.5627927686058118], [33215, 0.5792477317115279], [33229, 0.6383053396865739], [33243, 0.6250983848061611], [33271, 0.7047601236901687], [33285, 0.7310139646678205], [33299, 0.7176903237195156], [33313, 0.7192978347015178], [33327, 0.7224737651769257], [33341, 0.7219522712441333], [33355, 0.732824127294536], [33369, 0.7157612131712323], [33383, 0.7417924195050287], [33397, 0.6939517010314147], [33411, 0.6924982435394675], [33425, 0.716969428684626], [33439, 0.7080219852036466], [33453, 0.7211268808105921], [33467, 0.7405038821402706], [33523, 0.7233121810368506], [33537, 0.7121448508737277], [33551, 0.7273171642152905], [33649, 0.7546383377267453], [33705, 0.7208062702383584], [33719, 0.7496767809650192], [33733, 0.7456601848568434], [33747, 0.7401343195203481], [33761, 0.7506222104552746], [33775, 0.7353221402206743], [33803, 0.734045846740302], [33817, 0.7046861468010809], [33831, 0.7055412385289505], [33845, 0.7134755827655636], [34041, 0.7318327464502881], [34055, 0.7438673694433509], [34069, 0.7087780722507494], [34083, 0.6902409641578369], [34125, 0.6914867119522591], [34139, 0.7081804195746296], [34153, 0.692414056937194], [34167, 0.6850362795514812]] \ No newline at end of file diff --git a/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_predict.json b/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_predict.json index 0a77fa6cfd..b308419d51 100644 --- a/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_predict.json +++ b/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_predict.json @@ -1 +1 @@ -[[28511, 0.07603053390923613], [29225, 0.024172280987084724], [29239, 0.020588852182880573], [29253, 0.012290635848592857], [29267, 0.012078682174026235], [29281, 0.011672760275965904], [29295, 0.011848681387373992], [29309, 0.011953854027733187], [29323, 0.012180908925059198], [29337, 0.011805058863771692], [29351, 0.012265816228389514], [29365, 0.01154615006315986], [29379, 0.012465483362136872], [29393, 0.011885129372157433], [29407, 0.011880142236587513], [29421, 0.01243438639339764], [29435, 0.011905835197306258], [29449, 0.02018190518871187], [29463, 0.020910598008554528], [29477, 0.0230952141716483], [29547, 0.02246778634824249], [29561, 0.021173141159168046], [29575, 0.01980127838783336], [29603, 0.018069959889993187], [29617, 0.019238565351342878], [29631, 0.016203359998021565], [29645, 0.016905544602428723], [29659, 0.016931641281073787], [29673, 0.017387735887713127], [29743, 0.018037844890805316], [29757, 0.017489514802091294], [29771, 0.01850004394215509], [29785, 0.022408074583367448], [29799, 0.020632545498838254], [29813, 0.021478856350161737], [29827, 0.019785387207323292], [29841, 0.020974256802300337], [29855, 0.02156303317473984], [29869, 0.022190693282770586], [30009, 0.02087368899942408], [30023, 0.02135743463197322], [30037, 0.021095328261760162], [30051, 0.022308840627720206], [30065, 0.02227040326492736], [30079, 0.021243417794867346], [30093, 0.020260033434924978], [30107, 0.022015401319077654], [30121, 0.02122667084387618], [30135, 0.020637995132432644], [30149, 0.02150903286723921], [30163, 0.02251354358420871], [30177, 0.023140470194595454], [30191, 0.020557223562110087], [30205, 0.019863797910044334], [30219, 0.021903315966500712], [30233, 0.02113159595262823], [30247, 0.02230204813921713], [30261, 0.021260807976760616], [30513, 0.021723611127278285], [30527, 0.022568374399246163], [30541, 0.02176160573323706], [30555, 0.021582668753744302], [30569, 0.02292764528590041], [30583, 0.02191051031446873], [30597, 0.021715289754023957], [30625, 0.020938583697382624], [30639, 0.019571722384269366], [30653, 0.02281728786509969], [30667, 0.021285951500365292], [30681, 0.02121306599481992], [30695, 0.02215991625638156], [30709, 0.023363330118115647], [30723, 0.020979917440710604], [30737, 0.02312274212300697], [30751, 0.022413693113452086], [30765, 0.02162970082492781], [30779, 0.02217777733235651], [30793, 0.020206640305047412], [30807, 0.02070024751628606], [30821, 0.02072924669002016], [30835, 0.020864417847913826], [30849, 0.019798236578578626], [30863, 0.02399643308092319], [30877, 0.019456532760603655], [30891, 0.01938713789907316], [30905, 0.018321301551085616], [30919, 0.02111703687762362], [30933, 0.019804306744641675], [30947, 0.022403321547540583], [30961, 0.020289651364451905], [30975, 0.021753051249023634], [30989, 0.022272320802601258], [31003, 0.020242582388062515], [31017, 0.019920301036868204], [31031, 0.018599085920339334], [31045, 0.021688004201456848], [32095, 0.016757417240189906], [32109, 0.015653245963762857], [32123, 0.015356499896542362], [32137, 0.014507731270685926], [32151, 0.015228201336267557], [32165, 0.01470057452513641], [32179, 0.015257761610052005], [32193, 0.014437091650919906], [32207, 0.01488122293517907], [32221, 0.014956576541390517], [32235, 0.015646714697219285], [32249, 0.014001853930327112], [32263, 0.013471518322915921], [32277, 0.015137299828420131], [32305, 0.014922060606642933], [32319, 0.014540618523337675], [32333, 0.018190504466985172], [32347, 0.01482589486434754], [32361, 0.014497362015067754], [32375, 0.015140296699506006], [32389, 0.015186272058571244], [32403, 0.01463868912232278], [32417, 0.01503157299999238], [32431, 0.014310934290366303], [32445, 0.01442572560519722], [32571, 0.012391300565553496], [32585, 0.014401061840590092], [32599, 0.014723970048470902], [32613, 0.01534914929874001], [32627, 0.014669379139471967], [32641, 0.016603634181367198], [32655, 0.013963816276858424], [32851, 0.012689287508743236], [32865, 0.013950170257339845], [32879, 0.013943415730689648], [32893, 0.012645333726035598], [32907, 0.01278133310944283], [32921, 0.012771144136752687], [32991, 0.012351956457545877], [33005, 0.014663083152644758], [33019, 0.014401730387927494], [33033, 0.01372197944308133], [33047, 0.011767956689832606], [33061, 0.01368990985181832], [33075, 0.012506618540952402], [33089, 0.013754756549136925], [33103, 0.014985295917183622], [33117, 0.01398386635643328], [33131, 0.013396991179276337], [33145, 0.01524966374957153], [33159, 0.012661410845708869], [33187, 0.01277211287108129], [33201, 0.013471498128481538], [33215, 0.014114336262623041], [33229, 0.013113687463093781], [33243, 0.013626787279340235], [33271, 0.01244723680685603], [33285, 0.014512463816356246], [33299, 0.014308492237265168], [33313, 0.01454684948828712], [33327, 0.013764658267436062], [33341, 0.014845154370989795], [33355, 0.015798037858401306], [33369, 0.01419958033811398], [33383, 0.014527138342174306], [33397, 0.014844179887154842], [33411, 0.01397388116024254], [33425, 0.013935766693271071], [33439, 0.014063943086824179], [33453, 0.014870544694814487], [33467, 0.014131850270487589], [33523, 0.014359728982750588], [33537, 0.014295068308314104], [33551, 0.01447389400113109], [33649, 0.012313711838169346], [33705, 0.013704564622871724], [33719, 0.014468103770935646], [33733, 0.017045643041167152], [33747, 0.01633775982268541], [33761, 0.013780034346051137], [33775, 0.016532402252968304], [33803, 0.014620393396234728], [33817, 0.013053523820013294], [33831, 0.013824243632799821], [33845, 0.013694555500861696], [34041, 0.013545783116917053], [34055, 0.014425626702010362], [34069, 0.013022658368675777], [34083, 0.015170721630756636], [34125, 0.013872195524668824], [34139, 0.014559219625549177], [34153, 0.01331893761454936], [34167, 0.013992823762473369]] \ No newline at end of file +[[28511, 0.07603053390923613], [29225, 0.024172280987084724], [29239, 0.020588852182880573], [29253, 0.012290635848592857], [29267, 0.012078682174026235], [29281, 0.011672760275965904], [29295, 0.011848681387373992], [29309, 0.011953854027733187], [29323, 0.012180908925059198], [29337, 0.011805058863771692], [29351, 0.012265816228389514], [29365, 0.01154615006315986], [29379, 0.012465483362136872], [29393, 0.011885129372157433], [29407, 0.011880142236587513], [29421, 0.01243438639339764], [29435, 0.011905835197306258], [29449, 0.02018190518871187], [29463, 0.020910598008554528], [29477, 0.0230952141716483], [29547, 0.02246778634824249], [29561, 0.021173141159168046], [29575, 0.01980127838783336], [29603, 0.018069959889993187], [29617, 0.019238565351342878], [29631, 0.016203359998021565], [29645, 0.016905544602428723], [29659, 0.016931641281073787], [29673, 0.017387735887713127], [29743, 0.018037844890805316], [29757, 0.017489514802091294], [29771, 0.01850004394215509], [29785, 0.022408074583367448], [29799, 0.020632545498838254], [29813, 0.021478856350161737], [29827, 0.019785387207323292], [29841, 0.020974256802300337], [29855, 0.02156303317473984], [29869, 0.022190693282770586], [30009, 0.02087368899942408], [30023, 0.02135743463197322], [30037, 0.021095328261760162], [30051, 0.022308840627720206], [30065, 0.02227040326492736], [30079, 0.021243417794867346], [30093, 0.020260033434924978], [30107, 0.022015401319077654], [30121, 0.02122667084387618], [30135, 0.020637995132432644], [30149, 0.02150903286723921], [30163, 0.02251354358420871], [30177, 0.023140470194595454], [30191, 0.020557223562110087], [30205, 0.019863797910044334], [30219, 0.021903315966500712], [30233, 0.02113159595262823], [30247, 0.02230204813921713], [30261, 0.021260807976760616], [30513, 0.021723611127278285], [30527, 0.022568374399246163], [30541, 0.02176160573323706], [30555, 0.021582668753744302], [30569, 0.02292764528590041], [30583, 0.02191051031446873], [30597, 0.021715289754023957], [30625, 0.020938583697382624], [30639, 0.019571722384269366], [30653, 0.02281728786509969], [30667, 0.021285951500365292], [30681, 0.02121306599481992], [30695, 0.02215991625638156], [30709, 0.023363330118115647], [30723, 0.020979917440710604], [30737, 0.02312274212300697], [30751, 0.022413693113452086], [30765, 0.02162970082492781], [30779, 0.02217777733235651], [30793, 0.020206640305047412], [30807, 0.02070024751628606], [30821, 0.02072924669002016], [30835, 0.020864417847913826], [30849, 0.019798236578578626], [30863, 0.02399643308092319], [30877, 0.019456532760603655], [30891, 0.01938713789907316], [30905, 0.018321301551085616], [30919, 0.02111703687762362], [30933, 0.019804306744641675], [30947, 0.022403321547540583], [30961, 0.020289651364451905], [30975, 0.021753051249023634], [30989, 0.022272320802601258], [31003, 0.020242582388062515], [31017, 0.019920301036868204], [31031, 0.018599085920339334], [31045, 0.021688004201456848], [32095, 0.016757417240189906], [32109, 0.015653245963762857], [32123, 0.015356499896542362], [32137, 0.014507731270685926], [32151, 0.015228201336267557], [32165, 0.01470057452513641], [32179, 0.015257761610052005], [32193, 0.014437091650919906], [32207, 0.01488122293517907], [32221, 0.014956576541390517], [32235, 0.015646714697219285], [32249, 0.014001853930327112], [32263, 0.013471518322915921], [32277, 0.015137299828420131], [32305, 0.014922060606642933], [32319, 0.014540618523337675], [32333, 0.018190504466985172], [32347, 0.01482589486434754], [32361, 0.014497362015067754], [32375, 0.015140296699506006], [32389, 0.015186272058571244], [32403, 0.01463868912232278], [32417, 0.01503157299999238], [32431, 0.014310934290366303], [32445, 0.01442572560519722], [32571, 0.012391300565553496], [32585, 0.014401061840590092], [32599, 0.014723970048470902], [32613, 0.01534914929874001], [32627, 0.014669379139471967], [32641, 0.016603634181367198], [32655, 0.013963816276858424], [32851, 0.012689287508743236], [32865, 0.013950170257339845], [32879, 0.013943415730689648], [32893, 0.012645333726035598], [32907, 0.01278133310944283], [32921, 0.012771144136752687], [32991, 0.012351956457545877], [33005, 0.014663083152644758], [33019, 0.014401730387927494], [33033, 0.01372197944308133], [33047, 0.011767956689832606], [33061, 0.01368990985181832], [33075, 0.012506618540952402], [33089, 0.013754756549136925], [33103, 0.014985295917183622], [33117, 0.01398386635643328], [33131, 0.013396991179276337], [33145, 0.01524966374957153], [33159, 0.012661410845708869], [33187, 0.01277211287108129], [33201, 0.013471498128481538], [33215, 0.014114336262623041], [33229, 0.013113687463093781], [33243, 0.013626787279340235], [33271, 0.01244723680685603], [33285, 0.014512463816356246], [33299, 0.014308492237265168], [33313, 0.01454684948828712], [33327, 0.013764658267436062], [33341, 0.014845154370989795], [33355, 0.015798037858401306], [33369, 0.01419958033811398], [33383, 0.014527138342174306], [33397, 0.014844179887154842], [33411, 0.01397388116024254], [33425, 0.013935766693271071], [33439, 0.014063943086824179], [33453, 0.014870544694814487], [33467, 0.014131850270487589], [33523, 0.014359728982750588], [33537, 0.014295068308314104], [33551, 0.01447389400113109], [33649, 0.012313711838169346], [33705, 0.013704564622871724], [33719, 0.014468103770935646], [33733, 0.017045643041167152], [33747, 0.01633775982268541], [33761, 0.013780034346051137], [33775, 0.016532402252968304], [33803, 0.014620393396234728], [33817, 0.013053523820013294], [33831, 0.013824243632799821], [33845, 0.013694555500861696], [34041, 0.013545783116917053], [34055, 0.014425626702010362], [34069, 0.013022658368675777], [34083, 0.015170721630756636], [34125, 0.013872195524668824], [34139, 0.014559219625549177], [34153, 0.01331893761454936], [34167, 0.013805119947252743]] \ No newline at end of file diff --git a/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_transform.json b/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_transform.json index 3245eb8db9..93e739e505 100644 --- a/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_transform.json +++ b/graphs/summary/cluster.MiniBatchKMeansBenchmark.time_transform.json @@ -1 +1 @@ -[[28511, 0.6411758793430627], [29225, 0.8367683246216389], [29239, 0.8342568458888033], [29253, 0.6285226412293143], [29267, 0.6406846341481085], [29281, 0.6457123257667446], [29295, 0.659164338290912], [29309, 0.668702832515405], [29323, 0.628654865820734], [29337, 0.6729778233218489], [29351, 0.6807311539246559], [29365, 0.6485883915197814], [29379, 0.6894902387593237], [29393, 0.6614495177464407], [29407, 0.6520625306400336], [29421, 0.6645036576857123], [29435, 0.6309324109740461], [29449, 0.9275812575453921], [29463, 0.9124956944077864], [29477, 0.9513892379114296], [29547, 1.003122350764527], [29561, 0.9452176532029753], [29575, 0.8147161874842552], [29603, 0.7906092220342904], [29617, 0.8141221914264785], [29631, 0.8225573793229618], [29645, 0.8137584769530999], [29659, 0.7949075923461704], [29673, 0.8107839113234444], [29743, 0.8112944725752866], [29757, 0.807642258352333], [29771, 0.8152788392647983], [29785, 0.8575167023375656], [29799, 0.8256819232401937], [29813, 0.850149486869597], [29827, 0.8397735550732646], [29841, 0.8913155447063172], [29855, 0.8565705988932767], [29869, 0.8480482867897965], [30009, 0.932086348298442], [30023, 0.8693705931584468], [30037, 0.8687256954597827], [30051, 0.8684205161958471], [30065, 0.8485175091445649], [30079, 0.8616510787018946], [30093, 0.8565366113441917], [30107, 0.8659809497749951], [30121, 0.8283152590629043], [30135, 0.8729425479460855], [30149, 0.8440604642147984], [30163, 0.8564606723673219], [30177, 0.8592282321098407], [30191, 0.8560439845295496], [30205, 0.8730427841649311], [30219, 0.8639269208987205], [30233, 0.8571834298053447], [30247, 0.8567346633868715], [30261, 0.8593442864559043], [30513, 0.8669423821098159], [30527, 0.8474922498008738], [30541, 0.8505762827857083], [30555, 0.8614040027911664], [30569, 0.845777828756117], [30583, 0.8477240120277959], [30597, 0.8470308860436011], [30625, 0.863065222074825], [30639, 0.8240959453521457], [30653, 0.8561860294798085], [30667, 0.8561023345994583], [30681, 0.8696438845313885], [30695, 0.8893200552405847], [30709, 0.8513684489218215], [30723, 0.8421181173386748], [30737, 0.8831021255299909], [30751, 0.8690457293205831], [30765, 0.8659816694768243], [30779, 0.8485149607281437], [30793, 0.8414814341857614], [30807, 0.8377256996831736], [30821, 0.859876057862182], [30835, 0.8264878281812248], [30849, 0.8343821288847196], [30863, 0.846282888426347], [30877, 0.8480652127837693], [30891, 0.8773193176728323], [30905, 0.854496147159246], [30919, 0.840926845469791], [30933, 0.8471479316142869], [30947, 0.8545634777832876], [30961, 0.8862804036464261], [30975, 0.8563396405238491], [30989, 0.845481079221741], [31003, 0.8387391090768327], [31017, 0.8633427817589611], [31031, 0.881371411971185], [31045, 0.8349293682956846], [32095, 0.858668575781856], [32109, 0.8696494982412108], [32123, 0.8694656790828337], [32137, 0.8646908833743673], [32151, 0.8536583997083111], [32165, 0.8724568806092855], [32179, 0.8111193607230336], [32193, 0.8695273439304473], [32207, 0.8520711051031409], [32221, 0.8493377009796492], [32235, 0.862170738114812], [32249, 0.8465701416716488], [32263, 0.8468184242894434], [32277, 0.8545656520317714], [32305, 0.8450273555540018], [32319, 0.8622603427220604], [32333, 0.9477873744031872], [32347, 0.812836347541382], [32361, 0.8174222301788951], [32375, 0.8186597839572107], [32389, 0.8495832201880651], [32403, 0.8246729505151081], [32417, 0.8331690413786443], [32431, 0.8184007559450638], [32445, 0.8290170858685655], [32571, 0.8232320326202842], [32585, 0.8155498142535773], [32599, 0.8470162858298211], [32613, 0.8645252134948519], [32627, 0.8151910350879961], [32641, 0.8303350502419441], [32655, 0.8297688201973381], [32851, 0.8452892691880928], [32865, 0.8255179040947633], [32879, 0.8448275929991201], [32893, 0.8217211734708354], [32907, 0.8709811156550155], [32921, 0.8493557815790601], [32991, 0.8485228956419225], [33005, 0.8514898023942593], [33019, 0.8554707751229695], [33033, 0.8857091037789517], [33047, 1.0147232849441858], [33061, 0.9784510202579889], [33075, 1.016225533366482], [33089, 1.0207874502861929], [33103, 1.0266707668440624], [33117, 1.0472322829814453], [33131, 1.0334082897933539], [33145, 1.0246229932059934], [33159, 1.0075625161417179], [33187, 1.0091974243343436], [33201, 1.0212170267047145], [33215, 1.0116699129945883], [33229, 0.9627527340157398], [33243, 0.957286901150736], [33271, 0.9082025232147029], [33285, 0.881138629547663], [33299, 0.9154530254004556], [33313, 0.9455215515818669], [33327, 0.9685853193693903], [33341, 0.9445524431142799], [33355, 0.9785994996840893], [33369, 0.988434967247415], [33383, 0.9468732817022723], [33397, 0.9312494638266267], [33411, 0.9724652661980299], [33425, 0.9739356006048252], [33439, 0.8727084153061504], [33453, 0.8275687443980033], [33467, 0.7958773426894232], [33523, 0.791371271287987], [33537, 0.7710797185504328], [33551, 0.7830693979249288], [33649, 0.7527888066813295], [33705, 0.7942931409476431], [33719, 0.7818857489199637], [33733, 0.7914820616785009], [33747, 0.7853072024646528], [33761, 0.8228217124999565], [33775, 0.8042004746067899], [33803, 0.798978679890384], [33817, 0.7901185005802437], [33831, 0.8131735340358675], [33845, 0.8051579360170495], [34041, 0.8050970521332432], [34055, 0.8033002054888866], [34069, 0.7936291475186669], [34083, 0.8109125066093816], [34125, 0.8047507468435554], [34139, 0.8102705234337659], [34153, 0.803776441136718], [34167, 0.8021965423549314]] \ No newline at end of file +[[28511, 0.6411758793430627], [29225, 0.8367683246216389], [29239, 0.8342568458888033], [29253, 0.6285226412293143], [29267, 0.6406846341481085], [29281, 0.6457123257667446], [29295, 0.659164338290912], [29309, 0.668702832515405], [29323, 0.628654865820734], [29337, 0.6729778233218489], [29351, 0.6807311539246559], [29365, 0.6485883915197814], [29379, 0.6894902387593237], [29393, 0.6614495177464407], [29407, 0.6520625306400336], [29421, 0.6645036576857123], [29435, 0.6309324109740461], [29449, 0.9275812575453921], [29463, 0.9124956944077864], [29477, 0.9513892379114296], [29547, 1.003122350764527], [29561, 0.9452176532029753], [29575, 0.8147161874842552], [29603, 0.7906092220342904], [29617, 0.8141221914264785], [29631, 0.8225573793229618], [29645, 0.8137584769530999], [29659, 0.7949075923461704], [29673, 0.8107839113234444], [29743, 0.8112944725752866], [29757, 0.807642258352333], [29771, 0.8152788392647983], [29785, 0.8575167023375656], [29799, 0.8256819232401937], [29813, 0.850149486869597], [29827, 0.8397735550732646], [29841, 0.8913155447063172], [29855, 0.8565705988932767], [29869, 0.8480482867897965], [30009, 0.932086348298442], [30023, 0.8693705931584468], [30037, 0.8687256954597827], [30051, 0.8684205161958471], [30065, 0.8485175091445649], [30079, 0.8616510787018946], [30093, 0.8565366113441917], [30107, 0.8659809497749951], [30121, 0.8283152590629043], [30135, 0.8729425479460855], [30149, 0.8440604642147984], [30163, 0.8564606723673219], [30177, 0.8592282321098407], [30191, 0.8560439845295496], [30205, 0.8730427841649311], [30219, 0.8639269208987205], [30233, 0.8571834298053447], [30247, 0.8567346633868715], [30261, 0.8593442864559043], [30513, 0.8669423821098159], [30527, 0.8474922498008738], [30541, 0.8505762827857083], [30555, 0.8614040027911664], [30569, 0.845777828756117], [30583, 0.8477240120277959], [30597, 0.8470308860436011], [30625, 0.863065222074825], [30639, 0.8240959453521457], [30653, 0.8561860294798085], [30667, 0.8561023345994583], [30681, 0.8696438845313885], [30695, 0.8893200552405847], [30709, 0.8513684489218215], [30723, 0.8421181173386748], [30737, 0.8831021255299909], [30751, 0.8690457293205831], [30765, 0.8659816694768243], [30779, 0.8485149607281437], [30793, 0.8414814341857614], [30807, 0.8377256996831736], [30821, 0.859876057862182], [30835, 0.8264878281812248], [30849, 0.8343821288847196], [30863, 0.846282888426347], [30877, 0.8480652127837693], [30891, 0.8773193176728323], [30905, 0.854496147159246], [30919, 0.840926845469791], [30933, 0.8471479316142869], [30947, 0.8545634777832876], [30961, 0.8862804036464261], [30975, 0.8563396405238491], [30989, 0.845481079221741], [31003, 0.8387391090768327], [31017, 0.8633427817589611], [31031, 0.881371411971185], [31045, 0.8349293682956846], [32095, 0.858668575781856], [32109, 0.8696494982412108], [32123, 0.8694656790828337], [32137, 0.8646908833743673], [32151, 0.8536583997083111], [32165, 0.8724568806092855], [32179, 0.8111193607230336], [32193, 0.8695273439304473], [32207, 0.8520711051031409], [32221, 0.8493377009796492], [32235, 0.862170738114812], [32249, 0.8465701416716488], [32263, 0.8468184242894434], [32277, 0.8545656520317714], [32305, 0.8450273555540018], [32319, 0.8622603427220604], [32333, 0.9477873744031872], [32347, 0.812836347541382], [32361, 0.8174222301788951], [32375, 0.8186597839572107], [32389, 0.8495832201880651], [32403, 0.8246729505151081], [32417, 0.8331690413786443], [32431, 0.8184007559450638], [32445, 0.8290170858685655], [32571, 0.8232320326202842], [32585, 0.8155498142535773], [32599, 0.8470162858298211], [32613, 0.8645252134948519], [32627, 0.8151910350879961], [32641, 0.8303350502419441], [32655, 0.8297688201973381], [32851, 0.8452892691880928], [32865, 0.8255179040947633], [32879, 0.8448275929991201], [32893, 0.8217211734708354], [32907, 0.8709811156550155], [32921, 0.8493557815790601], [32991, 0.8485228956419225], [33005, 0.8514898023942593], [33019, 0.8554707751229695], [33033, 0.8857091037789517], [33047, 1.0147232849441858], [33061, 0.9784510202579889], [33075, 1.016225533366482], [33089, 1.0207874502861929], [33103, 1.0266707668440624], [33117, 1.0472322829814453], [33131, 1.0334082897933539], [33145, 1.0246229932059934], [33159, 1.0075625161417179], [33187, 1.0091974243343436], [33201, 1.0212170267047145], [33215, 1.0116699129945883], [33229, 0.9627527340157398], [33243, 0.957286901150736], [33271, 0.9082025232147029], [33285, 0.881138629547663], [33299, 0.9154530254004556], [33313, 0.9455215515818669], [33327, 0.9685853193693903], [33341, 0.9445524431142799], [33355, 0.9785994996840893], [33369, 0.988434967247415], [33383, 0.9468732817022723], [33397, 0.9312494638266267], [33411, 0.9724652661980299], [33425, 0.9739356006048252], [33439, 0.8727084153061504], [33453, 0.8275687443980033], [33467, 0.7958773426894232], [33523, 0.791371271287987], [33537, 0.7710797185504328], [33551, 0.7830693979249288], [33649, 0.7527888066813295], [33705, 0.7942931409476431], [33719, 0.7818857489199637], [33733, 0.7914820616785009], [33747, 0.7853072024646528], [33761, 0.8228217124999565], [33775, 0.8042004746067899], [33803, 0.798978679890384], [33817, 0.7901185005802437], [33831, 0.8131735340358675], [33845, 0.8051579360170495], [34041, 0.8050970521332432], [34055, 0.8033002054888866], [34069, 0.7936291475186669], [34083, 0.8109125066093816], [34125, 0.8047507468435554], [34139, 0.8102705234337659], [34153, 0.803776441136718], [34167, 0.7997818707334062]] \ No newline at end of file diff --git a/graphs/summary/cluster.MiniBatchKMeansBenchmark.track_test_score.json b/graphs/summary/cluster.MiniBatchKMeansBenchmark.track_test_score.json index 71c484f2ae..ddc6230513 100644 --- a/graphs/summary/cluster.MiniBatchKMeansBenchmark.track_test_score.json +++ b/graphs/summary/cluster.MiniBatchKMeansBenchmark.track_test_score.json @@ -1 +1 @@ -[[28511, -1.9315717623933144], [29225, -1.8185027638193878], [29239, -1.8185027638193882], [29253, -1.8185027638193878], [29267, -1.8185027638193878], [29281, -1.8185027638193878], [29295, -1.8185027638193878], [29309, -1.8185027638193878], [29323, -1.8185027638193878], [29337, -1.8185027638193878], [29351, -1.8185027638193878], [29365, -1.8185027638193878], [29379, -1.8185027638193878], [29393, -1.8185027638193878], [29407, -1.8185027638193878], [29421, -1.8185027638193878], [29435, -1.8185027638193878], [29449, -1.8185027638193878], [29463, -1.818502763819388], [29477, -1.8185027638193878], [29547, -1.8185027638193878], [29561, -1.8185027638193878], [29575, -1.8185027638193878], [29603, -1.8185027638193878], [29617, -1.8185027638193878], [29631, -1.8185027638193878], [29645, -1.8185027638193878], [29659, -1.8185027638193878], [29673, -1.8185027638193878], [29743, -1.8185027638193878], [29757, -1.8185027638193878], [29771, -1.818502763819388], [29785, -1.8185027638193878], [29799, -1.818502763819388], [29813, -1.8185027638193878], [29827, -1.8185027638193878], [29841, -1.8185027638193878], [29855, -1.8185027638193878], [29869, -1.8185027638193878], [30009, -1.8185027638193878], [30023, -1.8185027638193878], [30037, -1.8185027638193878], [30051, -1.8185027638193878], [30065, -1.8185027638193878], [30079, -1.8185027638193882], [30093, -1.8185027638193878], [30107, -1.8185027638193878], [30121, -1.8185027638193878], [30135, -1.8185027638193878], [30149, -1.8185027638193878], [30163, -1.8185027638193878], [30177, -1.8185027638193878], [30191, -1.8185027638193878], [30205, -1.8185027638193878], [30219, -1.818502763819388], [30233, -1.8185027638193878], [30247, -1.8185027638193878], [30261, -1.8185027638193878], [30513, -1.818502763819388], [30527, -1.818502763819388], [30541, -1.8185027638193878], [30555, -1.818502763819388], [30569, -1.8185027638193878], [30583, -1.8185027638193878], [30597, -1.8185027638193878], [30625, -1.8185027638193878], [30639, -1.8185027638193878], [30653, -1.818502763819388], [30667, -1.8185027638193878], [30681, -1.8185027638193878], [30695, -1.8185027638193878], [30709, -1.8185027638193878], [30723, -1.8185027638193878], [30737, -1.8185027638193878], [30751, -1.8185027638193878], [30765, -1.8185027638193878], [30779, -1.8185027638193878], [30793, -1.8185027638193878], [30807, -1.8185027638193878], [30821, -1.8185027638193878], [30835, -1.8185027638193878], [30849, -1.8185027638193878], [30863, -1.8185027638193878], [30877, -1.8185027638193878], [30891, -1.8185027638193878], [30905, -1.8185027638193878], [30919, -1.8185027638193878], [30933, -1.8185027638193878], [30947, -1.8185027638193878], [30961, -1.8185027638193878], [30975, -1.8185027638193878], [30989, -1.8185027638193878], [31003, -1.8185027638193878], [31017, -1.8185027638193878], [31031, -1.8185027638193878], [31045, -1.8185027638193878], [32095, -1.8185027638193878], [32109, -1.8185027638193878], [32123, -1.8185027638193878], [32137, -1.8185027638193878], [32151, -1.8185027638193878], [32165, -1.8185027638193878], [32179, -1.8185027638193878], [32193, -1.8185027638193878], [32207, -1.8185027638193878], [32221, -1.8185027638193878], [32235, -1.8185027638193878], [32249, -1.8185027638193878], [32263, -1.818502763819388], [32277, -1.8185027638193878], [32305, -1.8185027638193878], [32319, -1.8185027638193878], [32333, -1.8185027638193878], [32347, -1.8185027638193878], [32361, -1.8185027638193878], [32375, -1.8185027638193878], [32389, -1.8185027638193878], [32403, -1.8185027638193878], [32417, -1.8185027638193878], [32431, -1.8185027638193878], [32445, -1.8185027638193878], [32571, -1.8185027638193878], [32585, -1.8185027638193878], [32599, -1.8185027638193878], [32613, -1.8185027638193878], [32627, -1.8185027638193878], [32641, -1.8185027638193878], [32655, -1.8185027638193878], [32851, -1.8185027638193878], [32865, -1.8185027638193878], [32879, -1.8185027638193878], [32893, -1.8185027638193878], [32907, -1.8185027638193878], [32921, -1.8185027638193878], [32991, -1.8185027638193878], [33005, -1.8185027638193878], [33019, -1.8185027638193878], [33033, -1.8185027638193878], [33047, -1.8185027638193878], [33061, -1.8505953931082257], [33075, -1.882688022397064], [33089, -1.882688022397064], [33103, -1.882688022397064], [33117, -1.882688022397064], [33131, -1.882688022397064], [33145, -1.882688022397064], [33159, -1.882688022397064], [33187, -1.882688022397064], [33201, -1.882688022397064], [33215, -1.8826880223970641], [33229, -1.8826880223970641], [33243, -1.8826880223970641], [33271, -1.882688022397064], [33285, -1.882688022397064], [33299, -1.8826880223970641], [33313, -1.882688022397064], [33327, -1.882688022397064], [33341, -1.882688022397064], [33355, -1.882688022397064], [33369, -1.882688022397064], [33383, -1.882688022397064], [33397, -1.882688022397064], [33411, -1.882688022397064], [33425, -1.882688022397064], [33439, -1.882688022397064], [33453, -1.882688022397064], [33467, -1.882688022397064], [33523, -1.882688022397064], [33537, -1.882688022397064], [33551, -1.882688022397064], [33649, -1.882688022397064], [33705, -1.882688022397064], [33719, -1.882688022397064], [33733, -1.882688022397064], [33747, -1.882688022397064], [33761, -1.882688022397064], [33775, -1.882688022397064], [33803, -1.882688022397064], [33817, -1.882688022397064], [33831, -1.882688022397064], [33845, -1.882688022397064], [34041, -1.882688022397064], [34055, -1.882688022397064], [34069, -1.882688022397064], [34083, -1.882688022397064], [34125, -1.882688022397064], [34139, -1.882688022397064], [34153, -1.882688022397064], [34167, -1.882688022397064]] \ No newline at end of file +[[28511, -1.9315717623933144], [29225, -1.8185027638193878], [29239, -1.8185027638193882], [29253, -1.8185027638193878], [29267, -1.8185027638193878], [29281, -1.8185027638193878], [29295, -1.8185027638193878], [29309, -1.8185027638193878], [29323, -1.8185027638193878], [29337, -1.8185027638193878], [29351, -1.8185027638193878], [29365, -1.8185027638193878], [29379, -1.8185027638193878], [29393, -1.8185027638193878], [29407, -1.8185027638193878], [29421, -1.8185027638193878], [29435, -1.8185027638193878], [29449, -1.8185027638193878], [29463, -1.818502763819388], [29477, -1.8185027638193878], [29547, -1.8185027638193878], [29561, -1.8185027638193878], [29575, -1.8185027638193878], [29603, -1.8185027638193878], [29617, -1.8185027638193878], [29631, -1.8185027638193878], [29645, -1.8185027638193878], [29659, -1.8185027638193878], [29673, -1.8185027638193878], [29743, -1.8185027638193878], [29757, -1.8185027638193878], [29771, -1.818502763819388], [29785, -1.8185027638193878], [29799, -1.818502763819388], [29813, -1.8185027638193878], [29827, -1.8185027638193878], [29841, -1.8185027638193878], [29855, -1.8185027638193878], [29869, -1.8185027638193878], [30009, -1.8185027638193878], [30023, -1.8185027638193878], [30037, -1.8185027638193878], [30051, -1.8185027638193878], [30065, -1.8185027638193878], [30079, -1.8185027638193882], [30093, -1.8185027638193878], [30107, -1.8185027638193878], [30121, -1.8185027638193878], [30135, -1.8185027638193878], [30149, -1.8185027638193878], [30163, -1.8185027638193878], [30177, -1.8185027638193878], [30191, -1.8185027638193878], [30205, -1.8185027638193878], [30219, -1.818502763819388], [30233, -1.8185027638193878], [30247, -1.8185027638193878], [30261, -1.8185027638193878], [30513, -1.818502763819388], [30527, -1.818502763819388], [30541, -1.8185027638193878], [30555, -1.818502763819388], [30569, -1.8185027638193878], [30583, -1.8185027638193878], [30597, -1.8185027638193878], [30625, -1.8185027638193878], [30639, -1.8185027638193878], [30653, -1.818502763819388], [30667, -1.8185027638193878], [30681, -1.8185027638193878], [30695, -1.8185027638193878], [30709, -1.8185027638193878], [30723, -1.8185027638193878], [30737, -1.8185027638193878], [30751, -1.8185027638193878], [30765, -1.8185027638193878], [30779, -1.8185027638193878], [30793, -1.8185027638193878], [30807, -1.8185027638193878], [30821, -1.8185027638193878], [30835, -1.8185027638193878], [30849, -1.8185027638193878], [30863, -1.8185027638193878], [30877, -1.8185027638193878], [30891, -1.8185027638193878], [30905, -1.8185027638193878], [30919, -1.8185027638193878], [30933, -1.8185027638193878], [30947, -1.8185027638193878], [30961, -1.8185027638193878], [30975, -1.8185027638193878], [30989, -1.8185027638193878], [31003, -1.8185027638193878], [31017, -1.8185027638193878], [31031, -1.8185027638193878], [31045, -1.8185027638193878], [32095, -1.8185027638193878], [32109, -1.8185027638193878], [32123, -1.8185027638193878], [32137, -1.8185027638193878], [32151, -1.8185027638193878], [32165, -1.8185027638193878], [32179, -1.8185027638193878], [32193, -1.8185027638193878], [32207, -1.8185027638193878], [32221, -1.8185027638193878], [32235, -1.8185027638193878], [32249, -1.8185027638193878], [32263, -1.818502763819388], [32277, -1.8185027638193878], [32305, -1.8185027638193878], [32319, -1.8185027638193878], [32333, -1.8185027638193878], [32347, -1.8185027638193878], [32361, -1.8185027638193878], [32375, -1.8185027638193878], [32389, -1.8185027638193878], [32403, -1.8185027638193878], [32417, -1.8185027638193878], [32431, -1.8185027638193878], [32445, -1.8185027638193878], [32571, -1.8185027638193878], [32585, -1.8185027638193878], [32599, -1.8185027638193878], [32613, -1.8185027638193878], [32627, -1.8185027638193878], [32641, -1.8185027638193878], [32655, -1.8185027638193878], [32851, -1.8185027638193878], [32865, -1.8185027638193878], [32879, -1.8185027638193878], [32893, -1.8185027638193878], [32907, -1.8185027638193878], [32921, -1.8185027638193878], [32991, -1.8185027638193878], [33005, -1.8185027638193878], [33019, -1.8185027638193878], [33033, -1.8185027638193878], [33047, -1.8185027638193878], [33061, -1.8505953931082257], [33075, -1.882688022397064], [33089, -1.882688022397064], [33103, -1.882688022397064], [33117, -1.882688022397064], [33131, -1.882688022397064], [33145, -1.882688022397064], [33159, -1.882688022397064], [33187, -1.882688022397064], [33201, -1.882688022397064], [33215, -1.8826880223970641], [33229, -1.8826880223970641], [33243, -1.8826880223970641], [33271, -1.882688022397064], [33285, -1.882688022397064], [33299, -1.8826880223970641], [33313, -1.882688022397064], [33327, -1.882688022397064], [33341, -1.882688022397064], [33355, -1.882688022397064], [33369, -1.882688022397064], [33383, -1.882688022397064], [33397, -1.882688022397064], [33411, -1.882688022397064], [33425, -1.882688022397064], [33439, -1.882688022397064], [33453, -1.882688022397064], [33467, -1.882688022397064], [33523, -1.882688022397064], [33537, -1.882688022397064], [33551, -1.882688022397064], [33649, -1.882688022397064], [33705, -1.882688022397064], [33719, -1.882688022397064], [33733, -1.882688022397064], [33747, -1.882688022397064], [33761, -1.882688022397064], [33775, -1.882688022397064], [33803, -1.882688022397064], [33817, -1.882688022397064], [33831, -1.882688022397064], [33845, -1.882688022397064], [34041, -1.882688022397064], [34055, -1.882688022397064], [34069, -1.882688022397064], [34083, -1.882688022397064], [34125, -1.882688022397064], [34139, -1.882688022397064], [34153, -1.882688022397064], [34167, -1.8826880223970641]] \ No newline at end of file diff --git a/graphs/summary/decomposition.DictionaryLearningBenchmark.peakmem_fit.json b/graphs/summary/decomposition.DictionaryLearningBenchmark.peakmem_fit.json index 575478128b..6454a39f8a 100644 --- a/graphs/summary/decomposition.DictionaryLearningBenchmark.peakmem_fit.json +++ b/graphs/summary/decomposition.DictionaryLearningBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 120775135.73218125], [29225, 124589830.52587606], [29239, 124789441.52373028], [29253, 125556613.26679198], [29267, 126057482.99778935], [29281, 125678021.30430353], [29295, 125930561.31038018], [29309, 125576331.44623278], [29323, 125949975.66571073], [29337, 125633733.80129044], [29351, 125317106.2243238], [29365, 125019838.25592315], [29379, 125232873.85027052], [29393, 124862706.15555845], [29407, 125037146.99867097], [29421, 124824687.12513828], [29435, 125553677.21785372], [29449, 124287068.5793855], [29463, 124425409.90011093], [29477, 124367164.76554081], [29547, 124591654.34088838], [29561, 124637606.0233419], [29575, 124122885.75289284], [29603, 124925047.02634066], [29617, 125231725.16751075], [29631, 125330136.3665328], [29645, 125513548.25120372], [29659, 125390667.21562654], [29673, 125318442.00867724], [29743, 125236985.5407615], [29757, 125158779.63407451], [29771, 125361191.34456399], [29785, 125455202.77706632], [29799, 125295931.50012454], [29813, 125322400.01143424], [29827, 125807826.93054958], [29841, 125305766.50933015], [29855, 125046686.67862663], [29869, 125887197.99534151], [30009, 125436540.1528698], [30023, 125259436.12115514], [30037, 125274369.32393426], [30051, 125465306.98135649], [30065, 125326432.86741397], [30079, 125381866.23253812], [30093, 125294600.78735572], [30107, 125314212.10636918], [30121, 125284833.82297234], [30135, 125128123.02670366], [30149, 125593223.86688024], [30163, 125591924.60871457], [30177, 125594634.18695009], [30191, 125652016.69262345], [30205, 125827248.85502316], [30219, 125816893.07956879], [30233, 125521892.22064869], [30247, 125857165.15270951], [30261, 125505229.14334619], [30513, 123044013.41287854], [30527, 122052394.29705524], [30541, 121997019.03067426], [30555, 122013731.46073474], [30569, 122006736.35228689], [30583, 122225000.01042855], [30597, 121990842.76592815], [30625, 122007647.39694147], [30639, 122243359.95729098], [30653, 122100718.33276053], [30667, 122009559.62979394], [30681, 121934023.83791381], [30695, 122200514.11115794], [30709, 121981685.20057625], [30723, 121748868.56312385], [30737, 122167082.72216104], [30751, 122188748.5730898], [30765, 122518537.24704719], [30779, 121886735.63209838], [30793, 122014090.627106], [30807, 122075325.794215], [30821, 122087366.45243901], [30835, 122562629.85408215], [30849, 122290532.35469046], [30863, 122141321.21799643], [30877, 122327027.43637197], [30891, 122356285.70348497], [30905, 122320118.22791329], [30919, 122235067.32276557], [30933, 122006730.3968985], [30947, 122066747.13227266], [30961, 122091699.3258404], [30975, 122432632.26060742], [30989, 122442373.01648013], [31003, 122587944.58966851], [31017, 122371489.36821614], [31031, 122149984.66838755], [31045, 122124105.66150731], [32095, 134396920.76820028], [32109, 134166435.86038265], [32123, 134203352.26253612], [32137, 134308712.15144438], [32151, 134246672.10493398], [32165, 134305976.17360803], [32179, 134196672.38923763], [32193, 134221763.19638327], [32207, 135529809.69887042], [32221, 136772111.68082124], [32235, 136948788.70559078], [32249, 136566838.24046692], [32263, 136709437.42360118], [32277, 136881195.17371657], [32305, 138426371.24111554], [32319, 142051093.11770615], [32333, 141979166.32965142], [32347, 141970574.98696765], [32361, 142063066.43080813], [32375, 141907782.26421848], [32389, 141961955.8909665], [32403, 142139537.91911206], [32417, 142093061.68034625], [32431, 142115044.56649542], [32445, 142294278.64739537], [32585, 139973266.34721565], [32599, 140100761.8867155], [32613, 139978017.92550752], [32627, 139949292.00560477], [32641, 139912927.3029617], [32655, 139981814.96105218], [32851, 141109733.1163775], [32865, 140980277.0069291], [32879, 141309020.65818813], [32893, 141237904.55555502], [32907, 141193080.05491793], [32921, 141188793.98793638], [32991, 141073139.87461585], [33005, 141033802.46682957], [33019, 140666736.46256956], [33033, 141156670.98738107], [33047, 141071579.62876803], [33061, 141248021.1800757], [33075, 141260503.48818687], [33089, 155797629.87633756], [33103, 170357538.9150876], [33117, 170419700.19599932], [33131, 170228977.19951636], [33145, 170521570.68154728], [33159, 170558851.17145625], [33187, 141526974.6593886], [33201, 141404053.4737066], [33215, 138907413.71217263], [33229, 131603031.8473512], [33243, 131532386.48094413], [33271, 121608576.05691388], [33299, 122018913.2644357], [33313, 121548942.55378632], [33327, 121762428.4936247], [33341, 121848486.62450661], [33355, 122098900.40699162], [33369, 122649069.17917024], [33383, 122969476.7851062], [33397, 123315228.24377951], [33411, 123196870.342623], [33425, 123397507.75227728], [33439, 124407321.26226854], [33453, 119290351.02352276], [33467, 119699198.40763287], [33523, 119243031.57891369], [33537, 119279537.59949248], [33551, 119029736.07353], [33649, 118335881.24742308], [33705, 117457551.00827983], [33719, 117656200.52775043], [33733, 117990557.17084584], [33747, 117934056.52555066], [33761, 117956431.88423295], [33775, 117959433.07039006], [33803, 117991680.98362023], [33817, 117401321.74063924], [33831, 117691407.44349511], [33845, 117390201.15399723], [34041, 117198181.98275177], [34055, 117553480.34969445], [34069, 117574130.95888896], [34083, 117436217.52332854], [34125, 117564415.82908799], [34139, 118028691.37717743], [34153, 117503600.68892948], [34167, 117574832.53785631]] \ No newline at end of file +[[28511, 120775135.73218125], [29225, 124589830.52587606], [29239, 124789441.52373028], [29253, 125556613.26679198], [29267, 126057482.99778935], [29281, 125678021.30430353], [29295, 125930561.31038018], [29309, 125576331.44623278], [29323, 125949975.66571073], [29337, 125633733.80129044], [29351, 125317106.2243238], [29365, 125019838.25592315], [29379, 125232873.85027052], [29393, 124862706.15555845], [29407, 125037146.99867097], [29421, 124824687.12513828], [29435, 125553677.21785372], [29449, 124287068.5793855], [29463, 124425409.90011093], [29477, 124367164.76554081], [29547, 124591654.34088838], [29561, 124637606.0233419], [29575, 124122885.75289284], [29603, 124925047.02634066], [29617, 125231725.16751075], [29631, 125330136.3665328], [29645, 125513548.25120372], [29659, 125390667.21562654], [29673, 125318442.00867724], [29743, 125236985.5407615], [29757, 125158779.63407451], [29771, 125361191.34456399], [29785, 125455202.77706632], [29799, 125295931.50012454], [29813, 125322400.01143424], [29827, 125807826.93054958], [29841, 125305766.50933015], [29855, 125046686.67862663], [29869, 125887197.99534151], [30009, 125436540.1528698], [30023, 125259436.12115514], [30037, 125274369.32393426], [30051, 125465306.98135649], [30065, 125326432.86741397], [30079, 125381866.23253812], [30093, 125294600.78735572], [30107, 125314212.10636918], [30121, 125284833.82297234], [30135, 125128123.02670366], [30149, 125593223.86688024], [30163, 125591924.60871457], [30177, 125594634.18695009], [30191, 125652016.69262345], [30205, 125827248.85502316], [30219, 125816893.07956879], [30233, 125521892.22064869], [30247, 125857165.15270951], [30261, 125505229.14334619], [30513, 123044013.41287854], [30527, 122052394.29705524], [30541, 121997019.03067426], [30555, 122013731.46073474], [30569, 122006736.35228689], [30583, 122225000.01042855], [30597, 121990842.76592815], [30625, 122007647.39694147], [30639, 122243359.95729098], [30653, 122100718.33276053], [30667, 122009559.62979394], [30681, 121934023.83791381], [30695, 122200514.11115794], [30709, 121981685.20057625], [30723, 121748868.56312385], [30737, 122167082.72216104], [30751, 122188748.5730898], [30765, 122518537.24704719], [30779, 121886735.63209838], [30793, 122014090.627106], [30807, 122075325.794215], [30821, 122087366.45243901], [30835, 122562629.85408215], [30849, 122290532.35469046], [30863, 122141321.21799643], [30877, 122327027.43637197], [30891, 122356285.70348497], [30905, 122320118.22791329], [30919, 122235067.32276557], [30933, 122006730.3968985], [30947, 122066747.13227266], [30961, 122091699.3258404], [30975, 122432632.26060742], [30989, 122442373.01648013], [31003, 122587944.58966851], [31017, 122371489.36821614], [31031, 122149984.66838755], [31045, 122124105.66150731], [32095, 134396920.76820028], [32109, 134166435.86038265], [32123, 134203352.26253612], [32137, 134308712.15144438], [32151, 134246672.10493398], [32165, 134305976.17360803], [32179, 134196672.38923763], [32193, 134221763.19638327], [32207, 135529809.69887042], [32221, 136772111.68082124], [32235, 136948788.70559078], [32249, 136566838.24046692], [32263, 136709437.42360118], [32277, 136881195.17371657], [32305, 138426371.24111554], [32319, 142051093.11770615], [32333, 141979166.32965142], [32347, 141970574.98696765], [32361, 142063066.43080813], [32375, 141907782.26421848], [32389, 141961955.8909665], [32403, 142139537.91911206], [32417, 142093061.68034625], [32431, 142115044.56649542], [32445, 142294278.64739537], [32585, 139973266.34721565], [32599, 140100761.8867155], [32613, 139978017.92550752], [32627, 139949292.00560477], [32641, 139912927.3029617], [32655, 139981814.96105218], [32851, 141109733.1163775], [32865, 140980277.0069291], [32879, 141309020.65818813], [32893, 141237904.55555502], [32907, 141193080.05491793], [32921, 141188793.98793638], [32991, 141073139.87461585], [33005, 141033802.46682957], [33019, 140666736.46256956], [33033, 141156670.98738107], [33047, 141071579.62876803], [33061, 141248021.1800757], [33075, 141260503.48818687], [33089, 155797629.87633756], [33103, 170357538.9150876], [33117, 170419700.19599932], [33131, 170228977.19951636], [33145, 170521570.68154728], [33159, 170558851.17145625], [33187, 141526974.6593886], [33201, 141404053.4737066], [33215, 138907413.71217263], [33229, 131603031.8473512], [33243, 131532386.48094413], [33271, 121608576.05691388], [33299, 122018913.2644357], [33313, 121548942.55378632], [33327, 121762428.4936247], [33341, 121848486.62450661], [33355, 122098900.40699162], [33369, 122649069.17917024], [33383, 122969476.7851062], [33397, 123315228.24377951], [33411, 123196870.342623], [33425, 123397507.75227728], [33439, 124407321.26226854], [33453, 119290351.02352276], [33467, 119699198.40763287], [33523, 119243031.57891369], [33537, 119279537.59949248], [33551, 119029736.07353], [33649, 118335881.24742308], [33705, 117457551.00827983], [33719, 117656200.52775043], [33733, 117990557.17084584], [33747, 117934056.52555066], [33761, 117956431.88423295], [33775, 117959433.07039006], [33803, 117991680.98362023], [33817, 117401321.74063924], [33831, 117691407.44349511], [33845, 117390201.15399723], [34041, 117198181.98275177], [34055, 117553480.34969445], [34069, 117574130.95888896], [34083, 117436217.52332854], [34125, 117564415.82908799], [34139, 118028691.37717743], [34153, 117503600.68892948], [34167, 117538609.48437977]] \ No newline at end of file diff --git a/graphs/summary/decomposition.DictionaryLearningBenchmark.peakmem_transform.json b/graphs/summary/decomposition.DictionaryLearningBenchmark.peakmem_transform.json index 81681faa3b..2339958386 100644 --- a/graphs/summary/decomposition.DictionaryLearningBenchmark.peakmem_transform.json +++ b/graphs/summary/decomposition.DictionaryLearningBenchmark.peakmem_transform.json @@ -1 +1 @@ -[[28511, 88881954.15433522], [29225, 86241807.04629318], [29239, 86102793.12874818], [29253, 86532642.39362739], [29267, 86422442.37622279], [29281, 86424425.65801322], [29295, 86736346.58165337], [29309, 86340443.25917417], [29323, 86393277.3631002], [29337, 86540807.12747487], [29351, 85743468.36130829], [29365, 85804639.7578843], [29379, 86190886.63279372], [29393, 85867859.9408278], [29407, 86070564.71026456], [29421, 85677259.55321585], [29435, 86128205.3624901], [29449, 85867044.54879455], [29463, 85473474.02043532], [29477, 85655686.52492614], [29547, 86279249.48932764], [29561, 85743677.43989639], [29575, 85761885.0900848], [29603, 86355985.38169655], [29617, 86657055.54347473], [29631, 86432475.50906365], [29645, 86853793.50312255], [29659, 86620396.5970411], [29673, 86451064.76331352], [29743, 86529886.3596971], [29757, 86777041.373301], [29771, 86697148.14382872], [29785, 86877281.00718331], [29799, 86568630.5099763], [29813, 86855815.97970115], [29827, 86876653.96981663], [29841, 86703307.82125814], [29855, 86690584.0390236], [29869, 86933292.39758681], [30009, 86641520.63035613], [30023, 86791499.06271951], [30037, 86499521.81706826], [30051, 86460072.63051014], [30065, 86267046.79496254], [30079, 86855563.97234309], [30093, 86721460.07461664], [30107, 86739602.69332846], [30121, 86847968.38963409], [30135, 86408262.16098732], [30149, 86933442.03342728], [30163, 87063979.13987137], [30177, 87316820.52475698], [30191, 87125567.18108243], [30205, 87170599.28467791], [30219, 86986054.33899274], [30233, 86934632.03133737], [30247, 87096466.48901846], [30261, 87096081.7154678], [30513, 87216886.07112941], [30527, 86971539.78787147], [30541, 87116576.06225128], [30555, 87022773.03537013], [30569, 86875267.89857638], [30583, 87279519.69349176], [30597, 86812736.44992545], [30625, 86924724.06014782], [30639, 86854893.86507276], [30653, 87006773.66580768], [30667, 86691763.99861686], [30681, 86782691.05953194], [30695, 87218940.03225642], [30709, 86779573.43777807], [30723, 86953211.35165581], [30737, 87075074.42531493], [30751, 87121747.15702969], [30765, 87357024.421224], [30779, 86915691.07071331], [30793, 86724543.9301911], [30807, 86848408.38156265], [30821, 87028475.76357642], [30835, 87007190.96838476], [30849, 87173945.92305176], [30863, 87357909.80991805], [30877, 87266539.50127512], [30891, 87566293.51471096], [30905, 87541044.67480934], [30919, 87257309.78585462], [30933, 87014889.28883103], [30947, 87115928.6266059], [30961, 87057719.6287943], [30975, 87146780.05465926], [30989, 87218912.79152782], [31003, 87554315.10364945], [31017, 87410080.83783007], [31031, 86596334.85290347], [31045, 86966756.00003979], [32095, 99086157.3208295], [32109, 98767103.25796922], [32123, 98718417.08715308], [32137, 98843316.95548749], [32151, 98813437.4165223], [32165, 98660384.9527629], [32179, 98612604.32404171], [32193, 98880993.09974234], [32207, 99885548.30742422], [32221, 101152827.41736825], [32235, 101552767.09410852], [32249, 101226377.49198452], [32263, 101121742.4988673], [32277, 101029244.43918443], [32305, 103099782.20754154], [32319, 106843517.96314204], [32333, 106808786.44331838], [32347, 106779833.33220991], [32361, 106796448.75713158], [32375, 107012316.75958428], [32389, 106847501.90175596], [32403, 106677091.87614512], [32417, 106842601.07107644], [32431, 107072704.75963001], [32445, 107140568.7520435], [32585, 104877255.74604368], [32599, 104832943.01357977], [32613, 104712218.99474947], [32627, 104707555.216925], [32641, 104408353.89039133], [32655, 104670039.80422346], [32851, 105637011.97771394], [32865, 105756602.50575355], [32879, 105780308.4529429], [32893, 106143304.57463372], [32907, 105816846.37941116], [32921, 105755424.72202858], [32991, 105830929.07325712], [33005, 105817048.10892518], [33019, 105374481.54353204], [33033, 105609249.99857715], [33047, 105918929.65131608], [33061, 106111238.88614716], [33075, 105643862.97286068], [33089, 120138528.6194984], [33103, 134958501.32148007], [33117, 135259999.12356466], [33131, 134994881.07316792], [33145, 134993648.3102795], [33159, 135002677.69180572], [33187, 106152594.23545071], [33201, 106006190.39850774], [33215, 103882791.1383657], [33229, 97741818.49004817], [33243, 97817142.53331542], [33271, 90127959.90879251], [33299, 90361833.2557879], [33313, 90148132.37763695], [33327, 90570558.08305201], [33341, 90470133.86419614], [33355, 90709209.39737089], [33369, 91077194.36175583], [33383, 91374975.50890018], [33397, 91746413.50023776], [33411, 91813125.19920157], [33425, 91815260.32094611], [33439, 92852461.63943614], [33453, 88000404.28406493], [33467, 88084161.63327725], [33523, 88106534.63172963], [33537, 88151949.18292361], [33551, 87566632.78325742], [33649, 86841440.38474676], [33705, 86474414.0288962], [33719, 86476833.191324], [33733, 86667187.03139962], [33747, 86501775.22637591], [33761, 86391288.46218006], [33775, 86424694.17878091], [33803, 86497047.25729838], [33817, 86279424.95367298], [33831, 86408006.38821022], [33845, 86249237.99255905], [34041, 85995324.42330675], [34055, 86295284.77732778], [34069, 86221864.95557246], [34083, 86056305.13608295], [34125, 86107052.43149], [34139, 86472136.47276048], [34153, 86193024.57351248], [34167, 86147422.3703579]] \ No newline at end of file +[[28511, 88881954.15433522], [29225, 86241807.04629318], [29239, 86102793.12874818], [29253, 86532642.39362739], [29267, 86422442.37622279], [29281, 86424425.65801322], [29295, 86736346.58165337], [29309, 86340443.25917417], [29323, 86393277.3631002], [29337, 86540807.12747487], [29351, 85743468.36130829], [29365, 85804639.7578843], [29379, 86190886.63279372], [29393, 85867859.9408278], [29407, 86070564.71026456], [29421, 85677259.55321585], [29435, 86128205.3624901], [29449, 85867044.54879455], [29463, 85473474.02043532], [29477, 85655686.52492614], [29547, 86279249.48932764], [29561, 85743677.43989639], [29575, 85761885.0900848], [29603, 86355985.38169655], [29617, 86657055.54347473], [29631, 86432475.50906365], [29645, 86853793.50312255], [29659, 86620396.5970411], [29673, 86451064.76331352], [29743, 86529886.3596971], [29757, 86777041.373301], [29771, 86697148.14382872], [29785, 86877281.00718331], [29799, 86568630.5099763], [29813, 86855815.97970115], [29827, 86876653.96981663], [29841, 86703307.82125814], [29855, 86690584.0390236], [29869, 86933292.39758681], [30009, 86641520.63035613], [30023, 86791499.06271951], [30037, 86499521.81706826], [30051, 86460072.63051014], [30065, 86267046.79496254], [30079, 86855563.97234309], [30093, 86721460.07461664], [30107, 86739602.69332846], [30121, 86847968.38963409], [30135, 86408262.16098732], [30149, 86933442.03342728], [30163, 87063979.13987137], [30177, 87316820.52475698], [30191, 87125567.18108243], [30205, 87170599.28467791], [30219, 86986054.33899274], [30233, 86934632.03133737], [30247, 87096466.48901846], [30261, 87096081.7154678], [30513, 87216886.07112941], [30527, 86971539.78787147], [30541, 87116576.06225128], [30555, 87022773.03537013], [30569, 86875267.89857638], [30583, 87279519.69349176], [30597, 86812736.44992545], [30625, 86924724.06014782], [30639, 86854893.86507276], [30653, 87006773.66580768], [30667, 86691763.99861686], [30681, 86782691.05953194], [30695, 87218940.03225642], [30709, 86779573.43777807], [30723, 86953211.35165581], [30737, 87075074.42531493], [30751, 87121747.15702969], [30765, 87357024.421224], [30779, 86915691.07071331], [30793, 86724543.9301911], [30807, 86848408.38156265], [30821, 87028475.76357642], [30835, 87007190.96838476], [30849, 87173945.92305176], [30863, 87357909.80991805], [30877, 87266539.50127512], [30891, 87566293.51471096], [30905, 87541044.67480934], [30919, 87257309.78585462], [30933, 87014889.28883103], [30947, 87115928.6266059], [30961, 87057719.6287943], [30975, 87146780.05465926], [30989, 87218912.79152782], [31003, 87554315.10364945], [31017, 87410080.83783007], [31031, 86596334.85290347], [31045, 86966756.00003979], [32095, 99086157.3208295], [32109, 98767103.25796922], [32123, 98718417.08715308], [32137, 98843316.95548749], [32151, 98813437.4165223], [32165, 98660384.9527629], [32179, 98612604.32404171], [32193, 98880993.09974234], [32207, 99885548.30742422], [32221, 101152827.41736825], [32235, 101552767.09410852], [32249, 101226377.49198452], [32263, 101121742.4988673], [32277, 101029244.43918443], [32305, 103099782.20754154], [32319, 106843517.96314204], [32333, 106808786.44331838], [32347, 106779833.33220991], [32361, 106796448.75713158], [32375, 107012316.75958428], [32389, 106847501.90175596], [32403, 106677091.87614512], [32417, 106842601.07107644], [32431, 107072704.75963001], [32445, 107140568.7520435], [32585, 104877255.74604368], [32599, 104832943.01357977], [32613, 104712218.99474947], [32627, 104707555.216925], [32641, 104408353.89039133], [32655, 104670039.80422346], [32851, 105637011.97771394], [32865, 105756602.50575355], [32879, 105780308.4529429], [32893, 106143304.57463372], [32907, 105816846.37941116], [32921, 105755424.72202858], [32991, 105830929.07325712], [33005, 105817048.10892518], [33019, 105374481.54353204], [33033, 105609249.99857715], [33047, 105918929.65131608], [33061, 106111238.88614716], [33075, 105643862.97286068], [33089, 120138528.6194984], [33103, 134958501.32148007], [33117, 135259999.12356466], [33131, 134994881.07316792], [33145, 134993648.3102795], [33159, 135002677.69180572], [33187, 106152594.23545071], [33201, 106006190.39850774], [33215, 103882791.1383657], [33229, 97741818.49004817], [33243, 97817142.53331542], [33271, 90127959.90879251], [33299, 90361833.2557879], [33313, 90148132.37763695], [33327, 90570558.08305201], [33341, 90470133.86419614], [33355, 90709209.39737089], [33369, 91077194.36175583], [33383, 91374975.50890018], [33397, 91746413.50023776], [33411, 91813125.19920157], [33425, 91815260.32094611], [33439, 92852461.63943614], [33453, 88000404.28406493], [33467, 88084161.63327725], [33523, 88106534.63172963], [33537, 88151949.18292361], [33551, 87566632.78325742], [33649, 86841440.38474676], [33705, 86474414.0288962], [33719, 86476833.191324], [33733, 86667187.03139962], [33747, 86501775.22637591], [33761, 86391288.46218006], [33775, 86424694.17878091], [33803, 86497047.25729838], [33817, 86279424.95367298], [33831, 86408006.38821022], [33845, 86249237.99255905], [34041, 85995324.42330675], [34055, 86295284.77732778], [34069, 86221864.95557246], [34083, 86056305.13608295], [34125, 86107052.43149], [34139, 86472136.47276048], [34153, 86193024.57351248], [34167, 86124072.89803337]] \ No newline at end of file diff --git a/graphs/summary/decomposition.DictionaryLearningBenchmark.time_fit.json b/graphs/summary/decomposition.DictionaryLearningBenchmark.time_fit.json index 89f73c9792..372c44ff78 100644 --- a/graphs/summary/decomposition.DictionaryLearningBenchmark.time_fit.json +++ b/graphs/summary/decomposition.DictionaryLearningBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 4.464774934549746], [29225, 5.842319418398422], [29239, 5.656906508814271], [29253, 4.215566671138622], [29267, 4.305392635631548], [29281, 4.176969224951028], [29295, 4.230638006331424], [29309, 4.298424500803375], [29323, 4.249889488072557], [29337, 4.285685714534177], [29351, 4.223477879865559], [29365, 4.290712326488105], [29379, 4.289428904882113], [29393, 4.228990405827992], [29407, 4.200870307132782], [29421, 4.27605175204598], [29435, 4.223834874422695], [29449, 5.766719510650314], [29463, 5.964269211140705], [29477, 5.785747171808842], [29547, 6.0096283142077], [29561, 5.789882418959027], [29575, 5.558118921861694], [29603, 5.196699441297686], [29617, 5.356850140925438], [29631, 5.402829660650428], [29645, 5.1939761119240355], [29659, 5.218806897005562], [29673, 5.308323546982321], [29743, 5.468447599566511], [29757, 5.198926565843228], [29771, 5.194391588326799], [29785, 5.822429256923204], [29799, 5.797165644681199], [29813, 5.563729949131522], [29827, 5.955675978542885], [29841, 5.8082380393483755], [29855, 5.948366508966068], [29869, 5.784337570949562], [30009, 5.964726997764626], [30023, 5.863316360117086], [30037, 5.74249505998732], [30051, 5.84839476567403], [30065, 5.810848720991911], [30079, 5.721085523525846], [30093, 5.957542765577509], [30107, 5.718278927669331], [30121, 5.703064778780706], [30135, 5.557575446904899], [30149, 5.687011855586646], [30163, 5.932793497274577], [30177, 5.949222025318935], [30191, 5.817785773980491], [30205, 5.9201828055238], [30219, 5.841912274438256], [30233, 5.88979848540753], [30247, 5.97363383831635], [30261, 5.825043214414368], [30513, 5.384480479242765], [30527, 5.0823760421924336], [30541, 5.139897451322791], [30555, 5.194938961044909], [30569, 5.243069301137934], [30583, 5.360543929593406], [30597, 5.205152337473637], [30625, 5.268028913207143], [30639, 5.266615400779084], [30653, 5.212219923890558], [30667, 5.179102746181475], [30681, 5.263147860014168], [30695, 5.326568834124681], [30709, 5.2720446928373175], [30723, 5.267571564056002], [30737, 5.364944160558389], [30751, 5.242332440364524], [30765, 5.331180412501192], [30779, 5.096982770298995], [30793, 5.296536268916921], [30807, 5.329144813683547], [30821, 5.237042327695347], [30835, 5.367407360337696], [30849, 5.115548315892829], [30863, 5.092739582119764], [30877, 5.277076690020673], [30891, 5.282800076987656], [30905, 5.438628414727567], [30919, 5.247148658191069], [30933, 5.218578755566114], [30947, 5.120843217944123], [30961, 5.197186247992162], [30975, 5.1441044804494815], [30989, 4.886169446212717], [31003, 4.9049680924772865], [31017, 4.895848726079496], [31031, 5.3126915364247775], [31045, 5.0158490826278035], [32095, 4.948179907801169], [32109, 5.04457540706829], [32123, 5.013507070468597], [32137, 5.042733554083395], [32151, 5.041164869637752], [32165, 5.034772539182834], [32179, 4.816283246217479], [32193, 5.068856395377328], [32207, 4.858931451781857], [32221, 4.800786303414859], [32235, 4.652945421201038], [32249, 4.483285826265764], [32263, 4.817681260173022], [32277, 4.852398679846616], [32305, 4.736694723212178], [32319, 4.725408707883719], [32333, 4.784262552157444], [32347, 4.653963012965619], [32361, 4.859686902989804], [32375, 4.9189812710204395], [32389, 4.983957818154725], [32403, 5.042488864192267], [32417, 4.587956148120633], [32431, 4.644564776868297], [32445, 4.856042576226571], [32585, 4.445179222406875], [32599, 4.759937628686141], [32613, 4.728402525069559], [32627, 4.56477732456519], [32641, 4.747591712634277], [32655, 4.636811223710417], [32851, 4.508259566605832], [32865, 4.55136728960548], [32879, 4.598379428242718], [32893, 4.725562897322572], [32907, 4.723030509752442], [32921, 4.638277705871197], [32991, 4.713280796722888], [33005, 4.836276623363548], [33019, 4.763657286131984], [33033, 4.919304430257953], [33047, 4.582626399207612], [33061, 4.805865495769388], [33075, 4.668583821039428], [33089, 4.852159938160316], [33103, 4.777052454949873], [33117, 4.597830075617191], [33131, 4.844345203661568], [33145, 4.927675670992627], [33159, 4.825885119949556], [33187, 4.951269758294784], [33201, 4.735794599239772], [33215, 4.902249970594423], [33229, 4.870347731734478], [33243, 4.713479737275468], [33271, 4.647930651956005], [33299, 5.07614439696048], [33313, 4.692503781569666], [33327, 4.708481032704473], [33341, 4.640361942948146], [33355, 4.656266995845335], [33369, 4.574153434108417], [33383, 4.5820499167766995], [33397, 4.667048606706587], [33411, 4.494288088646385], [33425, 4.475705597749297], [33439, 4.409848363658536], [33453, 4.57997356840816], [33467, 4.603592714531504], [33523, 4.7442181619662485], [33537, 4.697076682201888], [33551, 4.6730223215897695], [33649, 4.8641830671848405], [33705, 4.789446822948693], [33719, 4.646914719261459], [33733, 4.795643669339368], [33747, 4.668638442948616], [33761, 4.7605663337048005], [33775, 4.610555241886031], [33803, 4.530525963835414], [33817, 4.645010098120565], [33831, 4.678209157864934], [33845, 4.843722661934962], [34041, 4.771044470307012], [34055, 4.513210739357548], [34069, 4.5112494523638915], [34083, 4.644337839766419], [34125, 4.551520749482118], [34139, 4.73685454330348], [34153, 4.5005188904202535], [34167, 4.604201434206401]] \ No newline at end of file +[[28511, 4.464774934549746], [29225, 5.842319418398422], [29239, 5.656906508814271], [29253, 4.215566671138622], [29267, 4.305392635631548], [29281, 4.176969224951028], [29295, 4.230638006331424], [29309, 4.298424500803375], [29323, 4.249889488072557], [29337, 4.285685714534177], [29351, 4.223477879865559], [29365, 4.290712326488105], [29379, 4.289428904882113], [29393, 4.228990405827992], [29407, 4.200870307132782], [29421, 4.27605175204598], [29435, 4.223834874422695], [29449, 5.766719510650314], [29463, 5.964269211140705], [29477, 5.785747171808842], [29547, 6.0096283142077], [29561, 5.789882418959027], [29575, 5.558118921861694], [29603, 5.196699441297686], [29617, 5.356850140925438], [29631, 5.402829660650428], [29645, 5.1939761119240355], [29659, 5.218806897005562], [29673, 5.308323546982321], [29743, 5.468447599566511], [29757, 5.198926565843228], [29771, 5.194391588326799], [29785, 5.822429256923204], [29799, 5.797165644681199], [29813, 5.563729949131522], [29827, 5.955675978542885], [29841, 5.8082380393483755], [29855, 5.948366508966068], [29869, 5.784337570949562], [30009, 5.964726997764626], [30023, 5.863316360117086], [30037, 5.74249505998732], [30051, 5.84839476567403], [30065, 5.810848720991911], [30079, 5.721085523525846], [30093, 5.957542765577509], [30107, 5.718278927669331], [30121, 5.703064778780706], [30135, 5.557575446904899], [30149, 5.687011855586646], [30163, 5.932793497274577], [30177, 5.949222025318935], [30191, 5.817785773980491], [30205, 5.9201828055238], [30219, 5.841912274438256], [30233, 5.88979848540753], [30247, 5.97363383831635], [30261, 5.825043214414368], [30513, 5.384480479242765], [30527, 5.0823760421924336], [30541, 5.139897451322791], [30555, 5.194938961044909], [30569, 5.243069301137934], [30583, 5.360543929593406], [30597, 5.205152337473637], [30625, 5.268028913207143], [30639, 5.266615400779084], [30653, 5.212219923890558], [30667, 5.179102746181475], [30681, 5.263147860014168], [30695, 5.326568834124681], [30709, 5.2720446928373175], [30723, 5.267571564056002], [30737, 5.364944160558389], [30751, 5.242332440364524], [30765, 5.331180412501192], [30779, 5.096982770298995], [30793, 5.296536268916921], [30807, 5.329144813683547], [30821, 5.237042327695347], [30835, 5.367407360337696], [30849, 5.115548315892829], [30863, 5.092739582119764], [30877, 5.277076690020673], [30891, 5.282800076987656], [30905, 5.438628414727567], [30919, 5.247148658191069], [30933, 5.218578755566114], [30947, 5.120843217944123], [30961, 5.197186247992162], [30975, 5.1441044804494815], [30989, 4.886169446212717], [31003, 4.9049680924772865], [31017, 4.895848726079496], [31031, 5.3126915364247775], [31045, 5.0158490826278035], [32095, 4.948179907801169], [32109, 5.04457540706829], [32123, 5.013507070468597], [32137, 5.042733554083395], [32151, 5.041164869637752], [32165, 5.034772539182834], [32179, 4.816283246217479], [32193, 5.068856395377328], [32207, 4.858931451781857], [32221, 4.800786303414859], [32235, 4.652945421201038], [32249, 4.483285826265764], [32263, 4.817681260173022], [32277, 4.852398679846616], [32305, 4.736694723212178], [32319, 4.725408707883719], [32333, 4.784262552157444], [32347, 4.653963012965619], [32361, 4.859686902989804], [32375, 4.9189812710204395], [32389, 4.983957818154725], [32403, 5.042488864192267], [32417, 4.587956148120633], [32431, 4.644564776868297], [32445, 4.856042576226571], [32585, 4.445179222406875], [32599, 4.759937628686141], [32613, 4.728402525069559], [32627, 4.56477732456519], [32641, 4.747591712634277], [32655, 4.636811223710417], [32851, 4.508259566605832], [32865, 4.55136728960548], [32879, 4.598379428242718], [32893, 4.725562897322572], [32907, 4.723030509752442], [32921, 4.638277705871197], [32991, 4.713280796722888], [33005, 4.836276623363548], [33019, 4.763657286131984], [33033, 4.919304430257953], [33047, 4.582626399207612], [33061, 4.805865495769388], [33075, 4.668583821039428], [33089, 4.852159938160316], [33103, 4.777052454949873], [33117, 4.597830075617191], [33131, 4.844345203661568], [33145, 4.927675670992627], [33159, 4.825885119949556], [33187, 4.951269758294784], [33201, 4.735794599239772], [33215, 4.902249970594423], [33229, 4.870347731734478], [33243, 4.713479737275468], [33271, 4.647930651956005], [33299, 5.07614439696048], [33313, 4.692503781569666], [33327, 4.708481032704473], [33341, 4.640361942948146], [33355, 4.656266995845335], [33369, 4.574153434108417], [33383, 4.5820499167766995], [33397, 4.667048606706587], [33411, 4.494288088646385], [33425, 4.475705597749297], [33439, 4.409848363658536], [33453, 4.57997356840816], [33467, 4.603592714531504], [33523, 4.7442181619662485], [33537, 4.697076682201888], [33551, 4.6730223215897695], [33649, 4.8641830671848405], [33705, 4.789446822948693], [33719, 4.646914719261459], [33733, 4.795643669339368], [33747, 4.668638442948616], [33761, 4.7605663337048005], [33775, 4.610555241886031], [33803, 4.530525963835414], [33817, 4.645010098120565], [33831, 4.678209157864934], [33845, 4.843722661934962], [34041, 4.771044470307012], [34055, 4.513210739357548], [34069, 4.5112494523638915], [34083, 4.644337839766419], [34125, 4.551520749482118], [34139, 4.73685454330348], [34153, 4.5005188904202535], [34167, 4.613769213099926]] \ No newline at end of file diff --git a/graphs/summary/decomposition.DictionaryLearningBenchmark.time_transform.json b/graphs/summary/decomposition.DictionaryLearningBenchmark.time_transform.json index d46cafded7..2cfd9ceda8 100644 --- a/graphs/summary/decomposition.DictionaryLearningBenchmark.time_transform.json +++ b/graphs/summary/decomposition.DictionaryLearningBenchmark.time_transform.json @@ -1 +1 @@ -[[28511, 0.1932692886163806], [29225, 0.39008603166056893], [29239, 0.3623614323925207], [29253, 0.1954420295183937], [29267, 0.19336415515738514], [29281, 0.18851270769580766], [29295, 0.1940814315135548], [29309, 0.19398911369569877], [29323, 0.19136574945500828], [29337, 0.192580863050254], [29351, 0.19438380707611777], [29365, 0.198934369484737], [29379, 0.19019336408589607], [29393, 0.1938413162918066], [29407, 0.19497371182139123], [29421, 0.19263972717638356], [29435, 0.20072898311017065], [29449, 0.3627469040661413], [29463, 0.35931626793028687], [29477, 0.34907958784306764], [29547, 0.3805664096331406], [29561, 0.35262434644988333], [29575, 0.34383267469166034], [29603, 0.3441879196161389], [29617, 0.35694079084598207], [29631, 0.3508334333492214], [29645, 0.3467417901213906], [29659, 0.34866241481792926], [29673, 0.33817310252981486], [29743, 0.35493543714152404], [29757, 0.33647385310743183], [29771, 0.34068554914301064], [29785, 0.3660056231489433], [29799, 0.37367740804183763], [29813, 0.35639179792786346], [29827, 0.37688998834153986], [29841, 0.36100624630575495], [29855, 0.3445346328417987], [29869, 0.3530260230888351], [30009, 0.35772768255169846], [30023, 0.3426222548104738], [30037, 0.3632732906608093], [30051, 0.3515244252025243], [30065, 0.34969425587111713], [30079, 0.3473272351556931], [30093, 0.35353615192857707], [30107, 0.36087349491532406], [30121, 0.3468153477280495], [30135, 0.3593302151722363], [30149, 0.36513327755585145], [30163, 0.35930849462416], [30177, 0.353822067027728], [30191, 0.3437994543478941], [30205, 0.34227549811945496], [30219, 0.3486552839972367], [30233, 0.3566376289776486], [30247, 0.36563114012540254], [30261, 0.35195524937749545], [30513, 0.34866290929239746], [30527, 0.35427555044112513], [30541, 0.34286969555973634], [30555, 0.36048529009129376], [30569, 0.35192150718436127], [30583, 0.34938222601544155], [30597, 0.3526983241475732], [30625, 0.3614490670806158], [30639, 0.343922434967288], [30653, 0.35319443331956], [30667, 0.35935423162105373], [30681, 0.35263249881337916], [30695, 0.3727236074741117], [30709, 0.3645164776669788], [30723, 0.36268875244505716], [30737, 0.3574502345648416], [30751, 0.34948758235213767], [30765, 0.3661220542702277], [30779, 0.3479248718683017], [30793, 0.333319144339002], [30807, 0.3633313538587841], [30821, 0.35455272506680535], [30835, 0.37062055670412836], [30849, 0.35835918173298303], [30863, 0.3546262661471099], [30877, 0.354594482845484], [30891, 0.3604779642654403], [30905, 0.35005987888051127], [30919, 0.3488733312624297], [30933, 0.3472411434349175], [30947, 0.34194599329465203], [30961, 0.3521587141645111], [30975, 0.36229621451781313], [30989, 0.33696432891290057], [31003, 0.3467416309668095], [31017, 0.3709920985773843], [31031, 0.34681216828664246], [31045, 0.3535028056772478], [32095, 0.3394704856582571], [32109, 0.36243383713247695], [32123, 0.34589666121595714], [32137, 0.35883097193146246], [32151, 0.34872125400045195], [32165, 0.35305903161711516], [32179, 0.3495751425392469], [32193, 0.3560615030928109], [32207, 0.3355693688039008], [32221, 0.3291283133795935], [32235, 0.34158903877189223], [32249, 0.3196152536300524], [32263, 0.3303629234654774], [32277, 0.3460795118417712], [32305, 0.3270504927986693], [32319, 0.3325416281203155], [32333, 0.35345336447517534], [32347, 0.3312736655807233], [32361, 0.3231953260405258], [32375, 0.34756296682202914], [32389, 0.3256806170177544], [32403, 0.30986669818715606], [32417, 0.3279018763928792], [32431, 0.2982375617515097], [32445, 0.2913871885058405], [32585, 0.319195081173028], [32599, 0.3350465621785212], [32613, 0.3307242247601558], [32627, 0.3274752541422986], [32641, 0.3260605641075801], [32655, 0.32209719618091937], [32851, 0.306830609993949], [32865, 0.32022187475859887], [32879, 0.3204248850075596], [32893, 0.30607074624791136], [32907, 0.31286012357363435], [32921, 0.3174046340937594], [32991, 0.34438161860177907], [33005, 0.3065608876063465], [33019, 0.3441830940350929], [33033, 0.309412852752258], [33047, 0.30255429015506624], [33061, 0.30777990819841283], [33075, 0.31536257154271263], [33089, 0.31879628102445934], [33103, 0.3021897293233535], [33117, 0.30456248432356725], [33131, 0.32944092402477604], [33145, 0.3010884401024105], [33159, 0.3099573927275498], [33187, 0.3202618016635318], [33201, 0.31034859441720347], [33215, 0.3183829200294414], [33229, 0.3099770764024755], [33243, 0.2797586516955892], [33271, 0.26856520779818616], [33299, 0.29812474623913204], [33313, 0.2737574391166754], [33327, 0.2697214853618508], [33341, 0.26908281336946205], [33355, 0.2558472339525561], [33369, 0.2606947281628152], [33383, 0.26965310606919474], [33397, 0.26679698818973263], [33411, 0.2605557026395765], [33425, 0.2519067583805463], [33439, 0.2556894262093413], [33453, 0.2525451790617113], [33467, 0.2552108576818052], [33523, 0.2677260267574937], [33537, 0.2618309680097899], [33551, 0.2707445752772506], [33649, 0.29446503124766665], [33705, 0.256633561740016], [33719, 0.2662308164813084], [33733, 0.2585479599171441], [33747, 0.2630328752903064], [33761, 0.2536410027008145], [33775, 0.24689051176887486], [33803, 0.2677409255275953], [33817, 0.2584906689219738], [33831, 0.26730337353999917], [33845, 0.28803605548502603], [34041, 0.26886104234877267], [34055, 0.258986532038111], [34069, 0.2564730917373989], [34083, 0.27114189488355406], [34125, 0.26515728838154334], [34139, 0.2757783789360517], [34153, 0.267871890176906], [34167, 0.2730044821233153]] \ No newline at end of file +[[28511, 0.1932692886163806], [29225, 0.39008603166056893], [29239, 0.3623614323925207], [29253, 0.1954420295183937], [29267, 0.19336415515738514], [29281, 0.18851270769580766], [29295, 0.1940814315135548], [29309, 0.19398911369569877], [29323, 0.19136574945500828], [29337, 0.192580863050254], [29351, 0.19438380707611777], [29365, 0.198934369484737], [29379, 0.19019336408589607], [29393, 0.1938413162918066], [29407, 0.19497371182139123], [29421, 0.19263972717638356], [29435, 0.20072898311017065], [29449, 0.3627469040661413], [29463, 0.35931626793028687], [29477, 0.34907958784306764], [29547, 0.3805664096331406], [29561, 0.35262434644988333], [29575, 0.34383267469166034], [29603, 0.3441879196161389], [29617, 0.35694079084598207], [29631, 0.3508334333492214], [29645, 0.3467417901213906], [29659, 0.34866241481792926], [29673, 0.33817310252981486], [29743, 0.35493543714152404], [29757, 0.33647385310743183], [29771, 0.34068554914301064], [29785, 0.3660056231489433], [29799, 0.37367740804183763], [29813, 0.35639179792786346], [29827, 0.37688998834153986], [29841, 0.36100624630575495], [29855, 0.3445346328417987], [29869, 0.3530260230888351], [30009, 0.35772768255169846], [30023, 0.3426222548104738], [30037, 0.3632732906608093], [30051, 0.3515244252025243], [30065, 0.34969425587111713], [30079, 0.3473272351556931], [30093, 0.35353615192857707], [30107, 0.36087349491532406], [30121, 0.3468153477280495], [30135, 0.3593302151722363], [30149, 0.36513327755585145], [30163, 0.35930849462416], [30177, 0.353822067027728], [30191, 0.3437994543478941], [30205, 0.34227549811945496], [30219, 0.3486552839972367], [30233, 0.3566376289776486], [30247, 0.36563114012540254], [30261, 0.35195524937749545], [30513, 0.34866290929239746], [30527, 0.35427555044112513], [30541, 0.34286969555973634], [30555, 0.36048529009129376], [30569, 0.35192150718436127], [30583, 0.34938222601544155], [30597, 0.3526983241475732], [30625, 0.3614490670806158], [30639, 0.343922434967288], [30653, 0.35319443331956], [30667, 0.35935423162105373], [30681, 0.35263249881337916], [30695, 0.3727236074741117], [30709, 0.3645164776669788], [30723, 0.36268875244505716], [30737, 0.3574502345648416], [30751, 0.34948758235213767], [30765, 0.3661220542702277], [30779, 0.3479248718683017], [30793, 0.333319144339002], [30807, 0.3633313538587841], [30821, 0.35455272506680535], [30835, 0.37062055670412836], [30849, 0.35835918173298303], [30863, 0.3546262661471099], [30877, 0.354594482845484], [30891, 0.3604779642654403], [30905, 0.35005987888051127], [30919, 0.3488733312624297], [30933, 0.3472411434349175], [30947, 0.34194599329465203], [30961, 0.3521587141645111], [30975, 0.36229621451781313], [30989, 0.33696432891290057], [31003, 0.3467416309668095], [31017, 0.3709920985773843], [31031, 0.34681216828664246], [31045, 0.3535028056772478], [32095, 0.3394704856582571], [32109, 0.36243383713247695], [32123, 0.34589666121595714], [32137, 0.35883097193146246], [32151, 0.34872125400045195], [32165, 0.35305903161711516], [32179, 0.3495751425392469], [32193, 0.3560615030928109], [32207, 0.3355693688039008], [32221, 0.3291283133795935], [32235, 0.34158903877189223], [32249, 0.3196152536300524], [32263, 0.3303629234654774], [32277, 0.3460795118417712], [32305, 0.3270504927986693], [32319, 0.3325416281203155], [32333, 0.35345336447517534], [32347, 0.3312736655807233], [32361, 0.3231953260405258], [32375, 0.34756296682202914], [32389, 0.3256806170177544], [32403, 0.30986669818715606], [32417, 0.3279018763928792], [32431, 0.2982375617515097], [32445, 0.2913871885058405], [32585, 0.319195081173028], [32599, 0.3350465621785212], [32613, 0.3307242247601558], [32627, 0.3274752541422986], [32641, 0.3260605641075801], [32655, 0.32209719618091937], [32851, 0.306830609993949], [32865, 0.32022187475859887], [32879, 0.3204248850075596], [32893, 0.30607074624791136], [32907, 0.31286012357363435], [32921, 0.3174046340937594], [32991, 0.34438161860177907], [33005, 0.3065608876063465], [33019, 0.3441830940350929], [33033, 0.309412852752258], [33047, 0.30255429015506624], [33061, 0.30777990819841283], [33075, 0.31536257154271263], [33089, 0.31879628102445934], [33103, 0.3021897293233535], [33117, 0.30456248432356725], [33131, 0.32944092402477604], [33145, 0.3010884401024105], [33159, 0.3099573927275498], [33187, 0.3202618016635318], [33201, 0.31034859441720347], [33215, 0.3183829200294414], [33229, 0.3099770764024755], [33243, 0.2797586516955892], [33271, 0.26856520779818616], [33299, 0.29812474623913204], [33313, 0.2737574391166754], [33327, 0.2697214853618508], [33341, 0.26908281336946205], [33355, 0.2558472339525561], [33369, 0.2606947281628152], [33383, 0.26965310606919474], [33397, 0.26679698818973263], [33411, 0.2605557026395765], [33425, 0.2519067583805463], [33439, 0.2556894262093413], [33453, 0.2525451790617113], [33467, 0.2552108576818052], [33523, 0.2677260267574937], [33537, 0.2618309680097899], [33551, 0.2707445752772506], [33649, 0.29446503124766665], [33705, 0.256633561740016], [33719, 0.2662308164813084], [33733, 0.2585479599171441], [33747, 0.2630328752903064], [33761, 0.2536410027008145], [33775, 0.24689051176887486], [33803, 0.2677409255275953], [33817, 0.2584906689219738], [33831, 0.26730337353999917], [33845, 0.28803605548502603], [34041, 0.26886104234877267], [34055, 0.258986532038111], [34069, 0.2564730917373989], [34083, 0.27114189488355406], [34125, 0.26515728838154334], [34139, 0.2757783789360517], [34153, 0.267871890176906], [34167, 0.2711431599256163]] \ No newline at end of file diff --git a/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json b/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json index 69ac404d00..fee444ec11 100644 --- a/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json +++ b/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 114834596.67055133], [29225, 116874596.44664134], [29239, 116044631.22296922], [29253, 111362756.66411412], [29267, 111503773.86963579], [29281, 111884514.81290573], [29295, 111979889.84621577], [29309, 111536032.75702378], [29323, 111271476.75791687], [29337, 111173594.23402017], [29351, 110558987.91935307], [29365, 110757759.01912391], [29379, 111369539.07864869], [29393, 110700940.08894718], [29407, 110666332.7025438], [29421, 110645582.90807945], [29435, 111164488.9249831], [29449, 116212605.41994043], [29463, 116207664.799215], [29477, 115679672.19960518], [29547, 115628493.886927], [29561, 116408428.88789117], [29575, 115645656.10350138], [29603, 117354846.88844517], [29617, 117892788.64164777], [29631, 118210089.27499533], [29645, 117782984.07873896], [29659, 117838405.64613909], [29673, 117034122.24216147], [29743, 118272312.10652637], [29757, 117823055.51952599], [29771, 117799108.23758559], [29785, 118109025.27082235], [29799, 116940858.43903653], [29813, 117994798.07491541], [29827, 118687005.83484876], [29841, 118088545.49640708], [29855, 118169620.92615171], [29869, 118484999.34369501], [30009, 118406055.61726066], [30023, 117474386.51712364], [30037, 117917325.55355375], [30051, 117795266.99603896], [30065, 117280781.40221664], [30079, 117548924.79695193], [30093, 117704308.94674648], [30107, 117373964.1078553], [30121, 117694731.67825706], [30135, 117688593.27303402], [30149, 118136416.28756137], [30163, 116669788.68317927], [30177, 117216134.8685182], [30191, 117446480.81868678], [30205, 117226000.95052917], [30219, 117492814.15182623], [30233, 116993568.878714], [30247, 117678784.92926311], [30261, 117383356.36378272], [30513, 111224719.15687466], [30527, 108959088.9039062], [30541, 109300058.84057708], [30555, 109427180.13319899], [30569, 109589863.68245277], [30583, 108533071.54579468], [30597, 109513454.49261796], [30625, 109973255.46223314], [30639, 108897091.72151886], [30653, 109398307.29241931], [30667, 109008585.14385465], [30681, 108609751.34386022], [30695, 109220150.9623922], [30709, 108855648.34416851], [30723, 108235436.8410934], [30737, 108221672.47213107], [30751, 108493347.83480296], [30765, 108640577.9568416], [30779, 108272874.45286721], [30793, 108133687.8197627], [30807, 108188330.85208948], [30821, 108601459.40049666], [30835, 108527915.37635739], [30849, 109053908.52172045], [30863, 108328990.78914136], [30877, 108343843.723029], [30891, 109150867.15131229], [30905, 108175636.7543823], [30919, 108860401.77283621], [30933, 109112205.9544693], [30947, 108667616.86577421], [30961, 108687506.05270232], [30975, 108189798.39242655], [30989, 108683312.7313344], [31003, 108593542.10005058], [31017, 108674793.98842463], [31031, 108224119.48186173], [31045, 108752018.35013792], [32095, 119552318.06000583], [32109, 120955035.6471963], [32123, 120986247.73544231], [32137, 120180938.73872244], [32151, 120904540.56647334], [32165, 120521699.38695262], [32179, 120659967.61234383], [32193, 120718917.2193769], [32207, 122201238.80506897], [32221, 123556828.59788631], [32235, 123987482.27218552], [32249, 123729832.11395895], [32263, 123536218.38274702], [32277, 123342800.1391686], [32305, 124313200.11887668], [32319, 126689054.60721815], [32333, 126837656.61856696], [32347, 126901906.7212115], [32361, 127049675.80659556], [32375, 126683016.3007118], [32389, 126908038.90860766], [32403, 126986545.96452945], [32417, 127025790.22961588], [32431, 127132679.10623185], [32445, 127425018.26522854], [32585, 124994861.65128751], [32599, 125037696.79413478], [32613, 124978514.55332594], [32627, 125089511.49484864], [32641, 124804311.6146659], [32655, 124916748.54740673], [32851, 126566005.6326887], [32865, 126592438.21938363], [32879, 126672443.78183271], [32893, 126626510.25989096], [32907, 126686927.09121345], [32921, 126442844.60855693], [32991, 126528188.42085159], [33005, 126993398.48297012], [33019, 125857447.84297599], [33033, 126827689.73430839], [33047, 126540160.53309445], [33061, 126931259.62821653], [33075, 126895402.47179662], [33089, 142499982.63702846], [33103, 157970360.78620458], [33117, 158254805.56850216], [33131, 158056779.9213932], [33145, 158301282.8308414], [33159, 158110471.02500528], [33187, 126716694.56784663], [33201, 127008808.43714298], [33215, 124184242.13209891], [33229, 116399802.51666997], [33243, 116283421.48843363], [33271, 106408526.03842685], [33299, 106715049.01112725], [33313, 106564700.65258548], [33327, 106965914.08362362], [33341, 106945774.16413823], [33355, 107221924.32234351], [33369, 107535358.44067986], [33383, 107923436.74019937], [33397, 108411099.18944412], [33411, 108380148.86925149], [33425, 108541345.50660461], [33439, 109759571.56232592], [33453, 104938761.79682791], [33467, 104765677.50809202], [33523, 104697692.33301352], [33537, 104851256.7880509], [33551, 104309809.60309315], [33649, 103772634.492263], [33705, 103375903.69569547], [33719, 103156518.05873351], [33733, 103095822.4238608], [33747, 103203272.46903354], [33761, 102716803.0708615], [33775, 103121387.29580425], [33803, 103381763.9852121], [33817, 102843957.68759555], [33831, 102947010.55744056], [33845, 102719996.08834133], [34041, 102254221.18890193], [34055, 102583030.46962832], [34069, 102666767.46521463], [34083, 102666226.21007189], [34125, 102570881.92076112], [34139, 102576303.85457827], [34153, 102457558.86605473], [34167, 102487450.19526565]] \ No newline at end of file +[[28511, 114834596.67055133], [29225, 116874596.44664134], [29239, 116044631.22296922], [29253, 111362756.66411412], [29267, 111503773.86963579], [29281, 111884514.81290573], [29295, 111979889.84621577], [29309, 111536032.75702378], [29323, 111271476.75791687], [29337, 111173594.23402017], [29351, 110558987.91935307], [29365, 110757759.01912391], [29379, 111369539.07864869], [29393, 110700940.08894718], [29407, 110666332.7025438], [29421, 110645582.90807945], [29435, 111164488.9249831], [29449, 116212605.41994043], [29463, 116207664.799215], [29477, 115679672.19960518], [29547, 115628493.886927], [29561, 116408428.88789117], [29575, 115645656.10350138], [29603, 117354846.88844517], [29617, 117892788.64164777], [29631, 118210089.27499533], [29645, 117782984.07873896], [29659, 117838405.64613909], [29673, 117034122.24216147], [29743, 118272312.10652637], [29757, 117823055.51952599], [29771, 117799108.23758559], [29785, 118109025.27082235], [29799, 116940858.43903653], [29813, 117994798.07491541], [29827, 118687005.83484876], [29841, 118088545.49640708], [29855, 118169620.92615171], [29869, 118484999.34369501], [30009, 118406055.61726066], [30023, 117474386.51712364], [30037, 117917325.55355375], [30051, 117795266.99603896], [30065, 117280781.40221664], [30079, 117548924.79695193], [30093, 117704308.94674648], [30107, 117373964.1078553], [30121, 117694731.67825706], [30135, 117688593.27303402], [30149, 118136416.28756137], [30163, 116669788.68317927], [30177, 117216134.8685182], [30191, 117446480.81868678], [30205, 117226000.95052917], [30219, 117492814.15182623], [30233, 116993568.878714], [30247, 117678784.92926311], [30261, 117383356.36378272], [30513, 111224719.15687466], [30527, 108959088.9039062], [30541, 109300058.84057708], [30555, 109427180.13319899], [30569, 109589863.68245277], [30583, 108533071.54579468], [30597, 109513454.49261796], [30625, 109973255.46223314], [30639, 108897091.72151886], [30653, 109398307.29241931], [30667, 109008585.14385465], [30681, 108609751.34386022], [30695, 109220150.9623922], [30709, 108855648.34416851], [30723, 108235436.8410934], [30737, 108221672.47213107], [30751, 108493347.83480296], [30765, 108640577.9568416], [30779, 108272874.45286721], [30793, 108133687.8197627], [30807, 108188330.85208948], [30821, 108601459.40049666], [30835, 108527915.37635739], [30849, 109053908.52172045], [30863, 108328990.78914136], [30877, 108343843.723029], [30891, 109150867.15131229], [30905, 108175636.7543823], [30919, 108860401.77283621], [30933, 109112205.9544693], [30947, 108667616.86577421], [30961, 108687506.05270232], [30975, 108189798.39242655], [30989, 108683312.7313344], [31003, 108593542.10005058], [31017, 108674793.98842463], [31031, 108224119.48186173], [31045, 108752018.35013792], [32095, 119552318.06000583], [32109, 120955035.6471963], [32123, 120986247.73544231], [32137, 120180938.73872244], [32151, 120904540.56647334], [32165, 120521699.38695262], [32179, 120659967.61234383], [32193, 120718917.2193769], [32207, 122201238.80506897], [32221, 123556828.59788631], [32235, 123987482.27218552], [32249, 123729832.11395895], [32263, 123536218.38274702], [32277, 123342800.1391686], [32305, 124313200.11887668], [32319, 126689054.60721815], [32333, 126837656.61856696], [32347, 126901906.7212115], [32361, 127049675.80659556], [32375, 126683016.3007118], [32389, 126908038.90860766], [32403, 126986545.96452945], [32417, 127025790.22961588], [32431, 127132679.10623185], [32445, 127425018.26522854], [32585, 124994861.65128751], [32599, 125037696.79413478], [32613, 124978514.55332594], [32627, 125089511.49484864], [32641, 124804311.6146659], [32655, 124916748.54740673], [32851, 126566005.6326887], [32865, 126592438.21938363], [32879, 126672443.78183271], [32893, 126626510.25989096], [32907, 126686927.09121345], [32921, 126442844.60855693], [32991, 126528188.42085159], [33005, 126993398.48297012], [33019, 125857447.84297599], [33033, 126827689.73430839], [33047, 126540160.53309445], [33061, 126931259.62821653], [33075, 126895402.47179662], [33089, 142499982.63702846], [33103, 157970360.78620458], [33117, 158254805.56850216], [33131, 158056779.9213932], [33145, 158301282.8308414], [33159, 158110471.02500528], [33187, 126716694.56784663], [33201, 127008808.43714298], [33215, 124184242.13209891], [33229, 116399802.51666997], [33243, 116283421.48843363], [33271, 106408526.03842685], [33299, 106715049.01112725], [33313, 106564700.65258548], [33327, 106965914.08362362], [33341, 106945774.16413823], [33355, 107221924.32234351], [33369, 107535358.44067986], [33383, 107923436.74019937], [33397, 108411099.18944412], [33411, 108380148.86925149], [33425, 108541345.50660461], [33439, 109759571.56232592], [33453, 104938761.79682791], [33467, 104765677.50809202], [33523, 104697692.33301352], [33537, 104851256.7880509], [33551, 104309809.60309315], [33649, 103772634.492263], [33705, 103375903.69569547], [33719, 103156518.05873351], [33733, 103095822.4238608], [33747, 103203272.46903354], [33761, 102716803.0708615], [33775, 103121387.29580425], [33803, 103381763.9852121], [33817, 102843957.68759555], [33831, 102947010.55744056], [33845, 102719996.08834133], [34041, 102254221.18890193], [34055, 102583030.46962832], [34069, 102666767.46521463], [34083, 102666226.21007189], [34125, 102570881.92076112], [34139, 102576303.85457827], [34153, 102457558.86605473], [34167, 102491867.71421425]] \ No newline at end of file diff --git a/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json b/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json index 9c831ee949..08c5cb1857 100644 --- a/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json +++ b/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json @@ -1 +1 @@ -[[28511, 99323903.99999999], [29225, 95834050.94439475], [29239, 95577471.10308099], [29253, 96642729.13860285], [29267, 96589311.99183759], [29281, 97090556.3557757], [29295, 96892926.37765895], [29309, 96720893.92180845], [29323, 96918527.98377103], [29337, 97461930.65052819], [29351, 96415061.32246639], [29365, 96334847.98367319], [29379, 96806398.17001489], [29393, 96677203.70099254], [29407, 96691710.1658971], [29421, 96512766.16060291], [29435, 97020926.47975111], [29449, 96178983.89779167], [29463, 96022385.11576077], [29477, 96033761.17980535], [29547, 96265160.92283408], [29561, 96368494.3141513], [29575, 95881986.28295797], [29603, 96784738.57580967], [29617, 96985974.62672019], [29631, 96821018.50507984], [29645, 97027849.96193743], [29659, 96951450.75424978], [29673, 96987709.24204628], [29743, 96784295.94114226], [29757, 96914258.49042706], [29771, 96998463.3876861], [29785, 97089485.22763342], [29799, 96971323.61140187], [29813, 97159221.47845109], [29827, 97113758.68020934], [29841, 97089941.15631962], [29855, 97145752.80762084], [29869, 97122683.69421452], [30009, 97366437.44795565], [30023, 97322877.68443856], [30037, 97043031.66107075], [30051, 96809765.95942642], [30065, 96921459.27118574], [30079, 97008937.93996856], [30093, 96815061.99734345], [30107, 96937254.68496054], [30121, 97070645.29745853], [30135, 97167770.34393324], [30149, 97417469.90296894], [30163, 97389767.85673214], [30177, 97674520.4466792], [30191, 97521275.08681257], [30205, 97388356.29693699], [30219, 97484909.02613454], [30233, 97331149.25643383], [30247, 97462906.47875741], [30261, 97286840.62244539], [30513, 90092826.37248006], [30527, 87888151.63211073], [30541, 88193882.64829576], [30555, 88011182.8731644], [30569, 88058219.9147108], [30583, 87990560.81871098], [30597, 87665741.29780143], [30625, 88131135.34417324], [30639, 87897973.84821838], [30653, 87945865.82881139], [30667, 87837092.14558014], [30681, 87557382.12095766], [30695, 87719820.85656564], [30709, 87613788.62962729], [30723, 87450073.87662125], [30737, 87882223.02457727], [30751, 87979027.8093964], [30765, 88144020.87595756], [30779, 87855553.07664259], [30793, 87552082.98664562], [30807, 87817742.52213876], [30821, 87687231.28018886], [30835, 87563422.1392631], [30849, 87933152.02019629], [30863, 87791806.08828434], [30877, 87826083.58365883], [30891, 88506293.51552406], [30905, 88080295.14220597], [30919, 88022672.19896854], [30933, 87794764.66412261], [30947, 87506540.58852983], [30961, 87837167.6462116], [30975, 88032326.07398151], [30989, 87965937.48421836], [31003, 88296904.48730406], [31017, 87702275.43615735], [31031, 87630258.05035739], [31045, 88018915.73495774], [32095, 99854138.46585432], [32109, 99788414.8742857], [32123, 99834455.81738143], [32137, 99827234.58949427], [32151, 99767437.72561154], [32165, 99573443.19887626], [32179, 99702660.76567902], [32193, 99731671.42280097], [32207, 100752892.59469923], [32221, 101901512.13114417], [32235, 102001054.64506416], [32249, 102006081.08619823], [32263, 101851885.07982704], [32277, 101934139.27670228], [32305, 103815484.09610046], [32319, 107430312.01159783], [32333, 107578905.55122922], [32347, 107554591.17931232], [32361, 107575465.43862475], [32375, 107304611.82443362], [32389, 107284491.62930912], [32403, 107227400.6955395], [32417, 107467970.57117237], [32431, 107799757.22046816], [32445, 107992495.70977771], [32585, 105502283.45817058], [32599, 105676875.26474135], [32613, 105591938.37062256], [32627, 105660026.07757145], [32641, 105421468.50656347], [32655, 105632534.41929571], [32851, 106481100.13463783], [32865, 106560307.90368539], [32879, 106613262.40900718], [32893, 106929768.04806276], [32907, 106781615.24594635], [32921, 106549572.48238854], [32991, 106596397.78770287], [33005, 106547011.89994074], [33019, 105944754.86328074], [33033, 106376040.46534626], [33047, 106357251.14335549], [33061, 106698046.78025794], [33075, 106459034.7991267], [33089, 121175142.96921104], [33103, 135685593.2479314], [33117, 136228221.82340044], [33131, 135625829.63453716], [33145, 135748122.17758676], [33159, 135853776.65714216], [33187, 106939230.19364038], [33201, 106746947.93873307], [33215, 104597314.38760361], [33229, 98538285.95851126], [33243, 98657923.63211213], [33271, 90980096.09336978], [33299, 91336710.32537347], [33313, 91161714.57274118], [33327, 91546040.68768947], [33341, 91407392.56326355], [33355, 91651566.67845398], [33369, 92006058.00890027], [33383, 92328445.54638976], [33397, 92759277.44221365], [33411, 92858814.0588745], [33425, 92827916.86541805], [33439, 93899292.24670199], [33453, 89182727.35963129], [33467, 89090844.70628572], [33523, 89120679.11678791], [33537, 89125196.4337879], [33551, 88487146.42911987], [33649, 87850052.4017502], [33705, 87406333.90621927], [33719, 87391550.7680291], [33733, 87539943.94282076], [33747, 87441045.68937193], [33761, 87235557.64762528], [33775, 87419805.14235476], [33803, 87438091.30153409], [33817, 87132136.78008288], [33831, 87287788.02354167], [33845, 86978195.90039836], [34041, 86858429.7981725], [34055, 87160078.64224221], [34069, 87099260.63342933], [34083, 87015173.25422528], [34125, 87070399.68417978], [34139, 87476762.73205835], [34153, 87081349.95725243], [34167, 87073088.39873399]] \ No newline at end of file +[[28511, 99323903.99999999], [29225, 95834050.94439475], [29239, 95577471.10308099], [29253, 96642729.13860285], [29267, 96589311.99183759], [29281, 97090556.3557757], [29295, 96892926.37765895], [29309, 96720893.92180845], [29323, 96918527.98377103], [29337, 97461930.65052819], [29351, 96415061.32246639], [29365, 96334847.98367319], [29379, 96806398.17001489], [29393, 96677203.70099254], [29407, 96691710.1658971], [29421, 96512766.16060291], [29435, 97020926.47975111], [29449, 96178983.89779167], [29463, 96022385.11576077], [29477, 96033761.17980535], [29547, 96265160.92283408], [29561, 96368494.3141513], [29575, 95881986.28295797], [29603, 96784738.57580967], [29617, 96985974.62672019], [29631, 96821018.50507984], [29645, 97027849.96193743], [29659, 96951450.75424978], [29673, 96987709.24204628], [29743, 96784295.94114226], [29757, 96914258.49042706], [29771, 96998463.3876861], [29785, 97089485.22763342], [29799, 96971323.61140187], [29813, 97159221.47845109], [29827, 97113758.68020934], [29841, 97089941.15631962], [29855, 97145752.80762084], [29869, 97122683.69421452], [30009, 97366437.44795565], [30023, 97322877.68443856], [30037, 97043031.66107075], [30051, 96809765.95942642], [30065, 96921459.27118574], [30079, 97008937.93996856], [30093, 96815061.99734345], [30107, 96937254.68496054], [30121, 97070645.29745853], [30135, 97167770.34393324], [30149, 97417469.90296894], [30163, 97389767.85673214], [30177, 97674520.4466792], [30191, 97521275.08681257], [30205, 97388356.29693699], [30219, 97484909.02613454], [30233, 97331149.25643383], [30247, 97462906.47875741], [30261, 97286840.62244539], [30513, 90092826.37248006], [30527, 87888151.63211073], [30541, 88193882.64829576], [30555, 88011182.8731644], [30569, 88058219.9147108], [30583, 87990560.81871098], [30597, 87665741.29780143], [30625, 88131135.34417324], [30639, 87897973.84821838], [30653, 87945865.82881139], [30667, 87837092.14558014], [30681, 87557382.12095766], [30695, 87719820.85656564], [30709, 87613788.62962729], [30723, 87450073.87662125], [30737, 87882223.02457727], [30751, 87979027.8093964], [30765, 88144020.87595756], [30779, 87855553.07664259], [30793, 87552082.98664562], [30807, 87817742.52213876], [30821, 87687231.28018886], [30835, 87563422.1392631], [30849, 87933152.02019629], [30863, 87791806.08828434], [30877, 87826083.58365883], [30891, 88506293.51552406], [30905, 88080295.14220597], [30919, 88022672.19896854], [30933, 87794764.66412261], [30947, 87506540.58852983], [30961, 87837167.6462116], [30975, 88032326.07398151], [30989, 87965937.48421836], [31003, 88296904.48730406], [31017, 87702275.43615735], [31031, 87630258.05035739], [31045, 88018915.73495774], [32095, 99854138.46585432], [32109, 99788414.8742857], [32123, 99834455.81738143], [32137, 99827234.58949427], [32151, 99767437.72561154], [32165, 99573443.19887626], [32179, 99702660.76567902], [32193, 99731671.42280097], [32207, 100752892.59469923], [32221, 101901512.13114417], [32235, 102001054.64506416], [32249, 102006081.08619823], [32263, 101851885.07982704], [32277, 101934139.27670228], [32305, 103815484.09610046], [32319, 107430312.01159783], [32333, 107578905.55122922], [32347, 107554591.17931232], [32361, 107575465.43862475], [32375, 107304611.82443362], [32389, 107284491.62930912], [32403, 107227400.6955395], [32417, 107467970.57117237], [32431, 107799757.22046816], [32445, 107992495.70977771], [32585, 105502283.45817058], [32599, 105676875.26474135], [32613, 105591938.37062256], [32627, 105660026.07757145], [32641, 105421468.50656347], [32655, 105632534.41929571], [32851, 106481100.13463783], [32865, 106560307.90368539], [32879, 106613262.40900718], [32893, 106929768.04806276], [32907, 106781615.24594635], [32921, 106549572.48238854], [32991, 106596397.78770287], [33005, 106547011.89994074], [33019, 105944754.86328074], [33033, 106376040.46534626], [33047, 106357251.14335549], [33061, 106698046.78025794], [33075, 106459034.7991267], [33089, 121175142.96921104], [33103, 135685593.2479314], [33117, 136228221.82340044], [33131, 135625829.63453716], [33145, 135748122.17758676], [33159, 135853776.65714216], [33187, 106939230.19364038], [33201, 106746947.93873307], [33215, 104597314.38760361], [33229, 98538285.95851126], [33243, 98657923.63211213], [33271, 90980096.09336978], [33299, 91336710.32537347], [33313, 91161714.57274118], [33327, 91546040.68768947], [33341, 91407392.56326355], [33355, 91651566.67845398], [33369, 92006058.00890027], [33383, 92328445.54638976], [33397, 92759277.44221365], [33411, 92858814.0588745], [33425, 92827916.86541805], [33439, 93899292.24670199], [33453, 89182727.35963129], [33467, 89090844.70628572], [33523, 89120679.11678791], [33537, 89125196.4337879], [33551, 88487146.42911987], [33649, 87850052.4017502], [33705, 87406333.90621927], [33719, 87391550.7680291], [33733, 87539943.94282076], [33747, 87441045.68937193], [33761, 87235557.64762528], [33775, 87419805.14235476], [33803, 87438091.30153409], [33817, 87132136.78008288], [33831, 87287788.02354167], [33845, 86978195.90039836], [34041, 86858429.7981725], [34055, 87160078.64224221], [34069, 87099260.63342933], [34083, 87015173.25422528], [34125, 87070399.68417978], [34139, 87476762.73205835], [34153, 87081349.95725243], [34167, 87044748.27125472]] \ No newline at end of file diff --git a/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json b/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json index a5585c01e5..0925480028 100644 --- a/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json +++ b/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 5.476430067021406], [29225, 9.52094371839126], [29239, 9.436935172138476], [29253, 5.326635454663351], [29267, 5.368743686007749], [29281, 5.607266172862515], [29295, 5.418037906996699], [29309, 5.691331951029652], [29323, 5.476998129131928], [29337, 5.149542732885405], [29351, 5.320299515970587], [29365, 5.36803230359886], [29379, 5.552126356268696], [29393, 5.370761093311259], [29407, 5.269901301793413], [29421, 5.149506650084591], [29435, 5.2206449909562815], [29449, 9.638045516965283], [29463, 9.513362362777148], [29477, 9.588017923595714], [29547, 10.139050729601326], [29561, 9.11006014633548], [29575, 9.93566161737111], [29603, 8.529230192740858], [29617, 8.231294024117972], [29631, 8.423927118383446], [29645, 8.51397203748064], [29659, 8.868313599780974], [29673, 8.584240366229679], [29743, 8.330024974184695], [29757, 8.025561053690755], [29771, 8.602720770589954], [29785, 9.297490458010486], [29799, 9.44538114080108], [29813, 9.724909050180074], [29827, 10.383060203002088], [29841, 9.704648869137166], [29855, 9.460944998671689], [29869, 9.375610766250812], [30009, 9.77373490441331], [30023, 10.101616811590326], [30037, 9.76514209130476], [30051, 9.653950049911677], [30065, 9.894366891528785], [30079, 9.650382549268654], [30093, 9.686762975645111], [30107, 9.705747639746134], [30121, 9.698204917824052], [30135, 9.795914169954894], [30149, 9.39416243307399], [30163, 9.599197118614512], [30177, 9.347964352915255], [30191, 9.562067807527686], [30205, 9.635486954105014], [30219, 9.401748449973637], [30233, 9.66370717428], [30247, 9.597311639793762], [30261, 9.67876050151188], [30513, 11.183963590928794], [30527, 11.227977119688637], [30541, 11.433209834450878], [30555, 11.463909312852905], [30569, 11.215311942344785], [30583, 11.31418378169088], [30597, 11.167824637549936], [30625, 11.54133706123356], [30639, 11.30793223142218], [30653, 11.20732445501926], [30667, 11.326774454277501], [30681, 8.111980195264152], [30695, 9.02627916970423], [30709, 8.283247197641115], [30723, 8.133931681653138], [30737, 8.523943139610507], [30751, 8.361377396186477], [30765, 8.380049661823946], [30779, 8.469885423374432], [30793, 7.907858521527332], [30807, 8.276670871634444], [30821, 8.39900473475417], [30835, 8.106223657287947], [30849, 8.358044840951427], [30863, 8.655071827280274], [30877, 8.491598900421579], [30891, 8.537679225677907], [30905, 8.55576843126377], [30919, 8.569328276294263], [30933, 8.452554799710203], [30947, 8.218013091854234], [30961, 8.565584016495812], [30975, 8.596348036056586], [30989, 8.551215193824321], [31003, 8.415248580107075], [31017, 8.83651036954382], [31031, 8.335461240193155], [31045, 8.594520028966368], [32095, 9.002018495276605], [32109, 9.087340763783315], [32123, 8.766952303226388], [32137, 9.145117087803351], [32151, 9.530037199635135], [32165, 9.193747445421648], [32179, 8.706210530028626], [32193, 9.299297404496475], [32207, 9.434741196067412], [32221, 8.603469904635181], [32235, 8.731530067627403], [32249, 8.469169477998134], [32263, 8.726104646278628], [32277, 9.093455662070937], [32305, 8.844680004737517], [32319, 8.446525474100676], [32333, 8.927463074900388], [32347, 8.850577616068536], [32361, 8.92612796419761], [32375, 8.865059499289481], [32389, 8.619142303624146], [32403, 9.068528459330853], [32417, 8.890441926212532], [32431, 9.035716059067433], [32445, 8.606112957330168], [32585, 8.434369141210075], [32599, 8.6223302357209], [32613, 8.559053401632132], [32627, 9.552976098982542], [32641, 8.76724900207618], [32655, 9.263186822435243], [32851, 8.979029383490955], [32865, 9.424842650516798], [32879, 8.966594378153143], [32893, 8.844938344160642], [32907, 9.395256366540913], [32921, 8.724387113387923], [32991, 9.01280681902145], [33005, 9.132062586644782], [33019, 8.572485551782371], [33033, 9.092728323334683], [33047, 8.481028957486165], [33061, 8.383728082936418], [33075, 8.835584668893958], [33089, 8.825553274964527], [33103, 9.082835764269754], [33117, 8.305216647683778], [33131, 9.124470745452657], [33145, 8.599530411738874], [33159, 8.670434954962039], [33187, 8.803656156455082], [33201, 9.24900337925212], [33215, 8.762722627157448], [33229, 8.9965310749382], [33243, 8.892043600290929], [33271, 8.73823995491883], [33299, 8.594518215833606], [33313, 8.66165323707431], [33327, 8.622062828078647], [33341, 8.851950577607004], [33355, 8.616190365006744], [33369, 8.806406232859318], [33383, 8.599144798093738], [33397, 8.85690752886568], [33411, 8.5675980846072], [33425, 8.665962623006099], [33439, 8.446518892323173], [33453, 11.154857996361716], [33467, 9.756742866550686], [33523, 10.810299163190706], [33537, 10.831996462526769], [33551, 10.588678235870304], [33649, 10.82350759635587], [33705, 10.481565592302397], [33719, 10.632021042572894], [33733, 10.635850726406314], [33747, 10.554738317163775], [33761, 10.373951851391562], [33775, 10.740730549319899], [33803, 10.70942121642436], [33817, 10.73545567905077], [33831, 10.748663479928686], [33845, 10.67439703869048], [34041, 10.398655077974503], [34055, 10.535492767259344], [34069, 10.5404847809123], [34083, 10.699978571118944], [34125, 10.6548034359791], [34139, 10.825986986951719], [34153, 10.916219113688712], [34167, 10.227015542194483]] \ No newline at end of file +[[28511, 5.476430067021406], [29225, 9.52094371839126], [29239, 9.436935172138476], [29253, 5.326635454663351], [29267, 5.368743686007749], [29281, 5.607266172862515], [29295, 5.418037906996699], [29309, 5.691331951029652], [29323, 5.476998129131928], [29337, 5.149542732885405], [29351, 5.320299515970587], [29365, 5.36803230359886], [29379, 5.552126356268696], [29393, 5.370761093311259], [29407, 5.269901301793413], [29421, 5.149506650084591], [29435, 5.2206449909562815], [29449, 9.638045516965283], [29463, 9.513362362777148], [29477, 9.588017923595714], [29547, 10.139050729601326], [29561, 9.11006014633548], [29575, 9.93566161737111], [29603, 8.529230192740858], [29617, 8.231294024117972], [29631, 8.423927118383446], [29645, 8.51397203748064], [29659, 8.868313599780974], [29673, 8.584240366229679], [29743, 8.330024974184695], [29757, 8.025561053690755], [29771, 8.602720770589954], [29785, 9.297490458010486], [29799, 9.44538114080108], [29813, 9.724909050180074], [29827, 10.383060203002088], [29841, 9.704648869137166], [29855, 9.460944998671689], [29869, 9.375610766250812], [30009, 9.77373490441331], [30023, 10.101616811590326], [30037, 9.76514209130476], [30051, 9.653950049911677], [30065, 9.894366891528785], [30079, 9.650382549268654], [30093, 9.686762975645111], [30107, 9.705747639746134], [30121, 9.698204917824052], [30135, 9.795914169954894], [30149, 9.39416243307399], [30163, 9.599197118614512], [30177, 9.347964352915255], [30191, 9.562067807527686], [30205, 9.635486954105014], [30219, 9.401748449973637], [30233, 9.66370717428], [30247, 9.597311639793762], [30261, 9.67876050151188], [30513, 11.183963590928794], [30527, 11.227977119688637], [30541, 11.433209834450878], [30555, 11.463909312852905], [30569, 11.215311942344785], [30583, 11.31418378169088], [30597, 11.167824637549936], [30625, 11.54133706123356], [30639, 11.30793223142218], [30653, 11.20732445501926], [30667, 11.326774454277501], [30681, 8.111980195264152], [30695, 9.02627916970423], [30709, 8.283247197641115], [30723, 8.133931681653138], [30737, 8.523943139610507], [30751, 8.361377396186477], [30765, 8.380049661823946], [30779, 8.469885423374432], [30793, 7.907858521527332], [30807, 8.276670871634444], [30821, 8.39900473475417], [30835, 8.106223657287947], [30849, 8.358044840951427], [30863, 8.655071827280274], [30877, 8.491598900421579], [30891, 8.537679225677907], [30905, 8.55576843126377], [30919, 8.569328276294263], [30933, 8.452554799710203], [30947, 8.218013091854234], [30961, 8.565584016495812], [30975, 8.596348036056586], [30989, 8.551215193824321], [31003, 8.415248580107075], [31017, 8.83651036954382], [31031, 8.335461240193155], [31045, 8.594520028966368], [32095, 9.002018495276605], [32109, 9.087340763783315], [32123, 8.766952303226388], [32137, 9.145117087803351], [32151, 9.530037199635135], [32165, 9.193747445421648], [32179, 8.706210530028626], [32193, 9.299297404496475], [32207, 9.434741196067412], [32221, 8.603469904635181], [32235, 8.731530067627403], [32249, 8.469169477998134], [32263, 8.726104646278628], [32277, 9.093455662070937], [32305, 8.844680004737517], [32319, 8.446525474100676], [32333, 8.927463074900388], [32347, 8.850577616068536], [32361, 8.92612796419761], [32375, 8.865059499289481], [32389, 8.619142303624146], [32403, 9.068528459330853], [32417, 8.890441926212532], [32431, 9.035716059067433], [32445, 8.606112957330168], [32585, 8.434369141210075], [32599, 8.6223302357209], [32613, 8.559053401632132], [32627, 9.552976098982542], [32641, 8.76724900207618], [32655, 9.263186822435243], [32851, 8.979029383490955], [32865, 9.424842650516798], [32879, 8.966594378153143], [32893, 8.844938344160642], [32907, 9.395256366540913], [32921, 8.724387113387923], [32991, 9.01280681902145], [33005, 9.132062586644782], [33019, 8.572485551782371], [33033, 9.092728323334683], [33047, 8.481028957486165], [33061, 8.383728082936418], [33075, 8.835584668893958], [33089, 8.825553274964527], [33103, 9.082835764269754], [33117, 8.305216647683778], [33131, 9.124470745452657], [33145, 8.599530411738874], [33159, 8.670434954962039], [33187, 8.803656156455082], [33201, 9.24900337925212], [33215, 8.762722627157448], [33229, 8.9965310749382], [33243, 8.892043600290929], [33271, 8.73823995491883], [33299, 8.594518215833606], [33313, 8.66165323707431], [33327, 8.622062828078647], [33341, 8.851950577607004], [33355, 8.616190365006744], [33369, 8.806406232859318], [33383, 8.599144798093738], [33397, 8.85690752886568], [33411, 8.5675980846072], [33425, 8.665962623006099], [33439, 8.446518892323173], [33453, 11.154857996361716], [33467, 9.756742866550686], [33523, 10.810299163190706], [33537, 10.831996462526769], [33551, 10.588678235870304], [33649, 10.82350759635587], [33705, 10.481565592302397], [33719, 10.632021042572894], [33733, 10.635850726406314], [33747, 10.554738317163775], [33761, 10.373951851391562], [33775, 10.740730549319899], [33803, 10.70942121642436], [33817, 10.73545567905077], [33831, 10.748663479928686], [33845, 10.67439703869048], [34041, 10.398655077974503], [34055, 10.535492767259344], [34069, 10.5404847809123], [34083, 10.699978571118944], [34125, 10.6548034359791], [34139, 10.825986986951719], [34153, 10.916219113688712], [34167, 10.36869314770437]] \ No newline at end of file diff --git a/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json b/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json index e8b32a47a9..a6d3ccc3de 100644 --- a/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json +++ b/graphs/summary/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json @@ -1 +1 @@ -[[28511, 0.16904128919712458], [29225, 0.2908706491549749], [29239, 0.3098731473263805], [29253, 0.16848773782706827], [29267, 0.16641018948225905], [29281, 0.16457824999769605], [29295, 0.1692402835141175], [29309, 0.16964122782816848], [29323, 0.16615569107283307], [29337, 0.16827740084387613], [29351, 0.1701128572503108], [29365, 0.16756966325836947], [29379, 0.1651656125200145], [29393, 0.16618870470286087], [29407, 0.16952237530911526], [29421, 0.16700794190259446], [29435, 0.16884337071306565], [29449, 0.2654014404126435], [29463, 0.2931406597857334], [29477, 0.25880478390685097], [29547, 0.2893439600237337], [29561, 0.268383733290507], [29575, 0.27653155559117004], [29603, 0.2617450574075425], [29617, 0.27542262691019626], [29631, 0.2783078388368581], [29645, 0.2619903351665558], [29659, 0.261987677775439], [29673, 0.2655708041409646], [29743, 0.2741098661646614], [29757, 0.2647400232206697], [29771, 0.2692925487982095], [29785, 0.3075006599629251], [29799, 0.2815253561878479], [29813, 0.26387084276246875], [29827, 0.27504798505122097], [29841, 0.2554933461686309], [29855, 0.24249852250472614], [29869, 0.2467014780464454], [30009, 0.2549980442049543], [30023, 0.2486663301462313], [30037, 0.2512466093104598], [30051, 0.2717890075806762], [30065, 0.2506284226409649], [30079, 0.2544118729934072], [30093, 0.25458787212503753], [30107, 0.2739192324974757], [30121, 0.24227630138222353], [30135, 0.2718649739460112], [30149, 0.2670152377847981], [30163, 0.25636223406920217], [30177, 0.24527373297625565], [30191, 0.25154830532679445], [30205, 0.2722588982090985], [30219, 0.2592466990441231], [30233, 0.26159900940668823], [30247, 0.254216652467278], [30261, 0.2600449128239608], [30513, 0.3359265997765918], [30527, 0.353996351591033], [30541, 0.3388830350728212], [30555, 0.35494119278131553], [30569, 0.35376142705932073], [30583, 0.35060691243192255], [30597, 0.35737448884197454], [30625, 0.3527435646036812], [30639, 0.34201857712649497], [30653, 0.3459355279965606], [30667, 0.34888019512224044], [30681, 0.35960341987788996], [30695, 0.36789554675524566], [30709, 0.3508930715780164], [30723, 0.3537650724461112], [30737, 0.3664502463792893], [30751, 0.34496401015334077], [30765, 0.3422550680781569], [30779, 0.35892791224262266], [30793, 0.3420309258820309], [30807, 0.35460566203199245], [30821, 0.34601600095124685], [30835, 0.32975646322507096], [30849, 0.3460236548251698], [30863, 0.3425585725393968], [30877, 0.35285846741403604], [30891, 0.3608340809425899], [30905, 0.3414218575178134], [30919, 0.3482253878321617], [30933, 0.35293299619634855], [30947, 0.34671376777126717], [30961, 0.3490177293439511], [30975, 0.3594261287077532], [30989, 0.3478479121699331], [31003, 0.33632357150446274], [31017, 0.3492275548971279], [31031, 0.345264985117586], [31045, 0.35790699603416776], [32095, 0.33894138081283887], [32109, 0.3579075224968678], [32123, 0.341512345206705], [32137, 0.3606449601930837], [32151, 0.34581218981923806], [32165, 0.3515373913901514], [32179, 0.36029486019020657], [32193, 0.3543671718031732], [32207, 0.330992726621091], [32221, 0.3266719496649468], [32235, 0.3448331274903846], [32249, 0.31002375160762546], [32263, 0.34050663821972577], [32277, 0.3370386142301938], [32305, 0.32759046385457574], [32319, 0.322504423092764], [32333, 0.3363886256290679], [32347, 0.3161974250124004], [32361, 0.30624036058681076], [32375, 0.3125785484242969], [32389, 0.3166455518642362], [32403, 0.30508901845568737], [32417, 0.33116910645611003], [32431, 0.2976554928558386], [32445, 0.316878118817954], [32585, 0.323142115392602], [32599, 0.3362557236318073], [32613, 0.33879687778271045], [32627, 0.3359746998265935], [32641, 0.3257163199726629], [32655, 0.32672053985059385], [32851, 0.3143105817368051], [32865, 0.31692108835956784], [32879, 0.3245825513579028], [32893, 0.2951964246197827], [32907, 0.30516344962843617], [32921, 0.3117541185584035], [32991, 0.3373978666257404], [33005, 0.3090916610603301], [33019, 0.3309613950067551], [33033, 0.3100028641064927], [33047, 0.30043843540909165], [33061, 0.32080192538410157], [33075, 0.3212931846394939], [33089, 0.3281087675026836], [33103, 0.3135331892689553], [33117, 0.3085823962063044], [33131, 0.31479068995730985], [33145, 0.3063343635202021], [33159, 0.3069126633488857], [33187, 0.3141699062655441], [33201, 0.31554594743813236], [33215, 0.31181922717145283], [33229, 0.2984852836303023], [33243, 0.27911409133401305], [33271, 0.2610668584579801], [33299, 0.3170345492655776], [33313, 0.2759900307270728], [33327, 0.2733637142941156], [33341, 0.26866090090927464], [33355, 0.26574679454877703], [33369, 0.26964915309149773], [33383, 0.2722959697809731], [33397, 0.27270090689102827], [33411, 0.27638862459985286], [33425, 0.26092040929733684], [33439, 0.25687651406043427], [33453, 0.26506363931215804], [33467, 0.27381012945236904], [33523, 0.26429269748517914], [33537, 0.2718910451670681], [33551, 0.2640233387614413], [33649, 0.28501374924620104], [33705, 0.25720128452550634], [33719, 0.2680493119246911], [33733, 0.2601574473498711], [33747, 0.26624139139122216], [33761, 0.26008518990038215], [33775, 0.2600548758216982], [33803, 0.2589240755868284], [33817, 0.26384938407766234], [33831, 0.2614926935893221], [33845, 0.2805174821198038], [34041, 0.28502332345685816], [34055, 0.26563065388840684], [34069, 0.26106651831426403], [34083, 0.27715760321650207], [34125, 0.26585739339336123], [34139, 0.2730671546317706], [34153, 0.26224401001661846], [34167, 0.2667659098483757]] \ No newline at end of file +[[28511, 0.16904128919712458], [29225, 0.2908706491549749], [29239, 0.3098731473263805], [29253, 0.16848773782706827], [29267, 0.16641018948225905], [29281, 0.16457824999769605], [29295, 0.1692402835141175], [29309, 0.16964122782816848], [29323, 0.16615569107283307], [29337, 0.16827740084387613], [29351, 0.1701128572503108], [29365, 0.16756966325836947], [29379, 0.1651656125200145], [29393, 0.16618870470286087], [29407, 0.16952237530911526], [29421, 0.16700794190259446], [29435, 0.16884337071306565], [29449, 0.2654014404126435], [29463, 0.2931406597857334], [29477, 0.25880478390685097], [29547, 0.2893439600237337], [29561, 0.268383733290507], [29575, 0.27653155559117004], [29603, 0.2617450574075425], [29617, 0.27542262691019626], [29631, 0.2783078388368581], [29645, 0.2619903351665558], [29659, 0.261987677775439], [29673, 0.2655708041409646], [29743, 0.2741098661646614], [29757, 0.2647400232206697], [29771, 0.2692925487982095], [29785, 0.3075006599629251], [29799, 0.2815253561878479], [29813, 0.26387084276246875], [29827, 0.27504798505122097], [29841, 0.2554933461686309], [29855, 0.24249852250472614], [29869, 0.2467014780464454], [30009, 0.2549980442049543], [30023, 0.2486663301462313], [30037, 0.2512466093104598], [30051, 0.2717890075806762], [30065, 0.2506284226409649], [30079, 0.2544118729934072], [30093, 0.25458787212503753], [30107, 0.2739192324974757], [30121, 0.24227630138222353], [30135, 0.2718649739460112], [30149, 0.2670152377847981], [30163, 0.25636223406920217], [30177, 0.24527373297625565], [30191, 0.25154830532679445], [30205, 0.2722588982090985], [30219, 0.2592466990441231], [30233, 0.26159900940668823], [30247, 0.254216652467278], [30261, 0.2600449128239608], [30513, 0.3359265997765918], [30527, 0.353996351591033], [30541, 0.3388830350728212], [30555, 0.35494119278131553], [30569, 0.35376142705932073], [30583, 0.35060691243192255], [30597, 0.35737448884197454], [30625, 0.3527435646036812], [30639, 0.34201857712649497], [30653, 0.3459355279965606], [30667, 0.34888019512224044], [30681, 0.35960341987788996], [30695, 0.36789554675524566], [30709, 0.3508930715780164], [30723, 0.3537650724461112], [30737, 0.3664502463792893], [30751, 0.34496401015334077], [30765, 0.3422550680781569], [30779, 0.35892791224262266], [30793, 0.3420309258820309], [30807, 0.35460566203199245], [30821, 0.34601600095124685], [30835, 0.32975646322507096], [30849, 0.3460236548251698], [30863, 0.3425585725393968], [30877, 0.35285846741403604], [30891, 0.3608340809425899], [30905, 0.3414218575178134], [30919, 0.3482253878321617], [30933, 0.35293299619634855], [30947, 0.34671376777126717], [30961, 0.3490177293439511], [30975, 0.3594261287077532], [30989, 0.3478479121699331], [31003, 0.33632357150446274], [31017, 0.3492275548971279], [31031, 0.345264985117586], [31045, 0.35790699603416776], [32095, 0.33894138081283887], [32109, 0.3579075224968678], [32123, 0.341512345206705], [32137, 0.3606449601930837], [32151, 0.34581218981923806], [32165, 0.3515373913901514], [32179, 0.36029486019020657], [32193, 0.3543671718031732], [32207, 0.330992726621091], [32221, 0.3266719496649468], [32235, 0.3448331274903846], [32249, 0.31002375160762546], [32263, 0.34050663821972577], [32277, 0.3370386142301938], [32305, 0.32759046385457574], [32319, 0.322504423092764], [32333, 0.3363886256290679], [32347, 0.3161974250124004], [32361, 0.30624036058681076], [32375, 0.3125785484242969], [32389, 0.3166455518642362], [32403, 0.30508901845568737], [32417, 0.33116910645611003], [32431, 0.2976554928558386], [32445, 0.316878118817954], [32585, 0.323142115392602], [32599, 0.3362557236318073], [32613, 0.33879687778271045], [32627, 0.3359746998265935], [32641, 0.3257163199726629], [32655, 0.32672053985059385], [32851, 0.3143105817368051], [32865, 0.31692108835956784], [32879, 0.3245825513579028], [32893, 0.2951964246197827], [32907, 0.30516344962843617], [32921, 0.3117541185584035], [32991, 0.3373978666257404], [33005, 0.3090916610603301], [33019, 0.3309613950067551], [33033, 0.3100028641064927], [33047, 0.30043843540909165], [33061, 0.32080192538410157], [33075, 0.3212931846394939], [33089, 0.3281087675026836], [33103, 0.3135331892689553], [33117, 0.3085823962063044], [33131, 0.31479068995730985], [33145, 0.3063343635202021], [33159, 0.3069126633488857], [33187, 0.3141699062655441], [33201, 0.31554594743813236], [33215, 0.31181922717145283], [33229, 0.2984852836303023], [33243, 0.27911409133401305], [33271, 0.2610668584579801], [33299, 0.3170345492655776], [33313, 0.2759900307270728], [33327, 0.2733637142941156], [33341, 0.26866090090927464], [33355, 0.26574679454877703], [33369, 0.26964915309149773], [33383, 0.2722959697809731], [33397, 0.27270090689102827], [33411, 0.27638862459985286], [33425, 0.26092040929733684], [33439, 0.25687651406043427], [33453, 0.26506363931215804], [33467, 0.27381012945236904], [33523, 0.26429269748517914], [33537, 0.2718910451670681], [33551, 0.2640233387614413], [33649, 0.28501374924620104], [33705, 0.25720128452550634], [33719, 0.2680493119246911], [33733, 0.2601574473498711], [33747, 0.26624139139122216], [33761, 0.26008518990038215], [33775, 0.2600548758216982], [33803, 0.2589240755868284], [33817, 0.26384938407766234], [33831, 0.2614926935893221], [33845, 0.2805174821198038], [34041, 0.28502332345685816], [34055, 0.26563065388840684], [34069, 0.26106651831426403], [34083, 0.27715760321650207], [34125, 0.26585739339336123], [34139, 0.2730671546317706], [34153, 0.26224401001661846], [34167, 0.2665338093430819]] \ No newline at end of file diff --git a/graphs/summary/decomposition.PCABenchmark.peakmem_fit.json b/graphs/summary/decomposition.PCABenchmark.peakmem_fit.json index 5bdf7baf84..3b014b880b 100644 --- a/graphs/summary/decomposition.PCABenchmark.peakmem_fit.json +++ b/graphs/summary/decomposition.PCABenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 823022357.7900832], [29225, 791601836.3333503], [29239, 792012922.6589046], [29253, 820659416.3851247], [29267, 820808072.5866995], [29281, 820819422.679456], [29295, 820941325.2061819], [29309, 820381524.0019672], [29323, 820799134.0763979], [29337, 820820676.2220087], [29351, 820086576.6426373], [29365, 819856387.4503908], [29379, 820132545.9905057], [29393, 819753296.9597931], [29407, 819960039.8602672], [29421, 820059488.7890491], [29435, 820373965.1572609], [29449, 791849924.094832], [29463, 791793727.3254406], [29477, 791634167.8796532], [29547, 791953369.2237861], [29561, 792094601.124754], [29575, 791523366.835417], [29603, 792314151.8859508], [29617, 792614156.65412], [29631, 792698240.9957119], [29645, 792748406.1817262], [29659, 792722138.279665], [29673, 792481321.0068461], [29743, 792768070.2296319], [29757, 792462897.5876433], [29771, 792607808.9702523], [29785, 792854036.7269288], [29799, 792552741.4279234], [29813, 792841648.9171132], [29827, 793049815.186948], [29841, 792955703.3812721], [29855, 792598481.348442], [29869, 793180232.2792156], [30009, 792649400.4362953], [30023, 792941193.8970695], [30037, 792675585.0328513], [30051, 792757097.7431015], [30065, 792683214.7835078], [30079, 792724784.0154684], [30093, 792709732.3784909], [30107, 792589023.2546], [30121, 792859677.4755403], [30135, 792520797.1397274], [30149, 793048267.0061278], [30163, 793044378.1087065], [30177, 793085570.6361613], [30191, 792988772.6265383], [30205, 792980885.271965], [30219, 793095633.4718422], [30233, 792780403.1825655], [30247, 793238274.8648167], [30261, 792928525.7449602], [30513, 793203058.9194314], [30527, 793078165.1014799], [30541, 793156116.3390495], [30555, 792777806.9887921], [30569, 792879685.0761164], [30583, 793092861.5166826], [30597, 792996019.6797109], [30625, 792935230.0089802], [30639, 793284514.292048], [30653, 792895445.2029253], [30667, 792604033.4188514], [30681, 792842480.4775863], [30695, 793149872.6102856], [30709, 792931425.3364332], [30723, 793069060.3131821], [30737, 792949273.0418696], [30751, 793042857.8237368], [30765, 793454784.9441185], [30779, 653249992.1436985], [30793, 653287503.6754471], [30807, 653128057.6852517], [30821, 653462699.2989933], [30835, 653658006.4602817], [30849, 652981305.3236399], [30863, 653350936.015498], [30877, 653632008.9660248], [30891, 653558700.2830198], [30905, 653436665.3768009], [30919, 653351349.5106875], [30933, 653208782.0324814], [30947, 653125599.6536472], [30961, 653277980.7525963], [30975, 653604177.7903929], [30989, 653524919.789609], [31003, 653777762.4326503], [31017, 653250418.831668], [31031, null], [31045, 653416108.1569178], [32109, 665212724.0130844], [32123, 665189390.3606033], [32137, 665402421.7400273], [32151, 665455180.6410706], [32165, 665247195.7578777], [32179, 665191554.9687709], [32193, 665260397.1315495], [32207, 667027707.8435616], [32221, 668737663.6041865], [32235, 668991229.2397528], [32249, 668235004.1755333], [32263, 668553215.175564], [32277, 668999360.6633558], [32305, 669675476.1250874], [32319, 672145531.3404765], [32333, 672125542.3097111], [32347, 671887406.9574933], [32361, 672035333.9480015], [32375, 671898623.9457405], [32389, 671898459.7386944], [32403, 672189923.4910431], [32417, 671971444.851518], [32431, 672233285.1559422], [32445, 672027748.8060696], [32585, 672472393.9669324], [32599, 672618197.9207112], [32613, 672605874.5108188], [32627, 672614150.3698024], [32641, 672560832.7680651], [32655, 672322027.3918089], [32851, 674558245.0934073], [32865, 674484267.2538265], [32879, 674746508.5591398], [32893, 674438147.0193816], [32907, 674801149.1577779], [32921, 674502717.8360751], [32991, 673976488.5373112], [33005, 674515930.0274447], [33019, 674179522.8428308], [33033, 674972632.7130306], [33047, 674960213.2723998], [33061, 675084826.0248871], [33075, 675006826.4676443], [33089, 689972577.6846756], [33103, 704975658.7052392], [33117, 704886678.5352066], [33131, 705014431.3291302], [33145, 705358049.4891063], [33159, 704858855.740922], [33187, 675084635.4784176], [33201, 675060919.7610364], [33215, 678388337.8891772], [33229, 688611793.0190806], [33243, 688749816.0827309], [33271, 702355741.7367594], [33299, 702719807.4815627], [33313, 702725464.6148301], [33327, 703199127.9448624], [33341, 702958196.6839894], [33355, 703303690.3692409], [33369, 703790195.77102], [33383, 704185510.2541391], [33397, 704580751.0993712], [33411, 704090315.067658], [33425, 704588349.7651169], [33439, 709363666.8893925], [33453, 704467308.2325615], [33467, 704873850.6671537], [33523, 704756898.2340844], [33537, 704681647.9338804], [33551, 704384627.7037503], [33649, 703571171.0748494], [33705, 702905518.8594898], [33719, 703040042.6975349], [33733, 703323504.6202909], [33747, 703182755.8481035], [33761, 703199556.6952105], [33775, 703075317.7784309], [33803, 702958658.4602942], [33817, 702786553.5656111], [33831, 702845811.6981406], [33845, 702429264.6245764], [34041, 702498449.9593215], [34055, 702646625.1329283], [34069, 702615062.4829386], [34083, 702809933.8703476], [34125, 701538289.9227428], [34139, 702801793.2935152], [34153, 702758876.0237982], [34167, 702652731.3517799]] \ No newline at end of file +[[28511, 823022357.7900832], [29225, 791601836.3333503], [29239, 792012922.6589046], [29253, 820659416.3851247], [29267, 820808072.5866995], [29281, 820819422.679456], [29295, 820941325.2061819], [29309, 820381524.0019672], [29323, 820799134.0763979], [29337, 820820676.2220087], [29351, 820086576.6426373], [29365, 819856387.4503908], [29379, 820132545.9905057], [29393, 819753296.9597931], [29407, 819960039.8602672], [29421, 820059488.7890491], [29435, 820373965.1572609], [29449, 791849924.094832], [29463, 791793727.3254406], [29477, 791634167.8796532], [29547, 791953369.2237861], [29561, 792094601.124754], [29575, 791523366.835417], [29603, 792314151.8859508], [29617, 792614156.65412], [29631, 792698240.9957119], [29645, 792748406.1817262], [29659, 792722138.279665], [29673, 792481321.0068461], [29743, 792768070.2296319], [29757, 792462897.5876433], [29771, 792607808.9702523], [29785, 792854036.7269288], [29799, 792552741.4279234], [29813, 792841648.9171132], [29827, 793049815.186948], [29841, 792955703.3812721], [29855, 792598481.348442], [29869, 793180232.2792156], [30009, 792649400.4362953], [30023, 792941193.8970695], [30037, 792675585.0328513], [30051, 792757097.7431015], [30065, 792683214.7835078], [30079, 792724784.0154684], [30093, 792709732.3784909], [30107, 792589023.2546], [30121, 792859677.4755403], [30135, 792520797.1397274], [30149, 793048267.0061278], [30163, 793044378.1087065], [30177, 793085570.6361613], [30191, 792988772.6265383], [30205, 792980885.271965], [30219, 793095633.4718422], [30233, 792780403.1825655], [30247, 793238274.8648167], [30261, 792928525.7449602], [30513, 793203058.9194314], [30527, 793078165.1014799], [30541, 793156116.3390495], [30555, 792777806.9887921], [30569, 792879685.0761164], [30583, 793092861.5166826], [30597, 792996019.6797109], [30625, 792935230.0089802], [30639, 793284514.292048], [30653, 792895445.2029253], [30667, 792604033.4188514], [30681, 792842480.4775863], [30695, 793149872.6102856], [30709, 792931425.3364332], [30723, 793069060.3131821], [30737, 792949273.0418696], [30751, 793042857.8237368], [30765, 793454784.9441185], [30779, 653249992.1436985], [30793, 653287503.6754471], [30807, 653128057.6852517], [30821, 653462699.2989933], [30835, 653658006.4602817], [30849, 652981305.3236399], [30863, 653350936.015498], [30877, 653632008.9660248], [30891, 653558700.2830198], [30905, 653436665.3768009], [30919, 653351349.5106875], [30933, 653208782.0324814], [30947, 653125599.6536472], [30961, 653277980.7525963], [30975, 653604177.7903929], [30989, 653524919.789609], [31003, 653777762.4326503], [31017, 653250418.831668], [31031, null], [31045, 653416108.1569178], [32109, 665212724.0130844], [32123, 665189390.3606033], [32137, 665402421.7400273], [32151, 665455180.6410706], [32165, 665247195.7578777], [32179, 665191554.9687709], [32193, 665260397.1315495], [32207, 667027707.8435616], [32221, 668737663.6041865], [32235, 668991229.2397528], [32249, 668235004.1755333], [32263, 668553215.175564], [32277, 668999360.6633558], [32305, 669675476.1250874], [32319, 672145531.3404765], [32333, 672125542.3097111], [32347, 671887406.9574933], [32361, 672035333.9480015], [32375, 671898623.9457405], [32389, 671898459.7386944], [32403, 672189923.4910431], [32417, 671971444.851518], [32431, 672233285.1559422], [32445, 672027748.8060696], [32585, 672472393.9669324], [32599, 672618197.9207112], [32613, 672605874.5108188], [32627, 672614150.3698024], [32641, 672560832.7680651], [32655, 672322027.3918089], [32851, 674558245.0934073], [32865, 674484267.2538265], [32879, 674746508.5591398], [32893, 674438147.0193816], [32907, 674801149.1577779], [32921, 674502717.8360751], [32991, 673976488.5373112], [33005, 674515930.0274447], [33019, 674179522.8428308], [33033, 674972632.7130306], [33047, 674960213.2723998], [33061, 675084826.0248871], [33075, 675006826.4676443], [33089, 689972577.6846756], [33103, 704975658.7052392], [33117, 704886678.5352066], [33131, 705014431.3291302], [33145, 705358049.4891063], [33159, 704858855.740922], [33187, 675084635.4784176], [33201, 675060919.7610364], [33215, 678388337.8891772], [33229, 688611793.0190806], [33243, 688749816.0827309], [33271, 702355741.7367594], [33299, 702719807.4815627], [33313, 702725464.6148301], [33327, 703199127.9448624], [33341, 702958196.6839894], [33355, 703303690.3692409], [33369, 703790195.77102], [33383, 704185510.2541391], [33397, 704580751.0993712], [33411, 704090315.067658], [33425, 704588349.7651169], [33439, 709363666.8893925], [33453, 704467308.2325615], [33467, 704873850.6671537], [33523, 704756898.2340844], [33537, 704681647.9338804], [33551, 704384627.7037503], [33649, 703571171.0748494], [33705, 702905518.8594898], [33719, 703040042.6975349], [33733, 703323504.6202909], [33747, 703182755.8481035], [33761, 703199556.6952105], [33775, 703075317.7784309], [33803, 702958658.4602942], [33817, 702786553.5656111], [33831, 702845811.6981406], [33845, 702429264.6245764], [34041, 702498449.9593215], [34055, 702646625.1329283], [34069, 702615062.4829386], [34083, 702809933.8703476], [34125, 701538289.9227428], [34139, 702801793.2935152], [34153, 702758876.0237982], [34167, 702615936.4813306]] \ No newline at end of file diff --git a/graphs/summary/decomposition.PCABenchmark.peakmem_transform.json b/graphs/summary/decomposition.PCABenchmark.peakmem_transform.json index f8fb5c2e21..f9caa4a43a 100644 --- a/graphs/summary/decomposition.PCABenchmark.peakmem_transform.json +++ b/graphs/summary/decomposition.PCABenchmark.peakmem_transform.json @@ -1 +1 @@ -[[28511, 505952927.5002441], [29225, 501583871.16381025], [29239, 501707570.865734], [29253, 502881387.4372758], [29267, 503078220.49329513], [29281, 503040644.5145283], [29295, 503283701.64167124], [29309, 502874786.67941576], [29323, 503115414.24468803], [29337, 503773390.9648521], [29351, 502923241.04255193], [29365, 502753921.950677], [29379, 503311689.3663095], [29393, 503105292.3252177], [29407, 503100725.64963603], [29421, 503035551.2745229], [29435, 503399744.9812626], [29449, 502204643.238815], [29463, 502105702.0658948], [29477, 502173695.16479236], [29547, 502378495.99999934], [29561, 502242417.7753032], [29575, 501854207.9999995], [29603, 502743039.9999995], [29617, 502833151.9999994], [29631, 502919167.9999996], [29645, 502964223.58311], [29659, 502936575.9999994], [29673, 502872746.38866735], [29743, 502863871.58299565], [29757, 502919167.5830296], [29771, 503025663.9999994], [29785, 503127380.8867387], [29799, 502935824.887249], [29813, 503055701.33148015], [29827, 503166293.33148074], [29841, 503048191.99999946], [29855, 502874111.99999934], [29869, 503277567.9999994], [30009, 502953983.5829131], [30023, 503001087.5831574], [30037, 502741219.55308247], [30051, 502747135.99999934], [30065, 502743039.9999994], [30079, 502888740.57036936], [30093, 502821546.66295874], [30107, 502787640.886417], [30121, 502931000.88765293], [30135, 502835882.6648128], [30149, 503093930.66481334], [30163, 503257770.66666603], [30177, 503564287.9999994], [30191, 503312042.48518276], [30205, 503263687.10987586], [30219, 503314841.4540793], [30233, 503104853.3296276], [30247, 503390207.99999946], [30261, 503167999.99999946], [30513, 503421951.99999946], [30527, 503248213.33259183], [30541, 503207708.44320965], [30555, 503100529.65680116], [30569, 503089834.66481394], [30583, 503332863.9999994], [30597, 502982655.99999946], [30625, 503336959.99999946], [30639, 503229780.9704075], [30653, 503123057.65670663], [30667, 503129429.33148026], [30681, 503193599.99999934], [30695, 503342421.32962924], [30709, 503104853.33148026], [30723, 503083007.9999994], [30737, 503223978.4852286], [30751, 503265621.33240664], [30765, 503567701.0904193], [30779, 503181311.9999994], [30793, 503129429.3333327], [30807, 503240021.33148086], [30821, 503406591.9999994], [30835, 503442090.66296333], [30849, 503197695.9999995], [30863, 503388159.9999995], [30877, 503457791.99999946], [30891, 503597738.66296446], [30905, 503462570.66296333], [30919, 503343331.31354386], [30933, 503252309.3314808], [30947, 503264597.33148026], [30961, 503256405.33333284], [30975, 503457109.3314804], [30989, 503366087.1086411], [31003, 503743146.66296554], [31017, 503336959.9999995], [31031, null], [31045, 503336959.99999946], [32109, 514822143.9999995], [32123, 514899967.9999994], [32137, 514874026.6666661], [32151, 514828287.9999994], [32165, 514859007.9999994], [32179, 514801663.99999934], [32193, 514968234.66425276], [32207, 516189183.99999946], [32221, 517520042.6666662], [32235, 517971967.9999995], [32249, 517545983.9999995], [32263, 517568648.3921715], [32277, 517423103.99999946], [32305, 518595014.87458533], [32319, 520710371.3215783], [32333, 520881493.32975394], [32347, 520677717.33154273], [32361, 520698538.4911726], [32375, 520753151.99999946], [32389, 520585215.99999946], [32403, 520671231.1944635], [32417, 520740863.9999995], [32431, 520797525.33154327], [32445, 520972970.6630879], [32585, 520882858.66666603], [32599, 520987989.3333327], [32613, 520998911.731572], [32627, 521031679.99999934], [32641, 520828927.9964202], [32655, 520913805.98842907], [32851, 521729365.3333328], [32865, 521820159.9999994], [32879, 522081621.3333328], [32893, 522096639.99999934], [32907, 522089813.33333284], [32921, 521946453.3315475], [32991, 521895935.99999934], [33005, 521875455.9999994], [33019, 521515007.99999934], [33033, 521848831.9999994], [33047, 522096639.99999934], [33061, 522231125.3315476], [33075, 522141695.99999934], [33089, 536557567.99999934], [33103, 551045347.5510465], [33117, 551352319.9966184], [33131, 551165269.3265684], [33145, 551155029.3299505], [33159, 551156394.6632837], [33187, 522280959.99999946], [33201, 522331477.3315485], [33215, 530043322.4689884], [33229, 553617256.3269553], [33243, 553598641.7664247], [33271, 586510335.9904643], [33299, 586914474.6634899], [33313, 586915157.2936301], [33327, 587332949.1983817], [33341, 587254101.2769924], [33355, 587441038.13443], [33369, 587939839.9556075], [33383, 588166030.1588266], [33397, 588506453.3174981], [33411, 588408149.3206602], [33425, 588497578.5890557], [33439, 589470378.6129062], [33453, 584656213.3205788], [33467, 584859647.9713137], [33523, 584799914.6467439], [33537, 584881493.2355915], [33551, 584344462.133946], [33649, 583169336.2382492], [33705, 582833480.1264544], [33719, 583100737.9182577], [33733, 583092856.6224174], [33747, 583042373.7042657], [33761, 583053311.6259228], [33775, 583076514.9422712], [33803, 583254002.8742601], [33817, 582860106.5855668], [33831, 582809368.4443167], [33845, 582914035.2964609], [34041, 582580888.781048], [34055, 582890355.3652695], [34069, 582809362.3436351], [34083, 582383601.7440443], [34125, 582837113.7889576], [34139, 582852604.4212025], [34153, 582789328.0082688], [34167, 582715033.6670645]] \ No newline at end of file +[[28511, 505952927.5002441], [29225, 501583871.16381025], [29239, 501707570.865734], [29253, 502881387.4372758], [29267, 503078220.49329513], [29281, 503040644.5145283], [29295, 503283701.64167124], [29309, 502874786.67941576], [29323, 503115414.24468803], [29337, 503773390.9648521], [29351, 502923241.04255193], [29365, 502753921.950677], [29379, 503311689.3663095], [29393, 503105292.3252177], [29407, 503100725.64963603], [29421, 503035551.2745229], [29435, 503399744.9812626], [29449, 502204643.238815], [29463, 502105702.0658948], [29477, 502173695.16479236], [29547, 502378495.99999934], [29561, 502242417.7753032], [29575, 501854207.9999995], [29603, 502743039.9999995], [29617, 502833151.9999994], [29631, 502919167.9999996], [29645, 502964223.58311], [29659, 502936575.9999994], [29673, 502872746.38866735], [29743, 502863871.58299565], [29757, 502919167.5830296], [29771, 503025663.9999994], [29785, 503127380.8867387], [29799, 502935824.887249], [29813, 503055701.33148015], [29827, 503166293.33148074], [29841, 503048191.99999946], [29855, 502874111.99999934], [29869, 503277567.9999994], [30009, 502953983.5829131], [30023, 503001087.5831574], [30037, 502741219.55308247], [30051, 502747135.99999934], [30065, 502743039.9999994], [30079, 502888740.57036936], [30093, 502821546.66295874], [30107, 502787640.886417], [30121, 502931000.88765293], [30135, 502835882.6648128], [30149, 503093930.66481334], [30163, 503257770.66666603], [30177, 503564287.9999994], [30191, 503312042.48518276], [30205, 503263687.10987586], [30219, 503314841.4540793], [30233, 503104853.3296276], [30247, 503390207.99999946], [30261, 503167999.99999946], [30513, 503421951.99999946], [30527, 503248213.33259183], [30541, 503207708.44320965], [30555, 503100529.65680116], [30569, 503089834.66481394], [30583, 503332863.9999994], [30597, 502982655.99999946], [30625, 503336959.99999946], [30639, 503229780.9704075], [30653, 503123057.65670663], [30667, 503129429.33148026], [30681, 503193599.99999934], [30695, 503342421.32962924], [30709, 503104853.33148026], [30723, 503083007.9999994], [30737, 503223978.4852286], [30751, 503265621.33240664], [30765, 503567701.0904193], [30779, 503181311.9999994], [30793, 503129429.3333327], [30807, 503240021.33148086], [30821, 503406591.9999994], [30835, 503442090.66296333], [30849, 503197695.9999995], [30863, 503388159.9999995], [30877, 503457791.99999946], [30891, 503597738.66296446], [30905, 503462570.66296333], [30919, 503343331.31354386], [30933, 503252309.3314808], [30947, 503264597.33148026], [30961, 503256405.33333284], [30975, 503457109.3314804], [30989, 503366087.1086411], [31003, 503743146.66296554], [31017, 503336959.9999995], [31031, null], [31045, 503336959.99999946], [32109, 514822143.9999995], [32123, 514899967.9999994], [32137, 514874026.6666661], [32151, 514828287.9999994], [32165, 514859007.9999994], [32179, 514801663.99999934], [32193, 514968234.66425276], [32207, 516189183.99999946], [32221, 517520042.6666662], [32235, 517971967.9999995], [32249, 517545983.9999995], [32263, 517568648.3921715], [32277, 517423103.99999946], [32305, 518595014.87458533], [32319, 520710371.3215783], [32333, 520881493.32975394], [32347, 520677717.33154273], [32361, 520698538.4911726], [32375, 520753151.99999946], [32389, 520585215.99999946], [32403, 520671231.1944635], [32417, 520740863.9999995], [32431, 520797525.33154327], [32445, 520972970.6630879], [32585, 520882858.66666603], [32599, 520987989.3333327], [32613, 520998911.731572], [32627, 521031679.99999934], [32641, 520828927.9964202], [32655, 520913805.98842907], [32851, 521729365.3333328], [32865, 521820159.9999994], [32879, 522081621.3333328], [32893, 522096639.99999934], [32907, 522089813.33333284], [32921, 521946453.3315475], [32991, 521895935.99999934], [33005, 521875455.9999994], [33019, 521515007.99999934], [33033, 521848831.9999994], [33047, 522096639.99999934], [33061, 522231125.3315476], [33075, 522141695.99999934], [33089, 536557567.99999934], [33103, 551045347.5510465], [33117, 551352319.9966184], [33131, 551165269.3265684], [33145, 551155029.3299505], [33159, 551156394.6632837], [33187, 522280959.99999946], [33201, 522331477.3315485], [33215, 530043322.4689884], [33229, 553617256.3269553], [33243, 553598641.7664247], [33271, 586510335.9904643], [33299, 586914474.6634899], [33313, 586915157.2936301], [33327, 587332949.1983817], [33341, 587254101.2769924], [33355, 587441038.13443], [33369, 587939839.9556075], [33383, 588166030.1588266], [33397, 588506453.3174981], [33411, 588408149.3206602], [33425, 588497578.5890557], [33439, 589470378.6129062], [33453, 584656213.3205788], [33467, 584859647.9713137], [33523, 584799914.6467439], [33537, 584881493.2355915], [33551, 584344462.133946], [33649, 583169336.2382492], [33705, 582833480.1264544], [33719, 583100737.9182577], [33733, 583092856.6224174], [33747, 583042373.7042657], [33761, 583053311.6259228], [33775, 583076514.9422712], [33803, 583254002.8742601], [33817, 582860106.5855668], [33831, 582809368.4443167], [33845, 582914035.2964609], [34041, 582580888.781048], [34055, 582890355.3652695], [34069, 582809362.3436351], [34083, 582383601.7440443], [34125, 582837113.7889576], [34139, 582852604.4212025], [34153, 582789328.0082688], [34167, 582661170.7773298]] \ No newline at end of file diff --git a/graphs/summary/decomposition.PCABenchmark.time_fit.json b/graphs/summary/decomposition.PCABenchmark.time_fit.json index c9039484d8..b1e5321112 100644 --- a/graphs/summary/decomposition.PCABenchmark.time_fit.json +++ b/graphs/summary/decomposition.PCABenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 1.6368591832466168], [29225, 1.4312503204941278], [29239, 1.3774598600675205], [29253, 1.739384835502188], [29267, 1.7790333598545338], [29281, 1.7748897663351422], [29295, 1.7014585115255574], [29309, 1.8560046739526368], [29323, 1.7579303490709495], [29337, 1.6938743738790425], [29351, 1.803495365459255], [29365, 1.660637315841992], [29379, 1.7644776900358738], [29393, 1.7618056204279775], [29407, 1.706481687277975], [29421, 1.724146300217711], [29435, 1.7472216009781796], [29449, 1.3503793594294742], [29463, 1.3649196092581914], [29477, 1.3400346707876682], [29547, 1.4043564207120596], [29561, 1.2655913927991678], [29575, 1.4362796364877535], [29603, 1.1854292862634659], [29617, 1.1718533662899393], [29631, 1.1807519403400093], [29645, 1.1673658298698504], [29659, 1.1794383045596382], [29673, 1.1700340907585438], [29743, 1.1646078648486435], [29757, 1.1844754691879809], [29771, 1.1733712326714385], [29785, 1.3394621660703692], [29799, 1.3805413663883832], [29813, 1.3874447522396536], [29827, 1.416149283610513], [29841, 1.342292304002878], [29855, 1.243570578885068], [29869, 1.3997809912461028], [30009, 1.3867728197259677], [30023, 1.3663277475330553], [30037, 1.3795524818090046], [30051, 1.4280975613283353], [30065, 1.5324286371891005], [30079, 1.3921276065702182], [30093, 1.3295981551114568], [30107, 1.3708997433672436], [30121, 1.3427791968651237], [30135, 1.3408997802358278], [30149, 1.4233369073936992], [30163, 1.3764596169120036], [30177, 1.349516346826288], [30191, 1.371570861518613], [30205, 1.379790659037534], [30219, 1.3707540416708515], [30233, 1.38664821706968], [30247, 1.4121744504390026], [30261, 1.405453320726203], [30513, 1.4008550601051128], [30527, 1.3679478417770279], [30541, 1.3393689843471999], [30555, 1.3489363818115203], [30569, 1.3314995868746613], [30583, 1.3838369916716609], [30597, 1.3088939546980005], [30625, 1.4026996683950956], [30639, 1.3666034638485562], [30653, 1.3981215304579404], [30667, 1.32618816590058], [30681, 1.3808784036667605], [30695, 1.3789821939119549], [30709, 1.4127973133531277], [30723, 1.3560281536944228], [30737, 1.4094171773825017], [30751, 1.385625246391352], [30765, 1.4365936976937894], [30779, 1.194606847440425], [30793, 1.254697722656241], [30807, 1.2111335885583956], [30821, 1.1977668073256962], [30835, 1.1814859459820142], [30849, 1.2453253054744382], [30863, 1.226610804898172], [30877, 1.2193483522336332], [30891, 1.2422022974518983], [30905, 1.1903219410198875], [30919, 1.1769848735681412], [30933, 1.2034824762261223], [30947, 1.2086118544411133], [30961, 1.2259869000883297], [30975, 1.2032296724388996], [30989, 1.199381027739877], [31003, 1.218279427432729], [31017, 1.2462907605687912], [31031, null], [31045, 1.241528242100417], [32109, 1.0414213633383254], [32123, 1.0322395274718092], [32137, 1.0168250281376026], [32151, 1.03044205400235], [32165, 1.018647110095175], [32179, 1.0315763943105971], [32193, 1.036088397061509], [32207, 1.0284485583894019], [32221, 1.035002463308038], [32235, 1.0282948105609822], [32249, 1.0357488213035524], [32263, 1.2158285021309934], [32277, 1.204617708875041], [32305, 1.1985223095316873], [32319, 1.2054071334121736], [32333, 1.2495884436893097], [32347, 1.2121536796575714], [32361, 1.228750693387447], [32375, 1.209424823835723], [32389, 1.2527973416012637], [32403, 1.2688483117512641], [32417, 1.2576451106533866], [32431, 1.2031060045283666], [32445, 1.218224693479588], [32585, 1.1119493910823897], [32599, 1.0467105734407542], [32613, 1.0352306894277428], [32627, 0.9964627608232657], [32641, 1.0737411832958115], [32655, 1.0209647031488942], [32851, 1.0352291707150505], [32865, 1.0273652213670676], [32879, 1.0277470759967402], [32893, 1.0362442133245953], [32907, 1.0417212500481579], [32921, 1.0338138434681083], [32991, 1.0390442448962893], [33005, 1.0299079624252725], [33019, 1.0321527241769448], [33033, 1.0376842974484268], [33047, 1.044283135747055], [33061, 1.0318605221755086], [33075, 1.0367283519509796], [33089, 1.0226064588743038], [33103, 1.0339363068813376], [33117, 1.0380417771722266], [33131, 1.0329034622410664], [33145, 1.0211473834434912], [33159, 1.0344156479058162], [33187, 1.0422698102535375], [33201, 1.0294404696549164], [33215, 1.1122883376722736], [33229, 1.3816344883235403], [33243, 1.380478964435671], [33271, 1.8364887066583355], [33299, 1.9772055828226913], [33313, 1.7823322984364605], [33327, 1.8869041067033843], [33341, 1.8783930111438134], [33355, 1.8788246935616126], [33369, 1.7558737497683374], [33383, 1.9187959041299087], [33397, 1.9098662648579716], [33411, 1.8602106359960013], [33425, 1.8660176975825815], [33439, 1.851336651782018], [33453, 1.895844465125382], [33467, 1.8415594399123392], [33523, 1.8797945040680477], [33537, 1.902725582801062], [33551, 1.8729873809710345], [33649, 1.9559991765494817], [33705, 1.9949801866728885], [33719, 1.8974814420854458], [33733, 1.6035926632176576], [33747, 1.6192348906628173], [33761, 1.574796859826654], [33775, 1.609213778263419], [33803, 1.432285795183541], [33817, 1.4321187154371957], [33831, 1.4426820744978002], [33845, 1.459458168022776], [34041, 1.511950379505631], [34055, 1.590516876686752], [34069, 1.605924760379758], [34083, 1.6169535761542644], [34125, 1.4652214498555338], [34139, 1.4421053564184243], [34153, 1.4518993651049839], [34167, 1.4375324076270566]] \ No newline at end of file +[[28511, 1.6368591832466168], [29225, 1.4312503204941278], [29239, 1.3774598600675205], [29253, 1.739384835502188], [29267, 1.7790333598545338], [29281, 1.7748897663351422], [29295, 1.7014585115255574], [29309, 1.8560046739526368], [29323, 1.7579303490709495], [29337, 1.6938743738790425], [29351, 1.803495365459255], [29365, 1.660637315841992], [29379, 1.7644776900358738], [29393, 1.7618056204279775], [29407, 1.706481687277975], [29421, 1.724146300217711], [29435, 1.7472216009781796], [29449, 1.3503793594294742], [29463, 1.3649196092581914], [29477, 1.3400346707876682], [29547, 1.4043564207120596], [29561, 1.2655913927991678], [29575, 1.4362796364877535], [29603, 1.1854292862634659], [29617, 1.1718533662899393], [29631, 1.1807519403400093], [29645, 1.1673658298698504], [29659, 1.1794383045596382], [29673, 1.1700340907585438], [29743, 1.1646078648486435], [29757, 1.1844754691879809], [29771, 1.1733712326714385], [29785, 1.3394621660703692], [29799, 1.3805413663883832], [29813, 1.3874447522396536], [29827, 1.416149283610513], [29841, 1.342292304002878], [29855, 1.243570578885068], [29869, 1.3997809912461028], [30009, 1.3867728197259677], [30023, 1.3663277475330553], [30037, 1.3795524818090046], [30051, 1.4280975613283353], [30065, 1.5324286371891005], [30079, 1.3921276065702182], [30093, 1.3295981551114568], [30107, 1.3708997433672436], [30121, 1.3427791968651237], [30135, 1.3408997802358278], [30149, 1.4233369073936992], [30163, 1.3764596169120036], [30177, 1.349516346826288], [30191, 1.371570861518613], [30205, 1.379790659037534], [30219, 1.3707540416708515], [30233, 1.38664821706968], [30247, 1.4121744504390026], [30261, 1.405453320726203], [30513, 1.4008550601051128], [30527, 1.3679478417770279], [30541, 1.3393689843471999], [30555, 1.3489363818115203], [30569, 1.3314995868746613], [30583, 1.3838369916716609], [30597, 1.3088939546980005], [30625, 1.4026996683950956], [30639, 1.3666034638485562], [30653, 1.3981215304579404], [30667, 1.32618816590058], [30681, 1.3808784036667605], [30695, 1.3789821939119549], [30709, 1.4127973133531277], [30723, 1.3560281536944228], [30737, 1.4094171773825017], [30751, 1.385625246391352], [30765, 1.4365936976937894], [30779, 1.194606847440425], [30793, 1.254697722656241], [30807, 1.2111335885583956], [30821, 1.1977668073256962], [30835, 1.1814859459820142], [30849, 1.2453253054744382], [30863, 1.226610804898172], [30877, 1.2193483522336332], [30891, 1.2422022974518983], [30905, 1.1903219410198875], [30919, 1.1769848735681412], [30933, 1.2034824762261223], [30947, 1.2086118544411133], [30961, 1.2259869000883297], [30975, 1.2032296724388996], [30989, 1.199381027739877], [31003, 1.218279427432729], [31017, 1.2462907605687912], [31031, null], [31045, 1.241528242100417], [32109, 1.0414213633383254], [32123, 1.0322395274718092], [32137, 1.0168250281376026], [32151, 1.03044205400235], [32165, 1.018647110095175], [32179, 1.0315763943105971], [32193, 1.036088397061509], [32207, 1.0284485583894019], [32221, 1.035002463308038], [32235, 1.0282948105609822], [32249, 1.0357488213035524], [32263, 1.2158285021309934], [32277, 1.204617708875041], [32305, 1.1985223095316873], [32319, 1.2054071334121736], [32333, 1.2495884436893097], [32347, 1.2121536796575714], [32361, 1.228750693387447], [32375, 1.209424823835723], [32389, 1.2527973416012637], [32403, 1.2688483117512641], [32417, 1.2576451106533866], [32431, 1.2031060045283666], [32445, 1.218224693479588], [32585, 1.1119493910823897], [32599, 1.0467105734407542], [32613, 1.0352306894277428], [32627, 0.9964627608232657], [32641, 1.0737411832958115], [32655, 1.0209647031488942], [32851, 1.0352291707150505], [32865, 1.0273652213670676], [32879, 1.0277470759967402], [32893, 1.0362442133245953], [32907, 1.0417212500481579], [32921, 1.0338138434681083], [32991, 1.0390442448962893], [33005, 1.0299079624252725], [33019, 1.0321527241769448], [33033, 1.0376842974484268], [33047, 1.044283135747055], [33061, 1.0318605221755086], [33075, 1.0367283519509796], [33089, 1.0226064588743038], [33103, 1.0339363068813376], [33117, 1.0380417771722266], [33131, 1.0329034622410664], [33145, 1.0211473834434912], [33159, 1.0344156479058162], [33187, 1.0422698102535375], [33201, 1.0294404696549164], [33215, 1.1122883376722736], [33229, 1.3816344883235403], [33243, 1.380478964435671], [33271, 1.8364887066583355], [33299, 1.9772055828226913], [33313, 1.7823322984364605], [33327, 1.8869041067033843], [33341, 1.8783930111438134], [33355, 1.8788246935616126], [33369, 1.7558737497683374], [33383, 1.9187959041299087], [33397, 1.9098662648579716], [33411, 1.8602106359960013], [33425, 1.8660176975825815], [33439, 1.851336651782018], [33453, 1.895844465125382], [33467, 1.8415594399123392], [33523, 1.8797945040680477], [33537, 1.902725582801062], [33551, 1.8729873809710345], [33649, 1.9559991765494817], [33705, 1.9949801866728885], [33719, 1.8974814420854458], [33733, 1.6035926632176576], [33747, 1.6192348906628173], [33761, 1.574796859826654], [33775, 1.609213778263419], [33803, 1.432285795183541], [33817, 1.4321187154371957], [33831, 1.4426820744978002], [33845, 1.459458168022776], [34041, 1.511950379505631], [34055, 1.590516876686752], [34069, 1.605924760379758], [34083, 1.6169535761542644], [34125, 1.4652214498555338], [34139, 1.4421053564184243], [34153, 1.4518993651049839], [34167, 1.438122363766188]] \ No newline at end of file diff --git a/graphs/summary/decomposition.PCABenchmark.time_transform.json b/graphs/summary/decomposition.PCABenchmark.time_transform.json index 295b44c600..c5a2273bba 100644 --- a/graphs/summary/decomposition.PCABenchmark.time_transform.json +++ b/graphs/summary/decomposition.PCABenchmark.time_transform.json @@ -1 +1 @@ -[[28511, 0.09379044078892974], [29225, 0.19087374746870495], [29239, 0.18308414931852107], [29253, 0.09608386123411387], [29267, 0.09754716067298128], [29281, 0.09991364980502303], [29295, 0.09724117731909654], [29309, 0.09762595535104279], [29323, 0.09927695393711455], [29337, 0.09647535384223756], [29351, 0.0971082268943414], [29365, 0.09407399997198918], [29379, 0.09681261977596323], [29393, 0.10099642659499107], [29407, 0.09829767115741095], [29421, 0.09812622785119413], [29435, 0.09728976442712534], [29449, 0.17988762418486884], [29463, 0.1883305536760536], [29477, 0.18861556814805228], [29547, 0.19440761342141616], [29561, 0.177355496778817], [29575, 0.18071339345222495], [29603, 0.17774785851018565], [29617, 0.1749661386668798], [29631, 0.17315087188809986], [29645, 0.17462219024393622], [29659, 0.1727642620017645], [29673, 0.1733100851846101], [29743, 0.1748391184492784], [29757, 0.17495470874932897], [29771, 0.1751171582035474], [29785, 0.18175826630752318], [29799, 0.18249203932271527], [29813, 0.19285932614006585], [29827, 0.19664651061146488], [29841, 0.19235760231882149], [29855, 0.17895501880641015], [29869, 0.18993067800720548], [30009, 0.18692832638721074], [30023, 0.18054291162828207], [30037, 0.18448226509471208], [30051, 0.18266356950660148], [30065, 0.19048874840690502], [30079, 0.186554677202648], [30093, 0.18166450040157958], [30107, 0.2003111362382836], [30121, 0.1847276420245596], [30135, 0.2001825250447581], [30149, 0.19307761434901172], [30163, 0.193432527821332], [30177, 0.18650983609706934], [30191, 0.1869738584531503], [30205, 0.19380904840314195], [30219, 0.18510250680802148], [30233, 0.18668816748651784], [30247, 0.1876043583715968], [30261, 0.18755317235701097], [30513, 0.18625989911963606], [30527, 0.18638983820960864], [30541, 0.18461502919326975], [30555, 0.18811217207531591], [30569, 0.18474042707822136], [30583, 0.18657043730368242], [30597, 0.18184492922368306], [30625, 0.18317961597370516], [30639, 0.18493488144016718], [30653, 0.18404993695307512], [30667, 0.1922230881804466], [30681, 0.19026893206031334], [30695, 0.19133634939370428], [30709, 0.1878794630648737], [30723, 0.18480938821570422], [30737, 0.18725173353267952], [30751, 0.18409170629481622], [30765, 0.18467539057753865], [30779, 0.18187496233875677], [30793, 0.18741632794114546], [30807, 0.18583139813513344], [30821, 0.18972976155119148], [30835, 0.18222567896725517], [30849, 0.18363746629967795], [30863, 0.18613364413576566], [30877, 0.18284550861373422], [30891, 0.18821908708505167], [30905, 0.18264287913716604], [30919, 0.1845007948926524], [30933, 0.18904773380923873], [30947, 0.18104977167502218], [30961, 0.19004502702694348], [30975, 0.18882555432413428], [30989, 0.18480431870766947], [31003, 0.18463663579747303], [31017, 0.1968065535658347], [31031, null], [31045, 0.18795274462713946], [32109, 0.17359463404214362], [32123, 0.1667791688920527], [32137, 0.1652187938587251], [32151, 0.1662213918321559], [32165, 0.16403618478639748], [32179, 0.16571299708948017], [32193, 0.16612879728473343], [32207, 0.1681188348000689], [32221, 0.16827009171261567], [32235, 0.17145229716413599], [32249, 0.16636983650837758], [32263, 0.16966441798609475], [32277, 0.16150081064003563], [32305, 0.16720727987955905], [32319, 0.16539037543949353], [32333, 0.16746483972462928], [32347, 0.1712152231053422], [32361, 0.1666039579475623], [32375, 0.16688567764848897], [32389, 0.16394255155459642], [32403, 0.1628551325485661], [32417, 0.16820736410116435], [32431, 0.16533370128386016], [32445, 0.1652471142159005], [32585, 0.15932600666936744], [32599, 0.15902592204792124], [32613, 0.15877520458863378], [32627, 0.15140573125483367], [32641, 0.15502052427635116], [32655, 0.16139636747232564], [32851, 0.1659947987761422], [32865, 0.16414413159190722], [32879, 0.16375739944109732], [32893, 0.16664911382009087], [32907, 0.16620507130356232], [32921, 0.16537595408743905], [32991, 0.16531541533305097], [33005, 0.16421721083901877], [33019, 0.1694194957776195], [33033, 0.16554365822587686], [33047, 0.16955858338455299], [33061, 0.16874298279380262], [33075, 0.16737148011587605], [33089, 0.1683236949600461], [33103, 0.17363560219353605], [33117, 0.1701718062622824], [33131, 0.16666184831596464], [33145, 0.1623403384391852], [33159, 0.1643386843697843], [33187, 0.16688634384405934], [33201, 0.1667940163523257], [33215, 0.16551961338197305], [33229, 0.16904120673795944], [33243, 0.16993749913505007], [33271, 0.17410067448224517], [33299, 0.2064610962017135], [33313, 0.16902010927928934], [33327, 0.17155554660201855], [33341, 0.1670553297593127], [33355, 0.17468156112972785], [33369, 0.16625205090351225], [33383, 0.17539736250051763], [33397, 0.1808883237279958], [33411, 0.17496288099165166], [33425, 0.18201703156556065], [33439, 0.17951988525473467], [33453, 0.17846732099395374], [33467, 0.175893884230647], [33523, 0.17789664682694906], [33537, 0.17854872107758998], [33551, 0.1801648873425178], [33649, 0.1798842129142689], [33705, 0.18013246192913301], [33719, 0.17945848579644602], [33733, 0.15990056714581072], [33747, 0.15782541268022038], [33761, 0.1600329669104794], [33775, 0.15582101993698186], [33803, 0.1567324124363651], [33817, 0.15797770015807153], [33831, 0.15908847276711072], [33845, 0.15948332576584012], [34041, 0.15570669642401025], [34055, 0.16009349781525894], [34069, 0.1595776594496214], [34083, 0.15958515166968132], [34125, 0.15841791003437797], [34139, 0.16195160541935602], [34153, 0.15869653359735567], [34167, 0.15970824703320372]] \ No newline at end of file +[[28511, 0.09379044078892974], [29225, 0.19087374746870495], [29239, 0.18308414931852107], [29253, 0.09608386123411387], [29267, 0.09754716067298128], [29281, 0.09991364980502303], [29295, 0.09724117731909654], [29309, 0.09762595535104279], [29323, 0.09927695393711455], [29337, 0.09647535384223756], [29351, 0.0971082268943414], [29365, 0.09407399997198918], [29379, 0.09681261977596323], [29393, 0.10099642659499107], [29407, 0.09829767115741095], [29421, 0.09812622785119413], [29435, 0.09728976442712534], [29449, 0.17988762418486884], [29463, 0.1883305536760536], [29477, 0.18861556814805228], [29547, 0.19440761342141616], [29561, 0.177355496778817], [29575, 0.18071339345222495], [29603, 0.17774785851018565], [29617, 0.1749661386668798], [29631, 0.17315087188809986], [29645, 0.17462219024393622], [29659, 0.1727642620017645], [29673, 0.1733100851846101], [29743, 0.1748391184492784], [29757, 0.17495470874932897], [29771, 0.1751171582035474], [29785, 0.18175826630752318], [29799, 0.18249203932271527], [29813, 0.19285932614006585], [29827, 0.19664651061146488], [29841, 0.19235760231882149], [29855, 0.17895501880641015], [29869, 0.18993067800720548], [30009, 0.18692832638721074], [30023, 0.18054291162828207], [30037, 0.18448226509471208], [30051, 0.18266356950660148], [30065, 0.19048874840690502], [30079, 0.186554677202648], [30093, 0.18166450040157958], [30107, 0.2003111362382836], [30121, 0.1847276420245596], [30135, 0.2001825250447581], [30149, 0.19307761434901172], [30163, 0.193432527821332], [30177, 0.18650983609706934], [30191, 0.1869738584531503], [30205, 0.19380904840314195], [30219, 0.18510250680802148], [30233, 0.18668816748651784], [30247, 0.1876043583715968], [30261, 0.18755317235701097], [30513, 0.18625989911963606], [30527, 0.18638983820960864], [30541, 0.18461502919326975], [30555, 0.18811217207531591], [30569, 0.18474042707822136], [30583, 0.18657043730368242], [30597, 0.18184492922368306], [30625, 0.18317961597370516], [30639, 0.18493488144016718], [30653, 0.18404993695307512], [30667, 0.1922230881804466], [30681, 0.19026893206031334], [30695, 0.19133634939370428], [30709, 0.1878794630648737], [30723, 0.18480938821570422], [30737, 0.18725173353267952], [30751, 0.18409170629481622], [30765, 0.18467539057753865], [30779, 0.18187496233875677], [30793, 0.18741632794114546], [30807, 0.18583139813513344], [30821, 0.18972976155119148], [30835, 0.18222567896725517], [30849, 0.18363746629967795], [30863, 0.18613364413576566], [30877, 0.18284550861373422], [30891, 0.18821908708505167], [30905, 0.18264287913716604], [30919, 0.1845007948926524], [30933, 0.18904773380923873], [30947, 0.18104977167502218], [30961, 0.19004502702694348], [30975, 0.18882555432413428], [30989, 0.18480431870766947], [31003, 0.18463663579747303], [31017, 0.1968065535658347], [31031, null], [31045, 0.18795274462713946], [32109, 0.17359463404214362], [32123, 0.1667791688920527], [32137, 0.1652187938587251], [32151, 0.1662213918321559], [32165, 0.16403618478639748], [32179, 0.16571299708948017], [32193, 0.16612879728473343], [32207, 0.1681188348000689], [32221, 0.16827009171261567], [32235, 0.17145229716413599], [32249, 0.16636983650837758], [32263, 0.16966441798609475], [32277, 0.16150081064003563], [32305, 0.16720727987955905], [32319, 0.16539037543949353], [32333, 0.16746483972462928], [32347, 0.1712152231053422], [32361, 0.1666039579475623], [32375, 0.16688567764848897], [32389, 0.16394255155459642], [32403, 0.1628551325485661], [32417, 0.16820736410116435], [32431, 0.16533370128386016], [32445, 0.1652471142159005], [32585, 0.15932600666936744], [32599, 0.15902592204792124], [32613, 0.15877520458863378], [32627, 0.15140573125483367], [32641, 0.15502052427635116], [32655, 0.16139636747232564], [32851, 0.1659947987761422], [32865, 0.16414413159190722], [32879, 0.16375739944109732], [32893, 0.16664911382009087], [32907, 0.16620507130356232], [32921, 0.16537595408743905], [32991, 0.16531541533305097], [33005, 0.16421721083901877], [33019, 0.1694194957776195], [33033, 0.16554365822587686], [33047, 0.16955858338455299], [33061, 0.16874298279380262], [33075, 0.16737148011587605], [33089, 0.1683236949600461], [33103, 0.17363560219353605], [33117, 0.1701718062622824], [33131, 0.16666184831596464], [33145, 0.1623403384391852], [33159, 0.1643386843697843], [33187, 0.16688634384405934], [33201, 0.1667940163523257], [33215, 0.16551961338197305], [33229, 0.16904120673795944], [33243, 0.16993749913505007], [33271, 0.17410067448224517], [33299, 0.2064610962017135], [33313, 0.16902010927928934], [33327, 0.17155554660201855], [33341, 0.1670553297593127], [33355, 0.17468156112972785], [33369, 0.16625205090351225], [33383, 0.17539736250051763], [33397, 0.1808883237279958], [33411, 0.17496288099165166], [33425, 0.18201703156556065], [33439, 0.17951988525473467], [33453, 0.17846732099395374], [33467, 0.175893884230647], [33523, 0.17789664682694906], [33537, 0.17854872107758998], [33551, 0.1801648873425178], [33649, 0.1798842129142689], [33705, 0.18013246192913301], [33719, 0.17945848579644602], [33733, 0.15990056714581072], [33747, 0.15782541268022038], [33761, 0.1600329669104794], [33775, 0.15582101993698186], [33803, 0.1567324124363651], [33817, 0.15797770015807153], [33831, 0.15908847276711072], [33845, 0.15948332576584012], [34041, 0.15570669642401025], [34055, 0.16009349781525894], [34069, 0.1595776594496214], [34083, 0.15958515166968132], [34125, 0.15841791003437797], [34139, 0.16195160541935602], [34153, 0.15869653359735567], [34167, 0.15956880457137182]] \ No newline at end of file diff --git a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json index b426ea3bd8..1f9f162b76 100644 --- a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json +++ b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[29227, 101187942.6972118], [29239, 101038408.22010806], [29251, 101025583.33756296], [29263, 101168232.60162169], [29287, 101216821.46098089], [29299, 101181607.9047823], [29323, 101141012.681746], [29335, 101311998.36166543], [29347, 100925241.46462294], [29359, 100839014.63209486], [29371, 100823155.23373467], [29383, 100662517.01887794], [29395, 100829971.46199355], [29407, 100619504.77190138], [29419, 100808733.93263857], [29431, 101163358.8062362], [29443, 101115704.62540855], [29455, 101101289.06238371], [29467, 101286025.29893012], [29479, 101192331.90933503], [29551, 101269748.35363658], [29563, 101424734.32690027], [29575, 100860914.68759367], [29599, 102102823.9514499], [29611, 102191128.21579736], [29623, 102185235.8209931], [29647, 102251563.61089817], [29659, 102087146.69997373], [29671, 101996049.66426443], [29743, 102041516.74312344], [29755, 102151303.38145024], [29767, 102093653.41864668], [29779, 102012036.24351776], [29791, 102170937.79344495], [29803, 102213824.80542529], [29815, 102400605.26040597], [29827, 102522288.42657933], [29839, 102551811.05690809], [29851, 102242951.4266132], [29863, 102249242.89624119], [29875, 102486622.92518422], [30007, 102463583.56689331], [30019, 102368836.71411243], [30031, 102393953.73325211], [30043, 102393829.1900679], [30055, 102590510.58684996], [30067, 102272981.10263829], [30079, 102418260.7658966], [30091, 102528925.75824705], [30103, 102339373.54089285], [30115, 102548592.68093705], [30127, 102498501.30589491], [30139, 102480928.98201689], [30151, 102626673.25176784], [30163, 102701941.87654006], [30175, 102752334.13153604], [30187, 102949809.26436174], [30199, 102878205.18848789], [30211, 102891158.52646156], [30223, 102821129.89319333], [30235, 102920178.90656905], [30247, 102887039.4564938], [30259, 102784298.77482474], [30271, 102871857.75311394], [30511, 102911917.11014786], [30523, 102723805.54815955], [30535, 102824337.95066373], [30547, 102785940.91614923], [30559, 102548515.4699759], [30571, 102678346.51808341], [30583, 102632302.35933203], [30595, 102827379.5344722], [30619, 102771498.7527455], [30631, 102768113.15106486], [30643, 102754300.04246807], [30655, 102892342.01861942], [30667, 102699012.06998557], [30679, 102932699.69026771], [30691, 102746445.3316764], [30703, 102639470.1753658], [30715, 102848186.2842277], [30727, 102920024.50435516], [30739, 102761461.44303147], [30751, 102848804.63417822], [30763, 103598926.94425702], [30787, 102903726.68003856], [30799, 103000796.09617384], [30811, 102845036.12406388], [30823, 103021433.9599467], [30847, 103036030.47212997], [30859, 102895426.45323093], [30871, 103024361.40643755], [30883, 103276334.76491854], [30895, 102934080.89928964], [30907, 102856238.21076064], [30919, 102932973.69420193], [30931, 103318226.44847319], [30943, 102982101.54700114], [30955, 103222571.31656012], [30967, 103163633.11447513], [30979, 102862755.2230682], [30991, 103124071.12131765], [31003, 102977928.29445374], [31015, 103079727.99343234], [31027, 103071417.88535279], [31039, 102774680.15729165], [31051, 103137770.42283106], [32095, 115610802.09174864], [32107, 115221348.50944337], [32119, 115449705.5325445], [32131, 115183804.67125875], [32143, 115294996.9909286], [32155, 115171680.41256875], [32167, 115411060.2866333], [32179, 114873607.21318379], [32191, 115126582.76314533], [32203, 116108182.45003141], [32215, 118215931.96665223], [32227, 118029339.01351428], [32251, 117991308.64534637], [32263, 118241429.05837047], [32275, 118151364.77970451], [32299, 118065841.33042708], [32311, 125312918.07275172], [32323, 125391262.64355053], [32335, 125423988.86773875], [32347, 125409394.75555257], [32359, 125535616.07661393], [32371, 125580755.55290213], [32383, 125461411.5256309], [32395, 125414333.74410987], [32407, 125354428.61141908], [32419, 125312304.03803991], [32431, 125515812.04978448], [32443, 125502164.81879468], [32575, 121176998.4863913], [32587, 121223463.16729423], [32599, 121273305.3465069], [32611, 121314037.35950357], [32623, 121420689.52539778], [32635, 121123456.69520448], [32647, 121272685.40782133], [32659, 121276956.89101166], [32839, 122432251.94228129], [32851, 122251543.77154943], [32863, 122310412.37609182], [32875, 122187565.27269715], [32887, 122387939.21165663], [32899, 122467845.46737266], [32911, 122171156.28099433], [32923, 122302890.48114912], [32995, 122325727.80545163], [33007, 122432095.31386149], [33019, 121858238.59832829], [33031, 122230395.67788458], [33043, 122412834.4242506], [33055, 122411006.33819075], [33067, 122559865.63156556], [33079, 122292883.03970595], [33091, 152912427.94760516], [33103, 152606552.41916567], [33115, 152878166.57546258], [33127, 152243744.8524301], [33139, 152725552.57945353], [33151, 152985378.47587708], [33187, 122932986.10574175], [33199, 122760146.55433261], [33211, 122702612.0338526], [33223, 120748740.21755785], [33235, 118695645.09991018], [33271, 114216476.36691582], [33307, 114624601.2682348], [33319, 114157673.00719267], [33331, 114703055.46895252], [33343, 114453774.87067012], [33355, 114705155.9232631], [33367, 115112377.69297622], [33379, 115151496.69441853], [33391, 115823232.78409836], [33403, 116011823.9771904], [33415, 116033848.2945477], [33427, 115908759.8376276], [33439, 117244758.1586699], [33451, 111872288.66921109], [33463, 112274995.83226264], [33523, 112096553.10256605], [33535, 112153363.98034573], [33547, 111767832.4301434], [33655, 104142342.5333154], [33715, 103944032.3167081], [33727, 103861549.51340052], [33739, 103355395.86355361], [33763, 104436822.94392835], [33775, 104232013.85954317], [33811, 104093749.63963793], [33823, 103732904.20771164], [33835, 103114785.90792668], [34039, 103475672.07545498], [34051, 103777351.36801258], [34063, 104215373.81795186], [34075, 103461614.29360011], [34087, 103065670.28543818], [34123, 103915411.44980569], [34135, 104081677.73633413], [34147, 103988920.73981059], [34159, 103993243.2557112], [34171, 103108200.12358503]] \ No newline at end of file +[[29227, 101187942.6972118], [29239, 101038408.22010806], [29251, 101025583.33756296], [29263, 101168232.60162169], [29287, 101216821.46098089], [29299, 101181607.9047823], [29323, 101141012.681746], [29335, 101311998.36166543], [29347, 100925241.46462294], [29359, 100839014.63209486], [29371, 100823155.23373467], [29383, 100662517.01887794], [29395, 100829971.46199355], [29407, 100619504.77190138], [29419, 100808733.93263857], [29431, 101163358.8062362], [29443, 101115704.62540855], [29455, 101101289.06238371], [29467, 101286025.29893012], [29479, 101192331.90933503], [29551, 101269748.35363658], [29563, 101424734.32690027], [29575, 100860914.68759367], [29599, 102102823.9514499], [29611, 102191128.21579736], [29623, 102185235.8209931], [29647, 102251563.61089817], [29659, 102087146.69997373], [29671, 101996049.66426443], [29743, 102041516.74312344], [29755, 102151303.38145024], [29767, 102093653.41864668], [29779, 102012036.24351776], [29791, 102170937.79344495], [29803, 102213824.80542529], [29815, 102400605.26040597], [29827, 102522288.42657933], [29839, 102551811.05690809], [29851, 102242951.4266132], [29863, 102249242.89624119], [29875, 102486622.92518422], [30007, 102463583.56689331], [30019, 102368836.71411243], [30031, 102393953.73325211], [30043, 102393829.1900679], [30055, 102590510.58684996], [30067, 102272981.10263829], [30079, 102418260.7658966], [30091, 102528925.75824705], [30103, 102339373.54089285], [30115, 102548592.68093705], [30127, 102498501.30589491], [30139, 102480928.98201689], [30151, 102626673.25176784], [30163, 102701941.87654006], [30175, 102752334.13153604], [30187, 102949809.26436174], [30199, 102878205.18848789], [30211, 102891158.52646156], [30223, 102821129.89319333], [30235, 102920178.90656905], [30247, 102887039.4564938], [30259, 102784298.77482474], [30271, 102871857.75311394], [30511, 102911917.11014786], [30523, 102723805.54815955], [30535, 102824337.95066373], [30547, 102785940.91614923], [30559, 102548515.4699759], [30571, 102678346.51808341], [30583, 102632302.35933203], [30595, 102827379.5344722], [30619, 102771498.7527455], [30631, 102768113.15106486], [30643, 102754300.04246807], [30655, 102892342.01861942], [30667, 102699012.06998557], [30679, 102932699.69026771], [30691, 102746445.3316764], [30703, 102639470.1753658], [30715, 102848186.2842277], [30727, 102920024.50435516], [30739, 102761461.44303147], [30751, 102848804.63417822], [30763, 103598926.94425702], [30787, 102903726.68003856], [30799, 103000796.09617384], [30811, 102845036.12406388], [30823, 103021433.9599467], [30847, 103036030.47212997], [30859, 102895426.45323093], [30871, 103024361.40643755], [30883, 103276334.76491854], [30895, 102934080.89928964], [30907, 102856238.21076064], [30919, 102932973.69420193], [30931, 103318226.44847319], [30943, 102982101.54700114], [30955, 103222571.31656012], [30967, 103163633.11447513], [30979, 102862755.2230682], [30991, 103124071.12131765], [31003, 102977928.29445374], [31015, 103079727.99343234], [31027, 103071417.88535279], [31039, 102774680.15729165], [31051, 103137770.42283106], [32095, 115610802.09174864], [32107, 115221348.50944337], [32119, 115449705.5325445], [32131, 115183804.67125875], [32143, 115294996.9909286], [32155, 115171680.41256875], [32167, 115411060.2866333], [32179, 114873607.21318379], [32191, 115126582.76314533], [32203, 116108182.45003141], [32215, 118215931.96665223], [32227, 118029339.01351428], [32251, 117991308.64534637], [32263, 118241429.05837047], [32275, 118151364.77970451], [32299, 118065841.33042708], [32311, 125312918.07275172], [32323, 125391262.64355053], [32335, 125423988.86773875], [32347, 125409394.75555257], [32359, 125535616.07661393], [32371, 125580755.55290213], [32383, 125461411.5256309], [32395, 125414333.74410987], [32407, 125354428.61141908], [32419, 125312304.03803991], [32431, 125515812.04978448], [32443, 125502164.81879468], [32575, 121176998.4863913], [32587, 121223463.16729423], [32599, 121273305.3465069], [32611, 121314037.35950357], [32623, 121420689.52539778], [32635, 121123456.69520448], [32647, 121272685.40782133], [32659, 121276956.89101166], [32839, 122432251.94228129], [32851, 122251543.77154943], [32863, 122310412.37609182], [32875, 122187565.27269715], [32887, 122387939.21165663], [32899, 122467845.46737266], [32911, 122171156.28099433], [32923, 122302890.48114912], [32995, 122325727.80545163], [33007, 122432095.31386149], [33019, 121858238.59832829], [33031, 122230395.67788458], [33043, 122412834.4242506], [33055, 122411006.33819075], [33067, 122559865.63156556], [33079, 122292883.03970595], [33091, 152912427.94760516], [33103, 152606552.41916567], [33115, 152878166.57546258], [33127, 152243744.8524301], [33139, 152725552.57945353], [33151, 152985378.47587708], [33187, 122932986.10574175], [33199, 122760146.55433261], [33211, 122702612.0338526], [33223, 120748740.21755785], [33235, 118695645.09991018], [33271, 114216476.36691582], [33307, 114624601.2682348], [33319, 114157673.00719267], [33331, 114703055.46895252], [33343, 114453774.87067012], [33355, 114705155.9232631], [33367, 115112377.69297622], [33379, 115151496.69441853], [33391, 115823232.78409836], [33403, 116011823.9771904], [33415, 116033848.2945477], [33427, 115908759.8376276], [33439, 117244758.1586699], [33451, 111872288.66921109], [33463, 112274995.83226264], [33523, 112096553.10256605], [33535, 112153363.98034573], [33547, 111767832.4301434], [33655, 104142342.5333154], [33715, 103944032.3167081], [33727, 103861549.51340052], [33739, 103355395.86355361], [33763, 104436822.94392835], [33775, 104232013.85954317], [33811, 104093749.63963793], [33823, 103732904.20771164], [33835, 103114785.90792668], [34039, 103475672.07545498], [34051, 103777351.36801258], [34063, 104215373.81795186], [34075, 103461614.29360011], [34087, 103065670.28543818], [34123, 103915411.44980569], [34135, 104081677.73633413], [34147, 103988920.73981059], [34159, 103993243.2557112], [34171, 103160181.59784602]] \ No newline at end of file diff --git a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json index ebf837f849..931be74bb2 100644 --- a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json +++ b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[29227, 85571205.98308323], [29239, 85225126.9578872], [29251, 85352840.67999645], [29263, 85529645.60336807], [29287, 85542804.23254053], [29299, 85589617.50631616], [29323, 85522745.43909192], [29335, 85468145.31096232], [29347, 85326908.30943736], [29359, 85116513.65361963], [29371, 84986277.64601284], [29383, 84951087.21996756], [29395, 85095965.58671622], [29407, 85039192.80284068], [29419, 85079349.75402766], [29431, 85478690.06224], [29443, 85439271.4534931], [29455, 85481292.82419659], [29467, 85637021.70420562], [29479, 85421159.35250704], [29551, 85641449.3265964], [29563, 85784123.0254233], [29575, 85302478.60551429], [29599, 86446449.46592958], [29611, 86520179.4373507], [29623, 86427020.46138766], [29647, 86426559.07036844], [29659, 86377099.33795448], [29671, 86380356.03816928], [29743, 86372768.99138808], [29755, 86450435.37221283], [29767, 86486043.79868239], [29779, 86388899.4689469], [29791, 86503053.88211192], [29803, 86640851.53265858], [29815, 86786018.52169676], [29827, 86854644.16265142], [29839, 86901247.9984917], [29851, 86679092.44305575], [29863, 86760517.89863461], [29875, 86871053.85088591], [30007, 86759249.97069705], [30019, 86755102.41148946], [30031, 86740050.23509163], [30043, 86823990.72708179], [30055, 86849688.15164247], [30067, 86721659.6153047], [30079, 86794883.64486405], [30091, 86754986.52325153], [30103, 86454308.96820168], [30115, 86798268.71565753], [30127, 86824431.26417823], [30139, 86835710.29709193], [30151, 86940101.85290596], [30163, 87244844.05833918], [30175, 87284540.89392108], [30187, 87380831.42675723], [30199, 87200929.6912613], [30211, 87263134.43890156], [30223, 87247599.33227402], [30235, 87291270.50777514], [30247, 87398969.35458666], [30259, 87262369.57148053], [30271, 87208420.2494438], [30511, 87344703.85056242], [30523, 87021703.37729338], [30535, 87212173.11625686], [30547, 87134982.72214235], [30559, 87026473.73208573], [30571, 87080633.75091346], [30583, 87166474.49505208], [30595, 87138792.426974], [30619, 87122035.15779884], [30631, 87158373.48737548], [30643, 87125205.35731675], [30655, 87174586.78982186], [30667, 87063158.96662256], [30679, 87310863.69028829], [30691, 86817778.65996617], [30703, 86994126.20398137], [30715, 87218674.70017546], [30727, 87339694.30061659], [30739, 87044168.2838248], [30751, 87187960.52706018], [30763, 87865338.34646285], [30787, 87210032.71558194], [30799, 87366359.61373867], [30811, 87179686.60825965], [30823, 87337189.84427668], [30847, 87404363.47176632], [30859, 87228418.78888051], [30871, 87467949.66343053], [30883, 87596717.47507764], [30895, 87455528.7350464], [30907, 87322650.41774543], [30919, 87241102.59701297], [30931, 87498717.19875725], [30943, 87202264.64581096], [30955, 87561220.11682627], [30967, 87496552.03641929], [30979, 87303095.99279477], [30991, 87522362.36092243], [31003, 87493418.33572018], [31015, 87541221.82639581], [31027, 87267048.82732093], [31039, 87156513.45169792], [31051, 87509580.64617185], [32095, 99660433.72139217], [32107, 99097434.82556853], [32119, 99452682.47825177], [32131, 99299556.92951736], [32143, 99322661.7557323], [32155, 99175493.26816581], [32167, 99481454.16686523], [32179, 98862709.25233476], [32191, 99306908.17836957], [32203, 100192867.35056286], [32215, 102131909.5668934], [32227, 101876603.6765079], [32251, 101934254.46756709], [32263, 102127668.53106493], [32275, 101899789.56976761], [32299, 101840044.3890619], [32311, 109093680.7263035], [32323, 109177354.07374845], [32335, 109042052.17037383], [32347, 109144905.18404186], [32359, 109243352.76377587], [32371, 109302678.43031785], [32383, 109105694.27233188], [32395, 109168971.6252725], [32407, 109089788.80399494], [32419, 109095474.49210764], [32431, 109268807.67050874], [32443, 109339578.7164432], [32575, 104909217.29541212], [32587, 104892625.84853569], [32599, 104905306.18413858], [32611, 104894833.95877302], [32623, 105042384.86182964], [32635, 104679595.39109088], [32647, 104878559.18529668], [32659, 104915367.4973112], [32839, 106082099.90358374], [32851, 105812683.79568344], [32863, 105921041.43475841], [32875, 105831267.54167952], [32887, 105925913.72509734], [32899, 106116671.28842853], [32911, 105915944.5791856], [32923, 106058382.6565175], [32995, 105981549.25769386], [33007, 106211164.96468464], [33019, 105671882.3835651], [33031, 105979405.33607657], [33043, 106093141.49887425], [33055, 106164292.42730926], [33067, 106185020.66963366], [33079, 106016682.70289811], [33091, 136011572.81452066], [33103, 135774559.2432429], [33115, 136036349.45297945], [33127, 135532028.8579167], [33139, 135801519.48246235], [33151, 136017778.38372514], [33187, 106327929.09179007], [33199, 106234788.23631525], [33211, 106206220.62328699], [33223, 104109859.3558139], [33235, 102270315.0898103], [33271, 97751339.92662975], [33307, 98235898.365555], [33319, 97880355.13298236], [33331, 98246019.03970958], [33343, 98034473.49966255], [33355, 98317818.203449], [33367, 98803915.74043746], [33379, 98895743.73704283], [33391, 99355339.98230082], [33403, 99429830.24194846], [33415, 99473982.26562119], [33427, 99364815.28833465], [33439, 100794606.22721669], [33451, 95602247.85074659], [33463, 95775205.55848263], [33523, 95807277.843198], [33535, 95772343.91727647], [33547, 95361890.10823692], [33655, 94554481.92922935], [33715, 94231358.63215296], [33727, 94206211.89340599], [33739, 93871291.56219332], [33763, 93875604.20965609], [33775, 93664134.41608395], [33811, 93549361.46819302], [33823, 93572959.28506482], [33835, 93452947.26419261], [34039, 93372102.03931221], [34051, 93637933.0369539], [34063, 93767181.6958526], [34075, 93321045.58899166], [34087, 93377070.35149619], [34123, 93510317.41340195], [34135, 93746094.34192339], [34147, 93523530.91231298], [34159, 93496223.6810219], [34171, 93454998.07436661]] \ No newline at end of file +[[29227, 85571205.98308323], [29239, 85225126.9578872], [29251, 85352840.67999645], [29263, 85529645.60336807], [29287, 85542804.23254053], [29299, 85589617.50631616], [29323, 85522745.43909192], [29335, 85468145.31096232], [29347, 85326908.30943736], [29359, 85116513.65361963], [29371, 84986277.64601284], [29383, 84951087.21996756], [29395, 85095965.58671622], [29407, 85039192.80284068], [29419, 85079349.75402766], [29431, 85478690.06224], [29443, 85439271.4534931], [29455, 85481292.82419659], [29467, 85637021.70420562], [29479, 85421159.35250704], [29551, 85641449.3265964], [29563, 85784123.0254233], [29575, 85302478.60551429], [29599, 86446449.46592958], [29611, 86520179.4373507], [29623, 86427020.46138766], [29647, 86426559.07036844], [29659, 86377099.33795448], [29671, 86380356.03816928], [29743, 86372768.99138808], [29755, 86450435.37221283], [29767, 86486043.79868239], [29779, 86388899.4689469], [29791, 86503053.88211192], [29803, 86640851.53265858], [29815, 86786018.52169676], [29827, 86854644.16265142], [29839, 86901247.9984917], [29851, 86679092.44305575], [29863, 86760517.89863461], [29875, 86871053.85088591], [30007, 86759249.97069705], [30019, 86755102.41148946], [30031, 86740050.23509163], [30043, 86823990.72708179], [30055, 86849688.15164247], [30067, 86721659.6153047], [30079, 86794883.64486405], [30091, 86754986.52325153], [30103, 86454308.96820168], [30115, 86798268.71565753], [30127, 86824431.26417823], [30139, 86835710.29709193], [30151, 86940101.85290596], [30163, 87244844.05833918], [30175, 87284540.89392108], [30187, 87380831.42675723], [30199, 87200929.6912613], [30211, 87263134.43890156], [30223, 87247599.33227402], [30235, 87291270.50777514], [30247, 87398969.35458666], [30259, 87262369.57148053], [30271, 87208420.2494438], [30511, 87344703.85056242], [30523, 87021703.37729338], [30535, 87212173.11625686], [30547, 87134982.72214235], [30559, 87026473.73208573], [30571, 87080633.75091346], [30583, 87166474.49505208], [30595, 87138792.426974], [30619, 87122035.15779884], [30631, 87158373.48737548], [30643, 87125205.35731675], [30655, 87174586.78982186], [30667, 87063158.96662256], [30679, 87310863.69028829], [30691, 86817778.65996617], [30703, 86994126.20398137], [30715, 87218674.70017546], [30727, 87339694.30061659], [30739, 87044168.2838248], [30751, 87187960.52706018], [30763, 87865338.34646285], [30787, 87210032.71558194], [30799, 87366359.61373867], [30811, 87179686.60825965], [30823, 87337189.84427668], [30847, 87404363.47176632], [30859, 87228418.78888051], [30871, 87467949.66343053], [30883, 87596717.47507764], [30895, 87455528.7350464], [30907, 87322650.41774543], [30919, 87241102.59701297], [30931, 87498717.19875725], [30943, 87202264.64581096], [30955, 87561220.11682627], [30967, 87496552.03641929], [30979, 87303095.99279477], [30991, 87522362.36092243], [31003, 87493418.33572018], [31015, 87541221.82639581], [31027, 87267048.82732093], [31039, 87156513.45169792], [31051, 87509580.64617185], [32095, 99660433.72139217], [32107, 99097434.82556853], [32119, 99452682.47825177], [32131, 99299556.92951736], [32143, 99322661.7557323], [32155, 99175493.26816581], [32167, 99481454.16686523], [32179, 98862709.25233476], [32191, 99306908.17836957], [32203, 100192867.35056286], [32215, 102131909.5668934], [32227, 101876603.6765079], [32251, 101934254.46756709], [32263, 102127668.53106493], [32275, 101899789.56976761], [32299, 101840044.3890619], [32311, 109093680.7263035], [32323, 109177354.07374845], [32335, 109042052.17037383], [32347, 109144905.18404186], [32359, 109243352.76377587], [32371, 109302678.43031785], [32383, 109105694.27233188], [32395, 109168971.6252725], [32407, 109089788.80399494], [32419, 109095474.49210764], [32431, 109268807.67050874], [32443, 109339578.7164432], [32575, 104909217.29541212], [32587, 104892625.84853569], [32599, 104905306.18413858], [32611, 104894833.95877302], [32623, 105042384.86182964], [32635, 104679595.39109088], [32647, 104878559.18529668], [32659, 104915367.4973112], [32839, 106082099.90358374], [32851, 105812683.79568344], [32863, 105921041.43475841], [32875, 105831267.54167952], [32887, 105925913.72509734], [32899, 106116671.28842853], [32911, 105915944.5791856], [32923, 106058382.6565175], [32995, 105981549.25769386], [33007, 106211164.96468464], [33019, 105671882.3835651], [33031, 105979405.33607657], [33043, 106093141.49887425], [33055, 106164292.42730926], [33067, 106185020.66963366], [33079, 106016682.70289811], [33091, 136011572.81452066], [33103, 135774559.2432429], [33115, 136036349.45297945], [33127, 135532028.8579167], [33139, 135801519.48246235], [33151, 136017778.38372514], [33187, 106327929.09179007], [33199, 106234788.23631525], [33211, 106206220.62328699], [33223, 104109859.3558139], [33235, 102270315.0898103], [33271, 97751339.92662975], [33307, 98235898.365555], [33319, 97880355.13298236], [33331, 98246019.03970958], [33343, 98034473.49966255], [33355, 98317818.203449], [33367, 98803915.74043746], [33379, 98895743.73704283], [33391, 99355339.98230082], [33403, 99429830.24194846], [33415, 99473982.26562119], [33427, 99364815.28833465], [33439, 100794606.22721669], [33451, 95602247.85074659], [33463, 95775205.55848263], [33523, 95807277.843198], [33535, 95772343.91727647], [33547, 95361890.10823692], [33655, 94554481.92922935], [33715, 94231358.63215296], [33727, 94206211.89340599], [33739, 93871291.56219332], [33763, 93875604.20965609], [33775, 93664134.41608395], [33811, 93549361.46819302], [33823, 93572959.28506482], [33835, 93452947.26419261], [34039, 93372102.03931221], [34051, 93637933.0369539], [34063, 93767181.6958526], [34075, 93321045.58899166], [34087, 93377070.35149619], [34123, 93510317.41340195], [34135, 93746094.34192339], [34147, 93523530.91231298], [34159, 93496223.6810219], [34171, 93465322.10406816]] \ No newline at end of file diff --git a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.time_fit.json b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.time_fit.json index 548ef38b61..910748a8ed 100644 --- a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.time_fit.json +++ b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.time_fit.json @@ -1 +1 @@ -[[29227, 6.310830025929775], [29239, 6.459605420277555], [29251, 3.951776408283148], [29263, 3.9881029965177532], [29287, 3.9979523620018704], [29299, 4.087399084092216], [29323, 3.9719939042249344], [29335, 4.094989269589381], [29347, 4.075137677278278], [29359, 3.7606633184227682], [29371, 3.800067990618089], [29383, 3.9326962704972], [29395, 4.061596969932272], [29407, 3.8938342346078105], [29419, 3.8441017980300103], [29431, 3.9112529491627512], [29443, 9.06765487141435], [29455, 8.086962802052039], [29467, 8.179006215294853], [29479, 6.403175935582288], [29551, 8.940917985821384], [29563, 6.63365047390054], [29575, 6.142877200237559], [29599, 6.175813255879229], [29611, 6.300606485215324], [29623, 6.069828591981448], [29647, 6.379030821960219], [29659, 6.470249871393978], [29671, 6.406636395734696], [29743, 6.504796206672925], [29755, 6.459044366181097], [29767, 6.535462216227275], [29779, 7.5785888189967245], [29791, 6.26674845898], [29803, 5.960166797207595], [29815, 6.40374959362412], [29827, 6.214694998528], [29839, 6.170255889462543], [29851, 6.279465293605755], [29863, 6.814817571438463], [29875, 6.378669607467775], [30007, 6.6772233548485875], [30019, 6.363962334188091], [30031, 6.678932969927671], [30043, 6.437604749736519], [30055, 6.403120364964289], [30067, 6.2763743573487085], [30079, 6.39838641899592], [30091, 6.39319372636], [30103, 6.463154162881294], [30115, 6.212923051527036], [30127, 6.184014379069404], [30139, 6.4426339686903775], [30151, 6.542293148098557], [30163, 6.367300806455284], [30175, 6.324160425396711], [30187, 6.453529520248782], [30199, 6.578131698046559], [30211, 6.712916206870864], [30223, 6.716728168394116], [30235, 6.299097691275333], [30247, 6.872906129408509], [30259, 6.672350499835073], [30271, 6.437160390082652], [30511, 6.495041663221227], [30523, 6.961980743916843], [30535, 6.543195700844054], [30547, 6.428287446587889], [30559, 6.624213410418168], [30571, 6.50702072354812], [30583, 6.376887122590773], [30595, 6.527699602499407], [30619, 6.137261245742873], [30631, 6.529358251093369], [30643, 6.311598703731872], [30655, 6.608133257436263], [30667, 6.640232891027022], [30679, 6.338184001600987], [30691, 6.832529225601797], [30703, 6.310369038496842], [30715, 6.529657840439009], [30727, 6.392394941193535], [30739, 6.379175944013234], [30751, 6.486156189926419], [30763, 6.209688902415145], [30787, 6.178539818534168], [30799, 6.400619032725637], [30811, 6.350720486198214], [30823, 6.329094630935491], [30847, 6.665008927790214], [30859, 6.365124540997716], [30871, 6.397554100188839], [30883, 6.313036329967217], [30895, 6.213539990579503], [30907, 6.188145056990987], [30919, 6.368157609787104], [30931, 6.022505532928909], [30943, 5.847560860383945], [30955, 6.431828731230944], [30967, 6.052384630155753], [30979, 6.09205234225733], [30991, 6.451919960028626], [31003, 6.306525652181399], [31015, 6.275374254796339], [31027, 6.547719186267029], [31039, 6.75428114103574], [31051, 5.935160867305503], [32095, 6.614875650835374], [32107, 6.338571466834589], [32119, 6.672658240004776], [32131, 6.47862364460798], [32143, 6.697237128402775], [32155, 6.651006857282636], [32167, 6.417045801876262], [32179, 6.443917962205552], [32191, 6.642170834901141], [32203, 6.566758325545412], [32215, 6.643956977481863], [32227, 6.664286091343059], [32251, 6.938114868980719], [32263, 6.416174524925313], [32275, 6.228458496413808], [32299, 6.105947805120945], [32311, 6.509197421633078], [32323, 6.058435519389705], [32335, 6.178182720128143], [32347, 6.331905143455865], [32359, 6.148865980825423], [32371, 5.9430288965334785], [32383, 6.094357279796787], [32395, 7.029487145277558], [32407, 6.45645748656101], [32419, 6.133617038940787], [32431, 6.995037470807345], [32443, 6.8848213364332835], [32575, 7.081332789899936], [32587, 7.000470547744046], [32599, 7.961773768352194], [32611, 7.892412143744067], [32623, 8.300943215160615], [32635, 7.740696294948778], [32647, 7.899362801856908], [32659, 8.026129835412513], [32839, 7.866160390101804], [32851, 7.525889272089572], [32863, 7.880661815260307], [32875, 8.102063593031273], [32887, 8.17574904937509], [32899, 8.029642517517631], [32911, 7.816522442915992], [32923, 7.875019585207422], [32995, 7.57178520518507], [33007, 8.043227171307532], [33019, 7.6017260675109934], [33031, 7.82903138091753], [33043, 8.035602539909206], [33055, 8.032344634273436], [33067, 7.956494678043551], [33079, 8.040394870466354], [33091, 8.265974462016704], [33103, 8.314520599112136], [33115, 7.711466716046887], [33127, 8.249104858096759], [33139, 8.092703106376574], [33151, 7.671631539522135], [33187, 7.603756786751667], [33199, 7.8744705947024], [33211, 7.876583181868409], [33223, 7.045785191239686], [33235, 7.214419625280855], [33271, 6.915296554458338], [33307, 6.983884865518055], [33319, 6.307286262967443], [33331, 6.170083357771768], [33343, 6.3739881214651675], [33355, 6.487307115522565], [33367, 6.1996751724760735], [33379, 5.983540664017081], [33391, 6.614709518442074], [33403, 6.38911865144933], [33415, 6.235554422955412], [33427, 6.258664676003992], [33439, 6.391057960112935], [33451, 5.9918270047000775], [33463, 6.48545963136695], [33523, 6.494636002248659], [33535, 6.38849522693952], [33547, 6.318738367280128], [33655, 4.288671477976082], [33715, 4.515504415396175], [33727, 3.589896939020522], [33739, 2.7694229448034964], [33763, 2.440329820475365], [33775, 2.7434165503847225], [33811, 2.54595455942826], [33823, 2.610793097477483], [33835, 2.5211569936104894], [34039, 3.869318579080323], [34051, 4.064451657057681], [34063, 4.113538008503764], [34075, 3.999084947844623], [34087, 4.188044418666948], [34123, 2.5593464763161227], [34135, 2.539517731658229], [34147, 2.601115095424691], [34159, 2.531358779832593], [34171, 2.657553312170405]] \ No newline at end of file +[[29227, 6.310830025929775], [29239, 6.459605420277555], [29251, 3.951776408283148], [29263, 3.9881029965177532], [29287, 3.9979523620018704], [29299, 4.087399084092216], [29323, 3.9719939042249344], [29335, 4.094989269589381], [29347, 4.075137677278278], [29359, 3.7606633184227682], [29371, 3.800067990618089], [29383, 3.9326962704972], [29395, 4.061596969932272], [29407, 3.8938342346078105], [29419, 3.8441017980300103], [29431, 3.9112529491627512], [29443, 9.06765487141435], [29455, 8.086962802052039], [29467, 8.179006215294853], [29479, 6.403175935582288], [29551, 8.940917985821384], [29563, 6.63365047390054], [29575, 6.142877200237559], [29599, 6.175813255879229], [29611, 6.300606485215324], [29623, 6.069828591981448], [29647, 6.379030821960219], [29659, 6.470249871393978], [29671, 6.406636395734696], [29743, 6.504796206672925], [29755, 6.459044366181097], [29767, 6.535462216227275], [29779, 7.5785888189967245], [29791, 6.26674845898], [29803, 5.960166797207595], [29815, 6.40374959362412], [29827, 6.214694998528], [29839, 6.170255889462543], [29851, 6.279465293605755], [29863, 6.814817571438463], [29875, 6.378669607467775], [30007, 6.6772233548485875], [30019, 6.363962334188091], [30031, 6.678932969927671], [30043, 6.437604749736519], [30055, 6.403120364964289], [30067, 6.2763743573487085], [30079, 6.39838641899592], [30091, 6.39319372636], [30103, 6.463154162881294], [30115, 6.212923051527036], [30127, 6.184014379069404], [30139, 6.4426339686903775], [30151, 6.542293148098557], [30163, 6.367300806455284], [30175, 6.324160425396711], [30187, 6.453529520248782], [30199, 6.578131698046559], [30211, 6.712916206870864], [30223, 6.716728168394116], [30235, 6.299097691275333], [30247, 6.872906129408509], [30259, 6.672350499835073], [30271, 6.437160390082652], [30511, 6.495041663221227], [30523, 6.961980743916843], [30535, 6.543195700844054], [30547, 6.428287446587889], [30559, 6.624213410418168], [30571, 6.50702072354812], [30583, 6.376887122590773], [30595, 6.527699602499407], [30619, 6.137261245742873], [30631, 6.529358251093369], [30643, 6.311598703731872], [30655, 6.608133257436263], [30667, 6.640232891027022], [30679, 6.338184001600987], [30691, 6.832529225601797], [30703, 6.310369038496842], [30715, 6.529657840439009], [30727, 6.392394941193535], [30739, 6.379175944013234], [30751, 6.486156189926419], [30763, 6.209688902415145], [30787, 6.178539818534168], [30799, 6.400619032725637], [30811, 6.350720486198214], [30823, 6.329094630935491], [30847, 6.665008927790214], [30859, 6.365124540997716], [30871, 6.397554100188839], [30883, 6.313036329967217], [30895, 6.213539990579503], [30907, 6.188145056990987], [30919, 6.368157609787104], [30931, 6.022505532928909], [30943, 5.847560860383945], [30955, 6.431828731230944], [30967, 6.052384630155753], [30979, 6.09205234225733], [30991, 6.451919960028626], [31003, 6.306525652181399], [31015, 6.275374254796339], [31027, 6.547719186267029], [31039, 6.75428114103574], [31051, 5.935160867305503], [32095, 6.614875650835374], [32107, 6.338571466834589], [32119, 6.672658240004776], [32131, 6.47862364460798], [32143, 6.697237128402775], [32155, 6.651006857282636], [32167, 6.417045801876262], [32179, 6.443917962205552], [32191, 6.642170834901141], [32203, 6.566758325545412], [32215, 6.643956977481863], [32227, 6.664286091343059], [32251, 6.938114868980719], [32263, 6.416174524925313], [32275, 6.228458496413808], [32299, 6.105947805120945], [32311, 6.509197421633078], [32323, 6.058435519389705], [32335, 6.178182720128143], [32347, 6.331905143455865], [32359, 6.148865980825423], [32371, 5.9430288965334785], [32383, 6.094357279796787], [32395, 7.029487145277558], [32407, 6.45645748656101], [32419, 6.133617038940787], [32431, 6.995037470807345], [32443, 6.8848213364332835], [32575, 7.081332789899936], [32587, 7.000470547744046], [32599, 7.961773768352194], [32611, 7.892412143744067], [32623, 8.300943215160615], [32635, 7.740696294948778], [32647, 7.899362801856908], [32659, 8.026129835412513], [32839, 7.866160390101804], [32851, 7.525889272089572], [32863, 7.880661815260307], [32875, 8.102063593031273], [32887, 8.17574904937509], [32899, 8.029642517517631], [32911, 7.816522442915992], [32923, 7.875019585207422], [32995, 7.57178520518507], [33007, 8.043227171307532], [33019, 7.6017260675109934], [33031, 7.82903138091753], [33043, 8.035602539909206], [33055, 8.032344634273436], [33067, 7.956494678043551], [33079, 8.040394870466354], [33091, 8.265974462016704], [33103, 8.314520599112136], [33115, 7.711466716046887], [33127, 8.249104858096759], [33139, 8.092703106376574], [33151, 7.671631539522135], [33187, 7.603756786751667], [33199, 7.8744705947024], [33211, 7.876583181868409], [33223, 7.045785191239686], [33235, 7.214419625280855], [33271, 6.915296554458338], [33307, 6.983884865518055], [33319, 6.307286262967443], [33331, 6.170083357771768], [33343, 6.3739881214651675], [33355, 6.487307115522565], [33367, 6.1996751724760735], [33379, 5.983540664017081], [33391, 6.614709518442074], [33403, 6.38911865144933], [33415, 6.235554422955412], [33427, 6.258664676003992], [33439, 6.391057960112935], [33451, 5.9918270047000775], [33463, 6.48545963136695], [33523, 6.494636002248659], [33535, 6.38849522693952], [33547, 6.318738367280128], [33655, 4.288671477976082], [33715, 4.515504415396175], [33727, 3.589896939020522], [33739, 2.7694229448034964], [33763, 2.440329820475365], [33775, 2.7434165503847225], [33811, 2.54595455942826], [33823, 2.610793097477483], [33835, 2.5211569936104894], [34039, 3.869318579080323], [34051, 4.064451657057681], [34063, 4.113538008503764], [34075, 3.999084947844623], [34087, 4.188044418666948], [34123, 2.5593464763161227], [34135, 2.539517731658229], [34147, 2.601115095424691], [34159, 2.531358779832593], [34171, 2.6050478246592697]] \ No newline at end of file diff --git a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.time_predict.json b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.time_predict.json index 3b9f582e6f..bc84b69802 100644 --- a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.time_predict.json +++ b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.time_predict.json @@ -1 +1 @@ -[[29227, 0.05330100658857589], [29239, 0.05667244629729582], [29251, 0.04198266587880483], [29263, 0.04206361526903825], [29287, 0.04227328375357946], [29299, 0.0421375871005381], [29323, 0.04194422303222947], [29335, 0.04217488135105129], [29347, 0.04199817801964621], [29359, 0.04204777824786485], [29371, 0.04129859241744152], [29383, 0.04138453741280051], [29395, 0.041963212623320846], [29407, 0.04244452956468367], [29419, 0.04228444658896627], [29431, 0.04211552452013658], [29443, 0.06873452332878498], [29455, 0.06996038921278694], [29467, 0.0625027867758128], [29479, 0.0652473653787209], [29551, 0.0713275242806392], [29563, 0.05982415879345671], [29575, 0.05547773118959431], [29599, 0.055695642709682566], [29611, 0.05844586593213865], [29623, 0.053652669183450845], [29647, 0.05822559269807848], [29659, 0.058379946442345516], [29671, 0.05792603868871032], [29743, 0.05632096033348462], [29755, 0.057079167035277004], [29767, 0.05847547782720669], [29779, 0.0669548915380779], [29791, 0.055879039799977555], [29803, 0.05490128313677228], [29815, 0.05748618853782087], [29827, 0.05459780558183465], [29839, 0.05313720512647527], [29851, 0.0536410551630609], [29863, 0.06430842296326134], [29875, 0.06019349301218849], [30007, 0.05956691185549384], [30019, 0.057475609383732564], [30031, 0.06133077465512989], [30043, 0.054628571289598395], [30055, 0.053156574423620304], [30067, 0.061095488162063914], [30079, 0.05638663609540568], [30091, 0.06318762432150465], [30103, 0.0607294434433651], [30115, 0.058966588814691474], [30127, 0.05451464926994407], [30139, 0.054765371422107606], [30151, 0.06011367118600739], [30163, 0.056489092442192364], [30175, 0.05721004163645034], [30187, 0.056085718955725755], [30199, 0.05496784920715749], [30211, 0.05595294781576185], [30223, 0.056366255880067107], [30235, 0.05415607259076183], [30247, 0.05611006011779504], [30259, 0.05899770340614267], [30271, 0.05463459301637721], [30511, 0.056668462781986284], [30523, 0.05622984893795558], [30535, 0.05739729275959679], [30547, 0.05681637075808692], [30559, 0.060413605953992346], [30571, 0.05630140691071245], [30583, 0.05691600764945691], [30595, 0.05758788760113438], [30619, 0.057878916707713994], [30631, 0.05920646676205348], [30643, 0.05772455622356631], [30655, 0.05624641591443788], [30667, 0.05679231151133974], [30679, 0.054070971785978916], [30691, 0.0526207039163535], [30703, 0.0568605245511164], [30715, 0.061507434663884406], [30727, 0.056893424307812294], [30739, 0.055618187812760844], [30751, 0.05480453231348002], [30763, 0.05527856868056894], [30787, 0.05369613998913062], [30799, 0.05394377209154838], [30811, 0.05292925156575404], [30823, 0.05631691372488531], [30847, 0.05994874265449596], [30859, 0.054887482996678935], [30871, 0.05269443848108159], [30883, 0.05455369081832994], [30895, 0.052836306633894], [30907, 0.06098605434374009], [30919, 0.05790166351062864], [30931, 0.05384557371307583], [30943, 0.0552518731478915], [30955, 0.058325004825037094], [30967, 0.05570007195687038], [30979, 0.05786155653369753], [30991, 0.0565637071198246], [31003, 0.05358528579216718], [31015, 0.0565194246942109], [31027, 0.060639867891738086], [31039, 0.05456077163398431], [31051, 0.05364465511177855], [32095, 0.05701634567017549], [32107, 0.056551735159852935], [32119, 0.059741534374653515], [32131, 0.059117927290255695], [32143, 0.05865596986386831], [32155, 0.05976686535124616], [32167, 0.05748221583208962], [32179, 0.05599189131897629], [32191, 0.057050021252176536], [32203, 0.056749524773586246], [32215, 0.05848270147560514], [32227, 0.058134177369080726], [32251, 0.05677558960523539], [32263, 0.05732504526152308], [32275, 0.05388538321269921], [32299, 0.054489875556420334], [32311, 0.05523491625033757], [32323, 0.05210722926818761], [32335, 0.05177919388626566], [32347, 0.05285931858246973], [32359, 0.05405915261257117], [32371, 0.05125248388501069], [32383, 0.0529911891182192], [32395, 0.05899431208443509], [32407, 0.054278939213363256], [32419, 0.05517846305755866], [32431, 0.054895506066224065], [32443, 0.05776776268385073], [32575, 0.05852895304204339], [32587, 0.05550279797242395], [32599, 0.05859429586191187], [32611, 0.05930045999108846], [32623, 0.05970807673118869], [32635, 0.05933587841532029], [32647, 0.05664705727223668], [32659, 0.05848261197406044], [32839, 0.05918756714016122], [32851, 0.05416312731514607], [32863, 0.055330169292270755], [32875, 0.05846596690841535], [32887, 0.05964627876101778], [32899, 0.05477083545675092], [32911, 0.06103849267577067], [32923, 0.059993592789716395], [32995, 0.05411497824904338], [33007, 0.05999668614663666], [33019, 0.05350510891772012], [33031, 0.055163962916631476], [33043, 0.05656445765588542], [33055, 0.05452211733878773], [33067, 0.055837532440904274], [33079, 0.057193650930531664], [33091, 0.0590892645969792], [33103, 0.057817438616213496], [33115, 0.054078458178947394], [33127, 0.06039717008485825], [33139, 0.05729370939152657], [33151, 0.054306990246640034], [33187, 0.0584423464442237], [33199, 0.05413206046676942], [33211, 0.05832109175916565], [33223, 0.054307594234121626], [33235, 0.051154545361451594], [33271, 0.04697923370309359], [33307, 0.04968563661938185], [33319, 0.04515377174590848], [33331, 0.04314215119464605], [33343, 0.04616299824916273], [33355, 0.04548927672429956], [33367, 0.046679732690163435], [33379, 0.04573871681629864], [33391, 0.0454295470001103], [33403, 0.04563997031599798], [33415, 0.04372535211745655], [33427, 0.04734909464440329], [33439, 0.04713825766208572], [33451, 0.04370599655276682], [33463, 0.047628210644034115], [33523, 0.0449947515911722], [33535, 0.045052300768588585], [33547, 0.04673312954024467], [33655, 0.04347735946664293], [33715, 0.05175957929643943], [33727, 0.04508296222414761], [33739, 0.04842307865632932], [33763, 0.04985840642239429], [33775, 0.046407306447941374], [33811, 0.04314465647438873], [33823, 0.043014392763628034], [33835, 0.04615384143815281], [34039, 0.04366897901375042], [34051, 0.0465333565646916], [34063, 0.05262438909739221], [34075, 0.04876659421675687], [34087, 0.04992856254470007], [34123, 0.04635442527237932], [34135, 0.04449776212570464], [34147, 0.04672353412559721], [34159, 0.043901398343369896], [34171, 0.04694349316703277]] \ No newline at end of file +[[29227, 0.05330100658857589], [29239, 0.05667244629729582], [29251, 0.04198266587880483], [29263, 0.04206361526903825], [29287, 0.04227328375357946], [29299, 0.0421375871005381], [29323, 0.04194422303222947], [29335, 0.04217488135105129], [29347, 0.04199817801964621], [29359, 0.04204777824786485], [29371, 0.04129859241744152], [29383, 0.04138453741280051], [29395, 0.041963212623320846], [29407, 0.04244452956468367], [29419, 0.04228444658896627], [29431, 0.04211552452013658], [29443, 0.06873452332878498], [29455, 0.06996038921278694], [29467, 0.0625027867758128], [29479, 0.0652473653787209], [29551, 0.0713275242806392], [29563, 0.05982415879345671], [29575, 0.05547773118959431], [29599, 0.055695642709682566], [29611, 0.05844586593213865], [29623, 0.053652669183450845], [29647, 0.05822559269807848], [29659, 0.058379946442345516], [29671, 0.05792603868871032], [29743, 0.05632096033348462], [29755, 0.057079167035277004], [29767, 0.05847547782720669], [29779, 0.0669548915380779], [29791, 0.055879039799977555], [29803, 0.05490128313677228], [29815, 0.05748618853782087], [29827, 0.05459780558183465], [29839, 0.05313720512647527], [29851, 0.0536410551630609], [29863, 0.06430842296326134], [29875, 0.06019349301218849], [30007, 0.05956691185549384], [30019, 0.057475609383732564], [30031, 0.06133077465512989], [30043, 0.054628571289598395], [30055, 0.053156574423620304], [30067, 0.061095488162063914], [30079, 0.05638663609540568], [30091, 0.06318762432150465], [30103, 0.0607294434433651], [30115, 0.058966588814691474], [30127, 0.05451464926994407], [30139, 0.054765371422107606], [30151, 0.06011367118600739], [30163, 0.056489092442192364], [30175, 0.05721004163645034], [30187, 0.056085718955725755], [30199, 0.05496784920715749], [30211, 0.05595294781576185], [30223, 0.056366255880067107], [30235, 0.05415607259076183], [30247, 0.05611006011779504], [30259, 0.05899770340614267], [30271, 0.05463459301637721], [30511, 0.056668462781986284], [30523, 0.05622984893795558], [30535, 0.05739729275959679], [30547, 0.05681637075808692], [30559, 0.060413605953992346], [30571, 0.05630140691071245], [30583, 0.05691600764945691], [30595, 0.05758788760113438], [30619, 0.057878916707713994], [30631, 0.05920646676205348], [30643, 0.05772455622356631], [30655, 0.05624641591443788], [30667, 0.05679231151133974], [30679, 0.054070971785978916], [30691, 0.0526207039163535], [30703, 0.0568605245511164], [30715, 0.061507434663884406], [30727, 0.056893424307812294], [30739, 0.055618187812760844], [30751, 0.05480453231348002], [30763, 0.05527856868056894], [30787, 0.05369613998913062], [30799, 0.05394377209154838], [30811, 0.05292925156575404], [30823, 0.05631691372488531], [30847, 0.05994874265449596], [30859, 0.054887482996678935], [30871, 0.05269443848108159], [30883, 0.05455369081832994], [30895, 0.052836306633894], [30907, 0.06098605434374009], [30919, 0.05790166351062864], [30931, 0.05384557371307583], [30943, 0.0552518731478915], [30955, 0.058325004825037094], [30967, 0.05570007195687038], [30979, 0.05786155653369753], [30991, 0.0565637071198246], [31003, 0.05358528579216718], [31015, 0.0565194246942109], [31027, 0.060639867891738086], [31039, 0.05456077163398431], [31051, 0.05364465511177855], [32095, 0.05701634567017549], [32107, 0.056551735159852935], [32119, 0.059741534374653515], [32131, 0.059117927290255695], [32143, 0.05865596986386831], [32155, 0.05976686535124616], [32167, 0.05748221583208962], [32179, 0.05599189131897629], [32191, 0.057050021252176536], [32203, 0.056749524773586246], [32215, 0.05848270147560514], [32227, 0.058134177369080726], [32251, 0.05677558960523539], [32263, 0.05732504526152308], [32275, 0.05388538321269921], [32299, 0.054489875556420334], [32311, 0.05523491625033757], [32323, 0.05210722926818761], [32335, 0.05177919388626566], [32347, 0.05285931858246973], [32359, 0.05405915261257117], [32371, 0.05125248388501069], [32383, 0.0529911891182192], [32395, 0.05899431208443509], [32407, 0.054278939213363256], [32419, 0.05517846305755866], [32431, 0.054895506066224065], [32443, 0.05776776268385073], [32575, 0.05852895304204339], [32587, 0.05550279797242395], [32599, 0.05859429586191187], [32611, 0.05930045999108846], [32623, 0.05970807673118869], [32635, 0.05933587841532029], [32647, 0.05664705727223668], [32659, 0.05848261197406044], [32839, 0.05918756714016122], [32851, 0.05416312731514607], [32863, 0.055330169292270755], [32875, 0.05846596690841535], [32887, 0.05964627876101778], [32899, 0.05477083545675092], [32911, 0.06103849267577067], [32923, 0.059993592789716395], [32995, 0.05411497824904338], [33007, 0.05999668614663666], [33019, 0.05350510891772012], [33031, 0.055163962916631476], [33043, 0.05656445765588542], [33055, 0.05452211733878773], [33067, 0.055837532440904274], [33079, 0.057193650930531664], [33091, 0.0590892645969792], [33103, 0.057817438616213496], [33115, 0.054078458178947394], [33127, 0.06039717008485825], [33139, 0.05729370939152657], [33151, 0.054306990246640034], [33187, 0.0584423464442237], [33199, 0.05413206046676942], [33211, 0.05832109175916565], [33223, 0.054307594234121626], [33235, 0.051154545361451594], [33271, 0.04697923370309359], [33307, 0.04968563661938185], [33319, 0.04515377174590848], [33331, 0.04314215119464605], [33343, 0.04616299824916273], [33355, 0.04548927672429956], [33367, 0.046679732690163435], [33379, 0.04573871681629864], [33391, 0.0454295470001103], [33403, 0.04563997031599798], [33415, 0.04372535211745655], [33427, 0.04734909464440329], [33439, 0.04713825766208572], [33451, 0.04370599655276682], [33463, 0.047628210644034115], [33523, 0.0449947515911722], [33535, 0.045052300768588585], [33547, 0.04673312954024467], [33655, 0.04347735946664293], [33715, 0.05175957929643943], [33727, 0.04508296222414761], [33739, 0.04842307865632932], [33763, 0.04985840642239429], [33775, 0.046407306447941374], [33811, 0.04314465647438873], [33823, 0.043014392763628034], [33835, 0.04615384143815281], [34039, 0.04366897901375042], [34051, 0.0465333565646916], [34063, 0.05262438909739221], [34075, 0.04876659421675687], [34087, 0.04992856254470007], [34123, 0.04635442527237932], [34135, 0.04449776212570464], [34147, 0.04672353412559721], [34159, 0.043901398343369896], [34171, 0.04717164808524658]] \ No newline at end of file diff --git a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.track_test_score.json b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.track_test_score.json index 640082b4ff..ae0e6ebdbd 100644 --- a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.track_test_score.json +++ b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.track_test_score.json @@ -1 +1 @@ -[[29227, 0.23992979507728426], [29239, 0.23996453638928664], [29251, 0.23983800065926805], [29263, 0.23862278618357818], [29287, 0.24077103810927536], [29299, 0.2394657260126239], [29323, 0.2396171751595747], [29335, 0.23952791556923328], [29347, 0.2414395107207814], [29359, 0.2417150365358336], [29371, 0.2410521191947952], [29383, 0.23744046740262156], [29395, 0.24094265911545515], [29407, 0.24227853440354066], [29419, 0.23994611666430568], [29431, 0.24240399024806944], [29443, 0.23503599649622728], [29455, 0.24073970657133775], [29467, 0.2391423790971955], [29479, 0.2397035836848513], [29551, 0.24108381739178733], [29563, 0.23971130136863736], [29575, 0.2383421521794865], [29599, 0.24209132473831307], [29611, 0.2351316414469322], [29623, 0.2404748382661945], [29647, 0.23847218532446512], [29659, 0.24076583590772882], [29671, 0.24149046309580766], [29743, 0.24029060474971525], [29755, 0.2397481388254479], [29767, 0.2390339108044105], [29779, 0.23973081879848518], [29791, 0.2385301292343005], [29803, 0.2396130682074683], [29815, 0.23899610024498727], [29827, 0.24159687432866256], [29839, 0.24184962672407156], [29851, 0.23917153296799043], [29863, 0.24034582382327002], [29875, 0.24200003996479075], [30007, 0.23946631608164204], [30019, 0.24003502964338058], [30031, 0.23928658211689596], [30043, 0.2422417459809017], [30055, 0.24393903485029622], [30067, 0.23546348735868944], [30079, 0.23912387788962855], [30091, 0.23896352933750817], [30103, 0.239806923147145], [30115, 0.23966103228218683], [30127, 0.23780659716539723], [30139, 0.24079315486691283], [30151, 0.23898675525841148], [30163, 0.24032075099580139], [30175, 0.2410370452926157], [30187, 0.237602545956486], [30199, 0.23962182789607597], [30211, 0.23844692430203038], [30223, 0.23887931630452525], [30235, 0.23933793262766145], [30247, 0.2384271650171095], [30259, 0.2367703176591192], [30271, 0.23874374341662857], [30511, 0.23761710995115815], [30523, 0.24051464246776377], [30535, 0.24161468797625946], [30547, 0.2378157217675346], [30559, 0.23970180170282818], [30571, 0.24291181743534696], [30583, 0.23973212982863887], [30595, 0.23746018119189655], [30619, 0.23860931461028048], [30631, 0.24064748303352834], [30643, 0.23854758720595556], [30655, 0.24041865632250595], [30667, 0.240200945025078], [30679, 0.2380664767126677], [30691, 0.24073514598080337], [30703, 0.2371254791973175], [30715, 0.23855385360898948], [30727, 0.23744404296354632], [30739, 0.2409948523935066], [30751, 0.2385590866087331], [30763, 0.23741886602206796], [30787, 0.24055287407208123], [30799, 0.23946160841576375], [30811, 0.23281434764197334], [30823, 0.24202043994576314], [30847, 0.2416116847950284], [30859, 0.240366054455643], [30871, 0.24008733264150608], [30883, 0.23945513757465897], [30895, 0.23779579926912467], [30907, 0.24240998937607927], [30919, 0.24083866522387398], [30931, 0.24140541195758636], [30943, 0.23821377620478043], [30955, 0.2371495915759986], [30967, 0.23984196973327032], [30979, 0.23828226086249707], [30991, 0.24014722349144493], [31003, 0.24114803053528952], [31015, 0.23923522717078696], [31027, 0.23972890448406028], [31039, 0.23611479251087752], [31051, 0.24064141545825446], [32095, 0.24349452121029758], [32107, 0.2380190831027605], [32119, 0.24116858731496352], [32131, 0.23878056605294073], [32143, 0.2388975170353901], [32155, 0.23792658123292343], [32167, 0.24054790709205734], [32179, 0.2378515278105024], [32191, 0.2401217903269255], [32203, 0.24032846598758054], [32215, 0.24005399150589884], [32227, 0.24078004719318855], [32251, 0.2393240567909139], [32263, 0.240324201167042], [32275, 0.24016420113774198], [32299, 0.2432389675943607], [32311, 0.24000872056030476], [32323, 0.244598172945857], [32335, 0.24036750602410908], [32347, 0.24143550655172694], [32359, 0.24032774074149166], [32371, 0.23772945308258103], [32383, 0.24179937712964766], [32395, 0.2408839714112621], [32407, 0.23998249842151548], [32419, 0.23947675685209316], [32431, 0.23899304605810487], [32443, 0.23991195955781053], [32575, 0.23894226668287444], [32587, 0.24005356767902725], [32599, 0.23993263620933725], [32611, 0.24075486638951246], [32623, 0.2419243200134161], [32635, 0.23747438376718621], [32647, 0.24019225967937144], [32659, 0.2379254453507363], [32839, 0.23902667104451544], [32851, 0.23999960898521605], [32863, 0.23663043982950568], [32875, 0.23857914699762353], [32887, 0.24319165138464455], [32899, 0.24108135220765253], [32911, 0.2354565009792357], [32923, 0.24192006044721934], [32995, 0.23864713105742266], [33007, 0.24135802962015965], [33019, 0.24112960349123655], [33031, 0.23964969367074823], [33043, 0.24068485860192387], [33055, 0.23807759878295975], [33067, 0.23917572791361924], [33079, 0.23954839849065104], [33091, 0.24267656237213686], [33103, 0.2386133483971184], [33115, 0.240689462824766], [33127, 0.24208805354603313], [33139, 0.2387737388693511], [33151, 0.24256971378587855], [33187, 0.23916935792493857], [33199, 0.24014542406964406], [33211, 0.2373829621600277], [33223, 0.23931089199263633], [33235, 0.24056207376437036], [33271, 0.23969378314207657], [33307, 0.23926393018922223], [33319, 0.24006421754394117], [33331, 0.24002147067131904], [33343, 0.24112615354717684], [33355, 0.23787341103854245], [33367, 0.24015001631501934], [33379, 0.24158707263596196], [33391, 0.23812719266297805], [33403, 0.2391536103275651], [33415, 0.23975850885974753], [33427, 0.2408292394110173], [33439, 0.24191621863395268], [33451, 0.23888014008760966], [33463, 0.23980008874225064], [33523, 0.2406916389971412], [33535, 0.2403284066958125], [33547, 0.23878469127640303], [33655, 0.23968525120572964], [33715, 0.23941610588459636], [33727, 0.23792356977831308], [33739, 0.24178414365790607], [33763, 0.2373498611382042], [33775, 0.24163989206013956], [33811, 0.23896859921576197], [33823, 0.23983217116142472], [33835, 0.2406731037176753], [34039, 0.24245225645282198], [34051, 0.23988152004074811], [34063, 0.2398104339869858], [34075, 0.24054674722419672], [34087, 0.23766232894037315], [34123, 0.23805376837185185], [34135, 0.2389980239640323], [34147, 0.23799620606742078], [34159, 0.2394832085356985], [34171, 0.238885379013793]] \ No newline at end of file +[[29227, 0.23992979507728426], [29239, 0.23996453638928664], [29251, 0.23983800065926805], [29263, 0.23862278618357818], [29287, 0.24077103810927536], [29299, 0.2394657260126239], [29323, 0.2396171751595747], [29335, 0.23952791556923328], [29347, 0.2414395107207814], [29359, 0.2417150365358336], [29371, 0.2410521191947952], [29383, 0.23744046740262156], [29395, 0.24094265911545515], [29407, 0.24227853440354066], [29419, 0.23994611666430568], [29431, 0.24240399024806944], [29443, 0.23503599649622728], [29455, 0.24073970657133775], [29467, 0.2391423790971955], [29479, 0.2397035836848513], [29551, 0.24108381739178733], [29563, 0.23971130136863736], [29575, 0.2383421521794865], [29599, 0.24209132473831307], [29611, 0.2351316414469322], [29623, 0.2404748382661945], [29647, 0.23847218532446512], [29659, 0.24076583590772882], [29671, 0.24149046309580766], [29743, 0.24029060474971525], [29755, 0.2397481388254479], [29767, 0.2390339108044105], [29779, 0.23973081879848518], [29791, 0.2385301292343005], [29803, 0.2396130682074683], [29815, 0.23899610024498727], [29827, 0.24159687432866256], [29839, 0.24184962672407156], [29851, 0.23917153296799043], [29863, 0.24034582382327002], [29875, 0.24200003996479075], [30007, 0.23946631608164204], [30019, 0.24003502964338058], [30031, 0.23928658211689596], [30043, 0.2422417459809017], [30055, 0.24393903485029622], [30067, 0.23546348735868944], [30079, 0.23912387788962855], [30091, 0.23896352933750817], [30103, 0.239806923147145], [30115, 0.23966103228218683], [30127, 0.23780659716539723], [30139, 0.24079315486691283], [30151, 0.23898675525841148], [30163, 0.24032075099580139], [30175, 0.2410370452926157], [30187, 0.237602545956486], [30199, 0.23962182789607597], [30211, 0.23844692430203038], [30223, 0.23887931630452525], [30235, 0.23933793262766145], [30247, 0.2384271650171095], [30259, 0.2367703176591192], [30271, 0.23874374341662857], [30511, 0.23761710995115815], [30523, 0.24051464246776377], [30535, 0.24161468797625946], [30547, 0.2378157217675346], [30559, 0.23970180170282818], [30571, 0.24291181743534696], [30583, 0.23973212982863887], [30595, 0.23746018119189655], [30619, 0.23860931461028048], [30631, 0.24064748303352834], [30643, 0.23854758720595556], [30655, 0.24041865632250595], [30667, 0.240200945025078], [30679, 0.2380664767126677], [30691, 0.24073514598080337], [30703, 0.2371254791973175], [30715, 0.23855385360898948], [30727, 0.23744404296354632], [30739, 0.2409948523935066], [30751, 0.2385590866087331], [30763, 0.23741886602206796], [30787, 0.24055287407208123], [30799, 0.23946160841576375], [30811, 0.23281434764197334], [30823, 0.24202043994576314], [30847, 0.2416116847950284], [30859, 0.240366054455643], [30871, 0.24008733264150608], [30883, 0.23945513757465897], [30895, 0.23779579926912467], [30907, 0.24240998937607927], [30919, 0.24083866522387398], [30931, 0.24140541195758636], [30943, 0.23821377620478043], [30955, 0.2371495915759986], [30967, 0.23984196973327032], [30979, 0.23828226086249707], [30991, 0.24014722349144493], [31003, 0.24114803053528952], [31015, 0.23923522717078696], [31027, 0.23972890448406028], [31039, 0.23611479251087752], [31051, 0.24064141545825446], [32095, 0.24349452121029758], [32107, 0.2380190831027605], [32119, 0.24116858731496352], [32131, 0.23878056605294073], [32143, 0.2388975170353901], [32155, 0.23792658123292343], [32167, 0.24054790709205734], [32179, 0.2378515278105024], [32191, 0.2401217903269255], [32203, 0.24032846598758054], [32215, 0.24005399150589884], [32227, 0.24078004719318855], [32251, 0.2393240567909139], [32263, 0.240324201167042], [32275, 0.24016420113774198], [32299, 0.2432389675943607], [32311, 0.24000872056030476], [32323, 0.244598172945857], [32335, 0.24036750602410908], [32347, 0.24143550655172694], [32359, 0.24032774074149166], [32371, 0.23772945308258103], [32383, 0.24179937712964766], [32395, 0.2408839714112621], [32407, 0.23998249842151548], [32419, 0.23947675685209316], [32431, 0.23899304605810487], [32443, 0.23991195955781053], [32575, 0.23894226668287444], [32587, 0.24005356767902725], [32599, 0.23993263620933725], [32611, 0.24075486638951246], [32623, 0.2419243200134161], [32635, 0.23747438376718621], [32647, 0.24019225967937144], [32659, 0.2379254453507363], [32839, 0.23902667104451544], [32851, 0.23999960898521605], [32863, 0.23663043982950568], [32875, 0.23857914699762353], [32887, 0.24319165138464455], [32899, 0.24108135220765253], [32911, 0.2354565009792357], [32923, 0.24192006044721934], [32995, 0.23864713105742266], [33007, 0.24135802962015965], [33019, 0.24112960349123655], [33031, 0.23964969367074823], [33043, 0.24068485860192387], [33055, 0.23807759878295975], [33067, 0.23917572791361924], [33079, 0.23954839849065104], [33091, 0.24267656237213686], [33103, 0.2386133483971184], [33115, 0.240689462824766], [33127, 0.24208805354603313], [33139, 0.2387737388693511], [33151, 0.24256971378587855], [33187, 0.23916935792493857], [33199, 0.24014542406964406], [33211, 0.2373829621600277], [33223, 0.23931089199263633], [33235, 0.24056207376437036], [33271, 0.23969378314207657], [33307, 0.23926393018922223], [33319, 0.24006421754394117], [33331, 0.24002147067131904], [33343, 0.24112615354717684], [33355, 0.23787341103854245], [33367, 0.24015001631501934], [33379, 0.24158707263596196], [33391, 0.23812719266297805], [33403, 0.2391536103275651], [33415, 0.23975850885974753], [33427, 0.2408292394110173], [33439, 0.24191621863395268], [33451, 0.23888014008760966], [33463, 0.23980008874225064], [33523, 0.2406916389971412], [33535, 0.2403284066958125], [33547, 0.23878469127640303], [33655, 0.23968525120572964], [33715, 0.23941610588459636], [33727, 0.23792356977831308], [33739, 0.24178414365790607], [33763, 0.2373498611382042], [33775, 0.24163989206013956], [33811, 0.23896859921576197], [33823, 0.23983217116142472], [33835, 0.2406731037176753], [34039, 0.24245225645282198], [34051, 0.23988152004074811], [34063, 0.2398104339869858], [34075, 0.24054674722419672], [34087, 0.23766232894037315], [34123, 0.23805376837185185], [34135, 0.2389980239640323], [34147, 0.23799620606742078], [34159, 0.2394832085356985], [34171, 0.23932352024795767]] \ No newline at end of file diff --git a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.track_train_score.json b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.track_train_score.json index baab2e892b..d3fd7f0818 100644 --- a/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.track_train_score.json +++ b/graphs/summary/ensemble.GradientBoostingClassifierBenchmark.track_train_score.json @@ -1 +1 @@ -[[29227, 0.3078993708968104], [29239, 0.3086506649210312], [29251, 0.3090241562246527], [29263, 0.307763110576788], [29287, 0.3083762379040027], [29299, 0.3089921760161314], [29323, 0.3083522598495631], [29335, 0.30912447466871207], [29347, 0.3087319234107716], [29359, 0.3101888385024271], [29371, 0.3081167058168037], [29383, 0.3093241366446506], [29395, 0.30942228836955066], [29407, 0.3091005257761801], [29419, 0.30861387716130156], [29431, 0.3095877927549895], [29443, 0.3076274255377279], [29455, 0.30867551915788904], [29467, 0.3088365896093635], [29479, 0.308683176130655], [29551, 0.30970041996227365], [29563, 0.3090481561172878], [29575, 0.3107165908497551], [29599, 0.3094683924622065], [29611, 0.305936635676955], [29623, 0.3085966396272891], [29647, 0.30794586365754234], [29659, 0.308544375828211], [29671, 0.3100627502551094], [29743, 0.3097214116052243], [29755, 0.3072957680549575], [29767, 0.3093524815190978], [29779, 0.308467115731339], [29791, 0.3087165358293146], [29803, 0.30959454101191697], [29815, 0.3087427689517219], [29827, 0.3089346214328879], [29839, 0.31017807191266766], [29851, 0.30881399694605727], [29863, 0.31036205935602795], [29875, 0.3091089307413447], [30007, 0.3079840340133625], [30019, 0.30878622820443036], [30031, 0.31021805682624315], [30043, 0.30971283248395765], [30055, 0.30957789238590194], [30067, 0.3086130345703739], [30079, 0.3086024012048336], [30091, 0.3081012243136032], [30103, 0.30790650931523017], [30115, 0.3081144036246228], [30127, 0.3080052600652872], [30139, 0.3089728722940658], [30151, 0.3083370528109142], [30163, 0.30856915959895387], [30175, 0.3079154622622919], [30187, 0.30858725662131054], [30199, 0.3096496857858766], [30211, 0.3091269090885356], [30223, 0.30943257609580294], [30235, 0.3085540089541481], [30247, 0.3088099687722115], [30259, 0.3095901916149956], [30271, 0.30946368174422795], [30511, 0.30806861681698633], [30523, 0.3084796815044271], [30535, 0.3082027473813172], [30547, 0.3082969264730667], [30559, 0.30915808217097607], [30571, 0.30912851375542155], [30583, 0.30984459647635443], [30595, 0.3092708070860233], [30619, 0.30987413992625923], [30631, 0.3085026221460785], [30643, 0.3092364606879862], [30655, 0.3089433900347298], [30667, 0.3084020709750024], [30679, 0.3074497779700447], [30691, 0.3090519339848951], [30703, 0.30873047377772034], [30715, 0.3080454284937578], [30727, 0.30863187367385403], [30739, 0.3089051997376782], [30751, 0.30839477413593563], [30763, 0.30761009382058946], [30787, 0.30804815042440103], [30799, 0.30887764000890616], [30811, 0.3080526163552032], [30823, 0.30878156628570147], [30847, 0.3083725702896315], [30859, 0.308030298396846], [30871, 0.30820582526454], [30883, 0.31011230394076433], [30895, 0.3081307636605102], [30907, 0.30886934756747514], [30919, 0.3096492012126781], [30931, 0.30774482713057544], [30943, 0.30905339044111213], [30955, 0.3096885512657005], [30967, 0.3094042940636227], [30979, 0.30813564573840163], [30991, 0.3087535541004075], [31003, 0.30944715684202573], [31015, 0.30997246723268496], [31027, 0.30533906092640084], [31039, 0.30756890921880975], [31051, 0.30905472695595204], [32095, 0.31042410018785876], [32107, 0.30922822691926893], [32119, 0.30956617627959643], [32131, 0.3084492957334006], [32143, 0.3088108495209832], [32155, 0.3072273909170253], [32167, 0.30963695397705876], [32179, 0.3075159592064263], [32191, 0.3086966188237551], [32203, 0.30928973215607436], [32215, 0.3085625590699535], [32227, 0.30821094617025996], [32251, 0.30958928132129176], [32263, 0.30930302989855113], [32275, 0.3096032460098818], [32299, 0.30933614172518076], [32311, 0.3085312286574418], [32323, 0.3095511179191892], [32335, 0.30833300547973125], [32347, 0.30992048132555283], [32359, 0.30937261762298646], [32371, 0.30801355821781695], [32383, 0.30893978181865345], [32395, 0.30987215548262675], [32407, 0.30752575907049506], [32419, 0.30830312789832165], [32431, 0.3079541999227795], [32443, 0.30751133316455137], [32575, 0.30907854071086893], [32587, 0.3096899454296903], [32599, 0.30894922595303714], [32611, 0.3080567862033076], [32623, 0.30736639066066385], [32635, 0.3083298922396443], [32647, 0.31113268215251433], [32659, 0.3082748534984192], [32839, 0.31011960258106214], [32851, 0.3098418085486637], [32863, 0.3085713041283169], [32875, 0.30945445337997646], [32887, 0.30907552837489166], [32899, 0.3073748244059974], [32911, 0.3096082535645527], [32923, 0.30817754068807546], [32995, 0.30924361686401364], [33007, 0.30873201842536857], [33019, 0.30971936234364217], [33031, 0.31009529359630683], [33043, 0.3075504753565963], [33055, 0.306885414402024], [33067, 0.30970307058562735], [33079, 0.30674712495055734], [33091, 0.31010136465904237], [33103, 0.3089790027719438], [33115, 0.30851929670947714], [33127, 0.3104096832795697], [33139, 0.3079489694482311], [33151, 0.30968707045668425], [33187, 0.3080864015191738], [33199, 0.30860886829543777], [33211, 0.3080573952535449], [33223, 0.30828051870693907], [33235, 0.30947511264516686], [33271, 0.3090114023627249], [33307, 0.3090549870970347], [33319, 0.30831785872663636], [33331, 0.3089996788253432], [33343, 0.30964344785618225], [33355, 0.30882209653387666], [33367, 0.3091162535925723], [33379, 0.308645344547819], [33391, 0.30926110786141126], [33403, 0.30907127293745695], [33415, 0.30944019187261657], [33427, 0.30896307099742204], [33439, 0.3078336502300715], [33451, 0.3098826900946818], [33463, 0.30927340748405174], [33523, 0.3095469852213809], [33535, 0.3101827363035049], [33547, 0.3082172248296501], [33655, 0.30918608160191136], [33715, 0.30851743108234864], [33727, 0.30873991838317], [33739, 0.3089405880128217], [33763, 0.30719013301615294], [33775, 0.3075463990736112], [33811, 0.3085696241295679], [33823, 0.3087465190380327], [33835, 0.3086100262949762], [34039, 0.30979747788831], [34051, 0.3082427085403625], [34063, 0.3089788482454664], [34075, 0.3079305083906039], [34087, 0.30921249242219756], [34123, 0.3082654844031513], [34135, 0.30803763469416034], [34147, 0.30968098950610984], [34159, 0.3083512592486555], [34171, 0.30940749486917346]] \ No newline at end of file +[[29227, 0.3078993708968104], [29239, 0.3086506649210312], [29251, 0.3090241562246527], [29263, 0.307763110576788], [29287, 0.3083762379040027], [29299, 0.3089921760161314], [29323, 0.3083522598495631], [29335, 0.30912447466871207], [29347, 0.3087319234107716], [29359, 0.3101888385024271], [29371, 0.3081167058168037], [29383, 0.3093241366446506], [29395, 0.30942228836955066], [29407, 0.3091005257761801], [29419, 0.30861387716130156], [29431, 0.3095877927549895], [29443, 0.3076274255377279], [29455, 0.30867551915788904], [29467, 0.3088365896093635], [29479, 0.308683176130655], [29551, 0.30970041996227365], [29563, 0.3090481561172878], [29575, 0.3107165908497551], [29599, 0.3094683924622065], [29611, 0.305936635676955], [29623, 0.3085966396272891], [29647, 0.30794586365754234], [29659, 0.308544375828211], [29671, 0.3100627502551094], [29743, 0.3097214116052243], [29755, 0.3072957680549575], [29767, 0.3093524815190978], [29779, 0.308467115731339], [29791, 0.3087165358293146], [29803, 0.30959454101191697], [29815, 0.3087427689517219], [29827, 0.3089346214328879], [29839, 0.31017807191266766], [29851, 0.30881399694605727], [29863, 0.31036205935602795], [29875, 0.3091089307413447], [30007, 0.3079840340133625], [30019, 0.30878622820443036], [30031, 0.31021805682624315], [30043, 0.30971283248395765], [30055, 0.30957789238590194], [30067, 0.3086130345703739], [30079, 0.3086024012048336], [30091, 0.3081012243136032], [30103, 0.30790650931523017], [30115, 0.3081144036246228], [30127, 0.3080052600652872], [30139, 0.3089728722940658], [30151, 0.3083370528109142], [30163, 0.30856915959895387], [30175, 0.3079154622622919], [30187, 0.30858725662131054], [30199, 0.3096496857858766], [30211, 0.3091269090885356], [30223, 0.30943257609580294], [30235, 0.3085540089541481], [30247, 0.3088099687722115], [30259, 0.3095901916149956], [30271, 0.30946368174422795], [30511, 0.30806861681698633], [30523, 0.3084796815044271], [30535, 0.3082027473813172], [30547, 0.3082969264730667], [30559, 0.30915808217097607], [30571, 0.30912851375542155], [30583, 0.30984459647635443], [30595, 0.3092708070860233], [30619, 0.30987413992625923], [30631, 0.3085026221460785], [30643, 0.3092364606879862], [30655, 0.3089433900347298], [30667, 0.3084020709750024], [30679, 0.3074497779700447], [30691, 0.3090519339848951], [30703, 0.30873047377772034], [30715, 0.3080454284937578], [30727, 0.30863187367385403], [30739, 0.3089051997376782], [30751, 0.30839477413593563], [30763, 0.30761009382058946], [30787, 0.30804815042440103], [30799, 0.30887764000890616], [30811, 0.3080526163552032], [30823, 0.30878156628570147], [30847, 0.3083725702896315], [30859, 0.308030298396846], [30871, 0.30820582526454], [30883, 0.31011230394076433], [30895, 0.3081307636605102], [30907, 0.30886934756747514], [30919, 0.3096492012126781], [30931, 0.30774482713057544], [30943, 0.30905339044111213], [30955, 0.3096885512657005], [30967, 0.3094042940636227], [30979, 0.30813564573840163], [30991, 0.3087535541004075], [31003, 0.30944715684202573], [31015, 0.30997246723268496], [31027, 0.30533906092640084], [31039, 0.30756890921880975], [31051, 0.30905472695595204], [32095, 0.31042410018785876], [32107, 0.30922822691926893], [32119, 0.30956617627959643], [32131, 0.3084492957334006], [32143, 0.3088108495209832], [32155, 0.3072273909170253], [32167, 0.30963695397705876], [32179, 0.3075159592064263], [32191, 0.3086966188237551], [32203, 0.30928973215607436], [32215, 0.3085625590699535], [32227, 0.30821094617025996], [32251, 0.30958928132129176], [32263, 0.30930302989855113], [32275, 0.3096032460098818], [32299, 0.30933614172518076], [32311, 0.3085312286574418], [32323, 0.3095511179191892], [32335, 0.30833300547973125], [32347, 0.30992048132555283], [32359, 0.30937261762298646], [32371, 0.30801355821781695], [32383, 0.30893978181865345], [32395, 0.30987215548262675], [32407, 0.30752575907049506], [32419, 0.30830312789832165], [32431, 0.3079541999227795], [32443, 0.30751133316455137], [32575, 0.30907854071086893], [32587, 0.3096899454296903], [32599, 0.30894922595303714], [32611, 0.3080567862033076], [32623, 0.30736639066066385], [32635, 0.3083298922396443], [32647, 0.31113268215251433], [32659, 0.3082748534984192], [32839, 0.31011960258106214], [32851, 0.3098418085486637], [32863, 0.3085713041283169], [32875, 0.30945445337997646], [32887, 0.30907552837489166], [32899, 0.3073748244059974], [32911, 0.3096082535645527], [32923, 0.30817754068807546], [32995, 0.30924361686401364], [33007, 0.30873201842536857], [33019, 0.30971936234364217], [33031, 0.31009529359630683], [33043, 0.3075504753565963], [33055, 0.306885414402024], [33067, 0.30970307058562735], [33079, 0.30674712495055734], [33091, 0.31010136465904237], [33103, 0.3089790027719438], [33115, 0.30851929670947714], [33127, 0.3104096832795697], [33139, 0.3079489694482311], [33151, 0.30968707045668425], [33187, 0.3080864015191738], [33199, 0.30860886829543777], [33211, 0.3080573952535449], [33223, 0.30828051870693907], [33235, 0.30947511264516686], [33271, 0.3090114023627249], [33307, 0.3090549870970347], [33319, 0.30831785872663636], [33331, 0.3089996788253432], [33343, 0.30964344785618225], [33355, 0.30882209653387666], [33367, 0.3091162535925723], [33379, 0.308645344547819], [33391, 0.30926110786141126], [33403, 0.30907127293745695], [33415, 0.30944019187261657], [33427, 0.30896307099742204], [33439, 0.3078336502300715], [33451, 0.3098826900946818], [33463, 0.30927340748405174], [33523, 0.3095469852213809], [33535, 0.3101827363035049], [33547, 0.3082172248296501], [33655, 0.30918608160191136], [33715, 0.30851743108234864], [33727, 0.30873991838317], [33739, 0.3089405880128217], [33763, 0.30719013301615294], [33775, 0.3075463990736112], [33811, 0.3085696241295679], [33823, 0.3087465190380327], [33835, 0.3086100262949762], [34039, 0.30979747788831], [34051, 0.3082427085403625], [34063, 0.3089788482454664], [34075, 0.3079305083906039], [34087, 0.30921249242219756], [34123, 0.3082654844031513], [34135, 0.30803763469416034], [34147, 0.30968098950610984], [34159, 0.3083512592486555], [34171, 0.3096052656009864]] \ No newline at end of file diff --git a/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit.json b/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit.json index 7dc3bf6198..c6be242133 100644 --- a/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit.json +++ b/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[29227, 96083968.0], [29239, 95742976.0], [29251, 95778133.33333333], [29263, 96043008.0], [29287, 95807488.0], [29299, 96084992.0], [29323, 95954944.0], [29335, 96120832.0], [29347, 95856640.0], [29359, 95641600.0], [29371, 95506432.0], [29383, 95794517.33333333], [29395, 95825920.0], [29407, 95821824.0], [29419, 95636138.66666667], [29431, 95924224.0], [29443, 96088064.0], [29455, 96225280.0], [29467, 96373418.66666667], [29479, 96231424.0], [29551, 96131754.66666667], [29563, 96387072.0], [29575, 95932416.0], [29599, 97447936.0], [29611, 97558528.0], [29623, 97681408.0], [29647, 97515520.0], [29659, 97644544.0], [29671, 97443840.0], [29743, 97445888.0], [29755, 97896448.0], [29767, 97439744.0], [29779, 97521664.0], [29791, 97627136.0], [29803, 97794048.0], [29815, 97859993.6], [29827, 97869824.0], [29839, 98217984.0], [29851, 98013184.0], [29863, 98025472.0], [29875, 97931264.0], [30007, 97839104.0], [30019, 97650688.0], [30031, 97646592.0], [30043, 97992704.0], [30055, 97845248.0], [30067, 97587200.0], [30079, 97885525.33333333], [30091, 97701888.0], [30103, 97533952.0], [30115, 97860266.66666667], [30127, 97899861.33333333], [30139, 97875968.0], [30151, 98238464.0], [30163, 98406400.0], [30175, 98392064.0], [30187, 98183168.0], [30199, 98331306.66666667], [30211, 98246656.0], [30223, 98225152.0], [30235, 98235733.33333333], [30247, 98409130.66666667], [30259, 98156544.0], [30271, 98232320.0], [30511, 98392473.6], [30523, 98267136.0], [30535, 98520064.0], [30547, 98694758.4], [30559, 98583893.33333333], [30571, 98772309.33333333], [30583, 98873344.0], [30595, 98988032.0], [30619, 98762752.0], [30631, 98981205.33333333], [30643, 98855594.66666667], [30655, 98710528.0], [30667, 98824192.0], [30679, 98938880.0], [30691, 98557952.0], [30703, 99229696.0], [30715, 98748416.0], [30727, 98828288.0], [30739, 98867882.66666667], [30751, 98989056.0], [30763, 99300693.33333333], [30787, 98821461.33333333], [30799, 98955264.0], [30811, 98811904.0], [30823, 98952533.33333333], [30847, 98955264.0], [30859, 99024896.0], [30871, 99135488.0], [30883, 99303424.0], [30895, 98934784.0], [30907, 99090432.0], [30919, 99060394.66666667], [30931, 98971648.0], [30943, 98908160.0], [30955, 99057664.0], [30967, 99127296.0], [30979, 99117738.66666667], [30991, 99237888.0], [31003, 99229696.0], [31015, 99012608.0], [31027, 99033088.0], [31039, 98873344.0], [31051, 99162794.66666667], [32095, 110313472.0], [32107, 110473216.0], [32119, 110575616.0], [32131, 110501888.0], [32143, 110329856.0], [32155, 109991936.0], [32167, 110243840.0], [32179, 110465024.0], [32191, 110111402.66666667], [32203, 111424853.33333333], [32215, 113256448.0], [32227, 113442816.0], [32251, 113258496.0], [32263, 113350656.0], [32275, 113291264.0], [32299, 113094656.0], [32311, 120556202.66666667], [32323, 120799232.0], [32335, 120791040.0], [32347, 120615936.0], [32359, 120434688.0], [32371, 120610816.0], [32383, 120635392.0], [32395, 120160256.0], [32407, 120233984.0], [32419, 120627200.0], [32431, 120393728.0], [32443, 120492032.0], [32575, 116588544.0], [32587, 116211712.0], [32599, 116390570.66666667], [32611, 116518912.0], [32623, 116731904.0], [32635, 116629504.0], [32647, 116469760.0], [32659, 116279296.0], [32839, 117399552.0], [32851, 117551104.0], [32863, 117398528.0], [32875, 117762730.66666667], [32887, 117530624.0], [32899, 117590016.0], [32911, 117587968.0], [32923, 117323776.0], [32995, 117841920.0], [33007, 117772288.0], [33019, 117043200.0], [33031, 117796864.0], [33043, 117553152.0], [33055, 117977088.0], [33067, 117796864.0], [33079, 118022144.0], [33091, 145600512.0], [33103, 145729536.0], [33115, 145958912.0], [33127, 145199104.0], [33139, 145731584.0], [33151, 146124800.0], [33187, 117989376.0], [33199, 117749760.0], [33211, 117669888.0], [33223, 114822506.79001874], [33235, 111843130.72559504], [33271, 106033152.0], [33307, 106653696.0], [33319, 106292224.0], [33331, 106872832.0], [33343, 106776166.4], [33355, 107032576.0], [33367, 107541845.33333333], [33379, 107499520.0], [33391, 108093440.0], [33403, 108341248.0], [33415, 108392448.0], [33427, 108359680.0], [33439, 109355008.0], [33451, 104267776.0], [33463, 104505344.0], [33523, 104538112.0], [33535, 104527872.0], [33547, 104114176.0], [33559, 103374848.0], [33655, 103505920.0], [33715, 103414784.0], [33727, 103348224.0], [33739, 103143424.0], [33763, 103247872.0], [33775, 103325696.0], [33811, 103020544.0], [33823, 102865578.66666667], [33835, 103047168.0], [34039, 103032832.0], [34051, 103245824.0], [34063, 103129088.0], [34075, 102930432.0], [34087, 103108608.0], [34123, 102951594.66666667], [34135, 103399424.0], [34147, 102827349.33333333], [34159, 102868992.0], [34171, 102887424.0]] \ No newline at end of file +[[29227, 96083968.0], [29239, 95742976.0], [29251, 95778133.33333333], [29263, 96043008.0], [29287, 95807488.0], [29299, 96084992.0], [29323, 95954944.0], [29335, 96120832.0], [29347, 95856640.0], [29359, 95641600.0], [29371, 95506432.0], [29383, 95794517.33333333], [29395, 95825920.0], [29407, 95821824.0], [29419, 95636138.66666667], [29431, 95924224.0], [29443, 96088064.0], [29455, 96225280.0], [29467, 96373418.66666667], [29479, 96231424.0], [29551, 96131754.66666667], [29563, 96387072.0], [29575, 95932416.0], [29599, 97447936.0], [29611, 97558528.0], [29623, 97681408.0], [29647, 97515520.0], [29659, 97644544.0], [29671, 97443840.0], [29743, 97445888.0], [29755, 97896448.0], [29767, 97439744.0], [29779, 97521664.0], [29791, 97627136.0], [29803, 97794048.0], [29815, 97859993.6], [29827, 97869824.0], [29839, 98217984.0], [29851, 98013184.0], [29863, 98025472.0], [29875, 97931264.0], [30007, 97839104.0], [30019, 97650688.0], [30031, 97646592.0], [30043, 97992704.0], [30055, 97845248.0], [30067, 97587200.0], [30079, 97885525.33333333], [30091, 97701888.0], [30103, 97533952.0], [30115, 97860266.66666667], [30127, 97899861.33333333], [30139, 97875968.0], [30151, 98238464.0], [30163, 98406400.0], [30175, 98392064.0], [30187, 98183168.0], [30199, 98331306.66666667], [30211, 98246656.0], [30223, 98225152.0], [30235, 98235733.33333333], [30247, 98409130.66666667], [30259, 98156544.0], [30271, 98232320.0], [30511, 98392473.6], [30523, 98267136.0], [30535, 98520064.0], [30547, 98694758.4], [30559, 98583893.33333333], [30571, 98772309.33333333], [30583, 98873344.0], [30595, 98988032.0], [30619, 98762752.0], [30631, 98981205.33333333], [30643, 98855594.66666667], [30655, 98710528.0], [30667, 98824192.0], [30679, 98938880.0], [30691, 98557952.0], [30703, 99229696.0], [30715, 98748416.0], [30727, 98828288.0], [30739, 98867882.66666667], [30751, 98989056.0], [30763, 99300693.33333333], [30787, 98821461.33333333], [30799, 98955264.0], [30811, 98811904.0], [30823, 98952533.33333333], [30847, 98955264.0], [30859, 99024896.0], [30871, 99135488.0], [30883, 99303424.0], [30895, 98934784.0], [30907, 99090432.0], [30919, 99060394.66666667], [30931, 98971648.0], [30943, 98908160.0], [30955, 99057664.0], [30967, 99127296.0], [30979, 99117738.66666667], [30991, 99237888.0], [31003, 99229696.0], [31015, 99012608.0], [31027, 99033088.0], [31039, 98873344.0], [31051, 99162794.66666667], [32095, 110313472.0], [32107, 110473216.0], [32119, 110575616.0], [32131, 110501888.0], [32143, 110329856.0], [32155, 109991936.0], [32167, 110243840.0], [32179, 110465024.0], [32191, 110111402.66666667], [32203, 111424853.33333333], [32215, 113256448.0], [32227, 113442816.0], [32251, 113258496.0], [32263, 113350656.0], [32275, 113291264.0], [32299, 113094656.0], [32311, 120556202.66666667], [32323, 120799232.0], [32335, 120791040.0], [32347, 120615936.0], [32359, 120434688.0], [32371, 120610816.0], [32383, 120635392.0], [32395, 120160256.0], [32407, 120233984.0], [32419, 120627200.0], [32431, 120393728.0], [32443, 120492032.0], [32575, 116588544.0], [32587, 116211712.0], [32599, 116390570.66666667], [32611, 116518912.0], [32623, 116731904.0], [32635, 116629504.0], [32647, 116469760.0], [32659, 116279296.0], [32839, 117399552.0], [32851, 117551104.0], [32863, 117398528.0], [32875, 117762730.66666667], [32887, 117530624.0], [32899, 117590016.0], [32911, 117587968.0], [32923, 117323776.0], [32995, 117841920.0], [33007, 117772288.0], [33019, 117043200.0], [33031, 117796864.0], [33043, 117553152.0], [33055, 117977088.0], [33067, 117796864.0], [33079, 118022144.0], [33091, 145600512.0], [33103, 145729536.0], [33115, 145958912.0], [33127, 145199104.0], [33139, 145731584.0], [33151, 146124800.0], [33187, 117989376.0], [33199, 117749760.0], [33211, 117669888.0], [33223, 114822506.79001874], [33235, 111843130.72559504], [33271, 106033152.0], [33307, 106653696.0], [33319, 106292224.0], [33331, 106872832.0], [33343, 106776166.4], [33355, 107032576.0], [33367, 107541845.33333333], [33379, 107499520.0], [33391, 108093440.0], [33403, 108341248.0], [33415, 108392448.0], [33427, 108359680.0], [33439, 109355008.0], [33451, 104267776.0], [33463, 104505344.0], [33523, 104538112.0], [33535, 104527872.0], [33547, 104114176.0], [33559, 103374848.0], [33655, 103505920.0], [33715, 103414784.0], [33727, 103348224.0], [33739, 103143424.0], [33763, 103247872.0], [33775, 103325696.0], [33811, 103020544.0], [33823, 102865578.66666667], [33835, 103047168.0], [34039, 103032832.0], [34051, 103245824.0], [34063, 103129088.0], [34075, 102930432.0], [34087, 103108608.0], [34123, 102951594.66666667], [34135, 103399424.0], [34147, 102827349.33333333], [34159, 102868992.0], [34171, 102952960.0]] \ No newline at end of file diff --git a/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json b/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json index 2b8d144582..5a08fb436a 100644 --- a/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json +++ b/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[29227, 84541440.0], [29239, 84484096.0], [29251, 84463616.0], [29263, 84584448.0], [29287, 84652032.0], [29299, 84579328.0], [29323, 84516864.0], [29335, 84605610.66666667], [29347, 84183040.0], [29359, 84058112.0], [29371, 84070400.0], [29383, 84086784.0], [29395, 84166656.0], [29407, 84017152.0], [29419, 84167338.66666667], [29431, 84405248.0], [29443, 84701184.0], [29455, 84591616.0], [29467, 84657493.33333333], [29479, 84590592.0], [29551, 84710741.33333333], [29563, 84963328.0], [29575, 84049920.0], [29599, 85815296.0], [29611, 85958656.0], [29623, 86059008.0], [29647, 86075392.0], [29659, 86018048.0], [29671, 85901312.0], [29743, 85962752.0], [29755, 85948416.0], [29767, 85895168.0], [29779, 85774336.0], [29791, 85942272.0], [29803, 86120448.0], [29815, 86030745.6], [29827, 86065152.0], [29839, 86126592.0], [29851, 86011904.0], [29863, 86032384.0], [29875, 86130688.0], [30007, 85993472.0], [30019, 85921792.0], [30031, 85956608.0], [30043, 85831680.0], [30055, 85991424.0], [30067, 85946368.0], [30079, 86071978.66666667], [30091, 86085632.0], [30103, 85950464.0], [30115, 86272682.66666667], [30127, 85994154.66666667], [30139, 86108160.0], [30151, 86163456.0], [30163, 86312277.33333333], [30175, 86398976.0], [30187, 86329344.0], [30199, 86422869.33333333], [30211, 86436522.66666667], [30223, 86392832.0], [30235, 86417408.0], [30247, 86379178.66666667], [30259, 86312960.0], [30271, 86396928.0], [30511, 86454272.0], [30523, 86413312.0], [30535, 86491136.0], [30547, 86535372.8], [30559, 86491136.0], [30571, 86560768.0], [30583, 86761472.0], [30595, 86493184.0], [30619, 86663168.0], [30631, 86638592.0], [30643, 86671360.0], [30655, 86578176.0], [30667, 86593536.0], [30679, 86650880.0], [30691, 86683648.0], [30703, 86671360.0], [30715, 86556672.0], [30727, 86675456.0], [30739, 86585344.0], [30751, 86720512.0], [30763, 86936234.66666667], [30787, 86495232.0], [30799, 86804480.0], [30811, 86794240.0], [30823, 86839296.0], [30847, 86601728.0], [30859, 86880256.0], [30871, 86708224.0], [30883, 86523904.0], [30895, 86757376.0], [30907, 86736896.0], [30919, 86799701.33333333], [30931, 86802432.0], [30943, 86753280.0], [30955, 86845440.0], [30967, 86767616.0], [30979, 86717781.33333333], [30991, 86743040.0], [31003, 86857728.0], [31015, 86720512.0], [31027, 86880256.0], [31039, 86802432.0], [31051, 86761472.0], [32095, 98570240.0], [32107, 98326528.0], [32119, 98257578.66666667], [32131, 98213888.0], [32143, 98201600.0], [32155, 98316288.0], [32167, 98309461.33333333], [32179, 98234368.0], [32191, 98231637.33333333], [32203, 99259733.33333333], [32215, 100990976.0], [32227, 101089280.0], [32251, 101105664.0], [32263, 100997120.0], [32275, 100885845.33333333], [32299, 100800512.0], [32311, 108395178.66666667], [32323, 108593152.0], [32335, 108544000.0], [32347, 108506112.0], [32359, 108568576.0], [32371, 108503040.0], [32383, 108408832.0], [32395, 108429312.0], [32407, 108298240.0], [32419, 108371968.0], [32431, 108447744.0], [32443, 108789760.0], [32575, 103768064.0], [32587, 103700480.0], [32599, 103814485.33333333], [32611, 103800832.0], [32623, 104030208.0], [32635, 103772160.0], [32647, 103878656.0], [32659, 103743488.0], [32839, 105123840.0], [32851, 105205760.0], [32863, 105169920.0], [32875, 105261738.66666667], [32887, 105291776.0], [32899, 105418752.0], [32911, 105394176.0], [32923, 105400320.0], [32995, 105639936.0], [33007, 105488384.0], [33019, 105385984.0], [33031, 105463808.0], [33043, 105525248.0], [33055, 105820160.0], [33067, 105670656.0], [33079, 105693184.0], [33091, 133545984.0], [33103, 133505024.0], [33115, 133593088.0], [33127, 133214208.0], [33139, 133505024.0], [33151, 133693440.0], [33187, 106045440.0], [33199, 105975808.0], [33211, 105895936.0], [33223, 103124272.63975424], [33235, 100223228.79437721], [33271, 94613504.0], [33307, 94406656.0], [33319, 94422016.0], [33331, 95223808.0], [33343, 95224627.2], [33355, 95520768.0], [33367, 96012970.66666667], [33379, 96258048.0], [33391, 96565248.0], [33403, 96724992.0], [33415, 96260096.0], [33427, 96530432.0], [33439, 97761280.0], [33451, 92966912.0], [33463, 93036544.0], [33523, 93100032.0], [33535, 93151232.0], [33547, 92525568.0], [33559, 91185152.0], [33655, 91811840.0], [33715, 91350016.0], [33727, 90996736.0], [33739, 91240448.0], [33763, 91480064.0], [33775, 91615232.0], [33811, 91521024.0], [33823, 91324416.0], [33835, 90961920.0], [34039, 90767360.0], [34051, 91056128.0], [34063, 91105280.0], [34075, 90775552.0], [34087, 90865664.0], [34123, 91009024.0], [34135, 91549696.0], [34147, 91015850.66666667], [34159, 91203584.0], [34171, 91037696.0]] \ No newline at end of file +[[29227, 84541440.0], [29239, 84484096.0], [29251, 84463616.0], [29263, 84584448.0], [29287, 84652032.0], [29299, 84579328.0], [29323, 84516864.0], [29335, 84605610.66666667], [29347, 84183040.0], [29359, 84058112.0], [29371, 84070400.0], [29383, 84086784.0], [29395, 84166656.0], [29407, 84017152.0], [29419, 84167338.66666667], [29431, 84405248.0], [29443, 84701184.0], [29455, 84591616.0], [29467, 84657493.33333333], [29479, 84590592.0], [29551, 84710741.33333333], [29563, 84963328.0], [29575, 84049920.0], [29599, 85815296.0], [29611, 85958656.0], [29623, 86059008.0], [29647, 86075392.0], [29659, 86018048.0], [29671, 85901312.0], [29743, 85962752.0], [29755, 85948416.0], [29767, 85895168.0], [29779, 85774336.0], [29791, 85942272.0], [29803, 86120448.0], [29815, 86030745.6], [29827, 86065152.0], [29839, 86126592.0], [29851, 86011904.0], [29863, 86032384.0], [29875, 86130688.0], [30007, 85993472.0], [30019, 85921792.0], [30031, 85956608.0], [30043, 85831680.0], [30055, 85991424.0], [30067, 85946368.0], [30079, 86071978.66666667], [30091, 86085632.0], [30103, 85950464.0], [30115, 86272682.66666667], [30127, 85994154.66666667], [30139, 86108160.0], [30151, 86163456.0], [30163, 86312277.33333333], [30175, 86398976.0], [30187, 86329344.0], [30199, 86422869.33333333], [30211, 86436522.66666667], [30223, 86392832.0], [30235, 86417408.0], [30247, 86379178.66666667], [30259, 86312960.0], [30271, 86396928.0], [30511, 86454272.0], [30523, 86413312.0], [30535, 86491136.0], [30547, 86535372.8], [30559, 86491136.0], [30571, 86560768.0], [30583, 86761472.0], [30595, 86493184.0], [30619, 86663168.0], [30631, 86638592.0], [30643, 86671360.0], [30655, 86578176.0], [30667, 86593536.0], [30679, 86650880.0], [30691, 86683648.0], [30703, 86671360.0], [30715, 86556672.0], [30727, 86675456.0], [30739, 86585344.0], [30751, 86720512.0], [30763, 86936234.66666667], [30787, 86495232.0], [30799, 86804480.0], [30811, 86794240.0], [30823, 86839296.0], [30847, 86601728.0], [30859, 86880256.0], [30871, 86708224.0], [30883, 86523904.0], [30895, 86757376.0], [30907, 86736896.0], [30919, 86799701.33333333], [30931, 86802432.0], [30943, 86753280.0], [30955, 86845440.0], [30967, 86767616.0], [30979, 86717781.33333333], [30991, 86743040.0], [31003, 86857728.0], [31015, 86720512.0], [31027, 86880256.0], [31039, 86802432.0], [31051, 86761472.0], [32095, 98570240.0], [32107, 98326528.0], [32119, 98257578.66666667], [32131, 98213888.0], [32143, 98201600.0], [32155, 98316288.0], [32167, 98309461.33333333], [32179, 98234368.0], [32191, 98231637.33333333], [32203, 99259733.33333333], [32215, 100990976.0], [32227, 101089280.0], [32251, 101105664.0], [32263, 100997120.0], [32275, 100885845.33333333], [32299, 100800512.0], [32311, 108395178.66666667], [32323, 108593152.0], [32335, 108544000.0], [32347, 108506112.0], [32359, 108568576.0], [32371, 108503040.0], [32383, 108408832.0], [32395, 108429312.0], [32407, 108298240.0], [32419, 108371968.0], [32431, 108447744.0], [32443, 108789760.0], [32575, 103768064.0], [32587, 103700480.0], [32599, 103814485.33333333], [32611, 103800832.0], [32623, 104030208.0], [32635, 103772160.0], [32647, 103878656.0], [32659, 103743488.0], [32839, 105123840.0], [32851, 105205760.0], [32863, 105169920.0], [32875, 105261738.66666667], [32887, 105291776.0], [32899, 105418752.0], [32911, 105394176.0], [32923, 105400320.0], [32995, 105639936.0], [33007, 105488384.0], [33019, 105385984.0], [33031, 105463808.0], [33043, 105525248.0], [33055, 105820160.0], [33067, 105670656.0], [33079, 105693184.0], [33091, 133545984.0], [33103, 133505024.0], [33115, 133593088.0], [33127, 133214208.0], [33139, 133505024.0], [33151, 133693440.0], [33187, 106045440.0], [33199, 105975808.0], [33211, 105895936.0], [33223, 103124272.63975424], [33235, 100223228.79437721], [33271, 94613504.0], [33307, 94406656.0], [33319, 94422016.0], [33331, 95223808.0], [33343, 95224627.2], [33355, 95520768.0], [33367, 96012970.66666667], [33379, 96258048.0], [33391, 96565248.0], [33403, 96724992.0], [33415, 96260096.0], [33427, 96530432.0], [33439, 97761280.0], [33451, 92966912.0], [33463, 93036544.0], [33523, 93100032.0], [33535, 93151232.0], [33547, 92525568.0], [33559, 91185152.0], [33655, 91811840.0], [33715, 91350016.0], [33727, 90996736.0], [33739, 91240448.0], [33763, 91480064.0], [33775, 91615232.0], [33811, 91521024.0], [33823, 91324416.0], [33835, 90961920.0], [34039, 90767360.0], [34051, 91056128.0], [34063, 91105280.0], [34075, 90775552.0], [34087, 90865664.0], [34123, 91009024.0], [34135, 91549696.0], [34147, 91015850.66666667], [34159, 91203584.0], [34171, 91074560.0]] \ No newline at end of file diff --git a/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json b/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json index b3208d5396..c09795e6b8 100644 --- a/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json +++ b/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json @@ -1 +1 @@ -[[29227, 2.805772871749923], [29239, 2.500591247624982], [29251, 1.857432272000248], [29263, 2.3231093559998044], [29287, 1.899330317250019], [29299, 1.81994013162506], [29323, 1.898525102500173], [29335, 2.0916008958333805], [29347, 2.078245873500009], [29359, 1.997273060000225], [29371, 1.7358767470000203], [29383, 1.9855079254999357], [29395, 2.2578154869999025], [29407, 2.1493857859998116], [29419, 1.9928887180000554], [29431, 2.1213746512500506], [29443, 2.959825056499767], [29455, 2.770559848374944], [29467, 2.89086585066669], [29479, 3.0236403859998973], [29551, 2.851432538666662], [29563, 2.267983565999657], [29575, 2.112279185000034], [29599, 2.135125255500043], [29611, 2.282446623999931], [29623, 2.125808891749898], [29647, 2.1228297692498472], [29659, 2.144176786749938], [29671, 2.130070903666592], [29743, 2.119067451250089], [29755, 2.121084961999941], [29767, 2.1489944016248614], [29779, 2.5393461792499465], [29791, 2.5877961077499663], [29803, 2.657043445000113], [29815, 2.6687083438000627], [29827, 2.5898222310001984], [29839, 2.5488236189999043], [29851, 2.837094992999937], [29863, 2.732304729999896], [29875, 2.758576574999779], [30007, 2.8596658737499183], [30019, 2.5101024932500877], [30031, 2.7725498370000423], [30043, 2.5070394909998868], [30055, 2.779021898999872], [30067, 2.4972384580000835], [30079, 2.6350451887499653], [30091, 2.6287231432499993], [30103, 2.5857450469998184], [30115, 2.6346069810000095], [30127, 2.636227595166853], [30139, 2.628798012750053], [30151, 2.773440368499905], [30163, 2.64008272133348], [30175, 2.778742310250209], [30187, 2.6515299597499506], [30199, 2.7769998923331514], [30211, 2.6498885603334656], [30223, 3.1147083325000153], [30235, 2.7244635654999456], [30247, 2.6348943371666187], [30259, 2.710803470999963], [30271, 2.548781761999976], [30511, 2.6255832962999195], [30523, 2.778408638666709], [30535, 2.5795824958750018], [30547, 2.7693268699999862], [30559, 2.624900456500048], [30571, 2.59205152833321], [30583, 2.5395939794998412], [30595, 2.7498109020000356], [30619, 2.762629972500008], [30631, 2.6756491005000194], [30643, 2.5003402326667583], [30655, 2.6633571859999847], [30667, 2.674203057500108], [30679, 2.946277230499959], [30691, 3.0130011114997615], [30703, 2.968732391499998], [30715, 2.7517907842500335], [30727, 2.901128955000104], [30739, 2.839026390166661], [30751, 2.5816157208751065], [30763, 2.5494549690001804], [30787, 2.675820736999943], [30799, 2.6933119622501636], [30811, 2.484915565999927], [30823, 2.536536536333339], [30847, 2.5668226300001606], [30859, 2.7439930339999137], [30871, 2.6900918259998434], [30883, 2.963036656999975], [30895, 2.498414428500155], [30907, 2.4731235710000874], [30919, 2.6087383219999083], [30931, 2.8630827409997437], [30943, 2.8582021029997122], [30955, 2.4974060394999924], [30967, 2.627690617999974], [30979, 2.64024848099992], [30991, 2.6202146800001174], [31003, 2.770087406499897], [31015, 2.589232544999959], [31027, 2.7065683249998074], [31039, 2.6831397770001786], [31051, 2.80007214050003], [32095, 2.509312826500036], [32107, 2.59182214749967], [32119, 2.610799769333122], [32131, 2.541561759500155], [32143, 2.65391648766672], [32155, 2.5297070685001017], [32167, 2.5719254446667037], [32179, 2.5283617330001107], [32191, 2.495063023166722], [32203, 2.544558276999927], [32215, 2.5056368087500687], [32227, 2.54607439666673], [32251, 2.679672331750112], [32263, 2.7636226105000787], [32275, 2.5168063446667475], [32299, 2.934056076500042], [32311, 2.871573464833394], [32323, 2.9017834414999015], [32335, 2.4717463269998916], [32347, 2.6085491863751713], [32359, 2.6375318353749435], [32371, 2.423161405000201], [32383, 3.0665921654999693], [32395, 2.928145442499954], [32407, 2.556639020000148], [32419, 2.987914743333325], [32431, 2.7362072977499565], [32443, 2.4773652190001485], [32575, 2.9527343940001174], [32587, 2.3008119354999508], [32599, 2.436630871000034], [32611, 2.7056859370000743], [32623, 2.6661874599999464], [32635, 2.5767248039996957], [32647, 2.7172770417499805], [32659, 2.819266969749947], [32839, 2.499879508500271], [32851, 2.400960689000044], [32863, 2.51029130250015], [32875, 2.472524025499903], [32887, 2.570100256999922], [32899, 2.4810781157500514], [32911, 2.4356431979999797], [32923, 2.5685488947500517], [32995, 2.452688290500191], [33007, 2.4885175080000863], [33019, 2.541104666999672], [33031, 2.544604488999994], [33043, 2.525842519250091], [33055, 2.478869933999931], [33067, 2.441795654749967], [33079, 2.5376858690001427], [33091, 2.5996044204998725], [33103, 2.471596749499895], [33115, 2.459947284750001], [33127, 2.608855559999938], [33139, 2.5710624724997615], [33151, 2.4848507629999403], [33187, 2.4512263620001704], [33199, 2.537973377500066], [33211, 2.4624082602498447], [33223, 2.464537143535388], [33235, 2.4828536422956318], [33271, 2.4198066745000233], [33307, 2.598065545499935], [33319, 2.3938211136251084], [33331, 2.5026904650003416], [33343, 2.4486033210999265], [33355, 2.4335455979999097], [33367, 2.282124225666621], [33379, 2.478237326249996], [33391, 2.427195066249965], [33403, 2.5179501499999333], [33415, 2.356803169999921], [33427, 2.5141646129995934], [33439, 2.319428334999884], [33451, 2.3278170779999527], [33463, 2.3605796709998685], [33523, 2.411371966874981], [33535, 2.4350792929999443], [33547, 2.36448406237497], [33559, 7.890795514000047], [33655, 7.7430761660002645], [33715, 8.100066507250062], [33727, 4.8064797437499465], [33739, 2.3813147445000595], [33763, 2.6505002989997593], [33775, 2.480448654999691], [33811, 2.341179932250043], [33823, 2.480333880333243], [33835, 2.499099964000152], [34039, 7.028721260999987], [34051, 7.20382646125006], [34063, 7.650581479250036], [34075, 7.099670288000084], [34087, 7.508945953999955], [34123, 2.43643154299995], [34135, 2.401516767999965], [34147, 2.424505824666691], [34159, 2.38994140300008], [34171, 2.403539215500018]] \ No newline at end of file +[[29227, 2.805772871749923], [29239, 2.500591247624982], [29251, 1.857432272000248], [29263, 2.3231093559998044], [29287, 1.899330317250019], [29299, 1.81994013162506], [29323, 1.898525102500173], [29335, 2.0916008958333805], [29347, 2.078245873500009], [29359, 1.997273060000225], [29371, 1.7358767470000203], [29383, 1.9855079254999357], [29395, 2.2578154869999025], [29407, 2.1493857859998116], [29419, 1.9928887180000554], [29431, 2.1213746512500506], [29443, 2.959825056499767], [29455, 2.770559848374944], [29467, 2.89086585066669], [29479, 3.0236403859998973], [29551, 2.851432538666662], [29563, 2.267983565999657], [29575, 2.112279185000034], [29599, 2.135125255500043], [29611, 2.282446623999931], [29623, 2.125808891749898], [29647, 2.1228297692498472], [29659, 2.144176786749938], [29671, 2.130070903666592], [29743, 2.119067451250089], [29755, 2.121084961999941], [29767, 2.1489944016248614], [29779, 2.5393461792499465], [29791, 2.5877961077499663], [29803, 2.657043445000113], [29815, 2.6687083438000627], [29827, 2.5898222310001984], [29839, 2.5488236189999043], [29851, 2.837094992999937], [29863, 2.732304729999896], [29875, 2.758576574999779], [30007, 2.8596658737499183], [30019, 2.5101024932500877], [30031, 2.7725498370000423], [30043, 2.5070394909998868], [30055, 2.779021898999872], [30067, 2.4972384580000835], [30079, 2.6350451887499653], [30091, 2.6287231432499993], [30103, 2.5857450469998184], [30115, 2.6346069810000095], [30127, 2.636227595166853], [30139, 2.628798012750053], [30151, 2.773440368499905], [30163, 2.64008272133348], [30175, 2.778742310250209], [30187, 2.6515299597499506], [30199, 2.7769998923331514], [30211, 2.6498885603334656], [30223, 3.1147083325000153], [30235, 2.7244635654999456], [30247, 2.6348943371666187], [30259, 2.710803470999963], [30271, 2.548781761999976], [30511, 2.6255832962999195], [30523, 2.778408638666709], [30535, 2.5795824958750018], [30547, 2.7693268699999862], [30559, 2.624900456500048], [30571, 2.59205152833321], [30583, 2.5395939794998412], [30595, 2.7498109020000356], [30619, 2.762629972500008], [30631, 2.6756491005000194], [30643, 2.5003402326667583], [30655, 2.6633571859999847], [30667, 2.674203057500108], [30679, 2.946277230499959], [30691, 3.0130011114997615], [30703, 2.968732391499998], [30715, 2.7517907842500335], [30727, 2.901128955000104], [30739, 2.839026390166661], [30751, 2.5816157208751065], [30763, 2.5494549690001804], [30787, 2.675820736999943], [30799, 2.6933119622501636], [30811, 2.484915565999927], [30823, 2.536536536333339], [30847, 2.5668226300001606], [30859, 2.7439930339999137], [30871, 2.6900918259998434], [30883, 2.963036656999975], [30895, 2.498414428500155], [30907, 2.4731235710000874], [30919, 2.6087383219999083], [30931, 2.8630827409997437], [30943, 2.8582021029997122], [30955, 2.4974060394999924], [30967, 2.627690617999974], [30979, 2.64024848099992], [30991, 2.6202146800001174], [31003, 2.770087406499897], [31015, 2.589232544999959], [31027, 2.7065683249998074], [31039, 2.6831397770001786], [31051, 2.80007214050003], [32095, 2.509312826500036], [32107, 2.59182214749967], [32119, 2.610799769333122], [32131, 2.541561759500155], [32143, 2.65391648766672], [32155, 2.5297070685001017], [32167, 2.5719254446667037], [32179, 2.5283617330001107], [32191, 2.495063023166722], [32203, 2.544558276999927], [32215, 2.5056368087500687], [32227, 2.54607439666673], [32251, 2.679672331750112], [32263, 2.7636226105000787], [32275, 2.5168063446667475], [32299, 2.934056076500042], [32311, 2.871573464833394], [32323, 2.9017834414999015], [32335, 2.4717463269998916], [32347, 2.6085491863751713], [32359, 2.6375318353749435], [32371, 2.423161405000201], [32383, 3.0665921654999693], [32395, 2.928145442499954], [32407, 2.556639020000148], [32419, 2.987914743333325], [32431, 2.7362072977499565], [32443, 2.4773652190001485], [32575, 2.9527343940001174], [32587, 2.3008119354999508], [32599, 2.436630871000034], [32611, 2.7056859370000743], [32623, 2.6661874599999464], [32635, 2.5767248039996957], [32647, 2.7172770417499805], [32659, 2.819266969749947], [32839, 2.499879508500271], [32851, 2.400960689000044], [32863, 2.51029130250015], [32875, 2.472524025499903], [32887, 2.570100256999922], [32899, 2.4810781157500514], [32911, 2.4356431979999797], [32923, 2.5685488947500517], [32995, 2.452688290500191], [33007, 2.4885175080000863], [33019, 2.541104666999672], [33031, 2.544604488999994], [33043, 2.525842519250091], [33055, 2.478869933999931], [33067, 2.441795654749967], [33079, 2.5376858690001427], [33091, 2.5996044204998725], [33103, 2.471596749499895], [33115, 2.459947284750001], [33127, 2.608855559999938], [33139, 2.5710624724997615], [33151, 2.4848507629999403], [33187, 2.4512263620001704], [33199, 2.537973377500066], [33211, 2.4624082602498447], [33223, 2.464537143535388], [33235, 2.4828536422956318], [33271, 2.4198066745000233], [33307, 2.598065545499935], [33319, 2.3938211136251084], [33331, 2.5026904650003416], [33343, 2.4486033210999265], [33355, 2.4335455979999097], [33367, 2.282124225666621], [33379, 2.478237326249996], [33391, 2.427195066249965], [33403, 2.5179501499999333], [33415, 2.356803169999921], [33427, 2.5141646129995934], [33439, 2.319428334999884], [33451, 2.3278170779999527], [33463, 2.3605796709998685], [33523, 2.411371966874981], [33535, 2.4350792929999443], [33547, 2.36448406237497], [33559, 7.890795514000047], [33655, 7.7430761660002645], [33715, 8.100066507250062], [33727, 4.8064797437499465], [33739, 2.3813147445000595], [33763, 2.6505002989997593], [33775, 2.480448654999691], [33811, 2.341179932250043], [33823, 2.480333880333243], [33835, 2.499099964000152], [34039, 7.028721260999987], [34051, 7.20382646125006], [34063, 7.650581479250036], [34075, 7.099670288000084], [34087, 7.508945953999955], [34123, 2.43643154299995], [34135, 2.401516767999965], [34147, 2.424505824666691], [34159, 2.38994140300008], [34171, 2.4044065956666145]] \ No newline at end of file diff --git a/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.time_predict.json b/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.time_predict.json index 5dd154362a..51a894e813 100644 --- a/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.time_predict.json +++ b/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.time_predict.json @@ -1 +1 @@ -[[29227, 0.09478870425016339], [29239, 0.0976536071249825], [29251, 0.0826927361666397], [29263, 0.08277377475008052], [29287, 0.07348355525016359], [29299, 0.07721154850003131], [29323, 0.08158954224995796], [29335, 0.07873750950003948], [29347, 0.08189096399996743], [29359, 0.0825261055001647], [29371, 0.08130026349999753], [29383, 0.08263014533334474], [29395, 0.08280527249985425], [29407, 0.08185438199996042], [29419, 0.07803645250002471], [29431, 0.078104508000024], [29443, 0.09107633400003579], [29455, 0.1068374473750282], [29467, 0.09877301966669923], [29479, 0.10268417699990096], [29551, 0.10988462966671857], [29563, 0.08671401499987041], [29575, 0.08106368300013855], [29599, 0.08373336449994895], [29611, 0.08726142999989861], [29623, 0.08311004350014173], [29647, 0.0830284952501188], [29659, 0.08324847187492423], [29671, 0.08334030699991975], [29743, 0.08347652250006377], [29755, 0.08336472475014034], [29767, 0.08372406962502055], [29779, 0.09050625449992822], [29791, 0.09432888262512051], [29803, 0.09193730274989775], [29815, 0.09371881849992861], [29827, 0.09433644199975788], [29839, 0.09587161549984557], [29851, 0.10380746675002683], [29863, 0.09145573150021846], [29875, 0.09528725950008265], [30007, 0.09640336850009135], [30019, 0.097825131499917], [30031, 0.09267724599999383], [30043, 0.09208397099996546], [30055, 0.09309591624992208], [30067, 0.09199744000011378], [30079, 0.09334699483334437], [30091, 0.09283687849995204], [30103, 0.09182261800015112], [30115, 0.09739284316674457], [30127, 0.09477923099999923], [30139, 0.0935723580001877], [30151, 0.0974714460000996], [30163, 0.09138864416672732], [30175, 0.09465969174993916], [30187, 0.09281458824978017], [30199, 0.09117422850007036], [30211, 0.10826790283325256], [30223, 0.09522084075007342], [30235, 0.09344945233328872], [30247, 0.09067090350004037], [30259, 0.10065457625000818], [30271, 0.09655862024999351], [30511, 0.0997677438998835], [30523, 0.09533522133354684], [30535, 0.09207715900009816], [30547, 0.09342887880002308], [30559, 0.09276900466670668], [30571, 0.09617912983352046], [30583, 0.09640437200005181], [30595, 0.09014292074994046], [30619, 0.110781227499956], [30631, 0.09089894716665488], [30643, 0.09192636533331704], [30655, 0.09890133062509676], [30667, 0.10501632074999634], [30679, 0.09446970750013861], [30691, 0.11135853550013053], [30703, 0.09078166650010644], [30715, 0.09512494049999987], [30727, 0.09192834750012935], [30739, 0.09946921983328139], [30751, 0.09155261637505419], [30763, 0.09450930166652445], [30787, 0.09790173216651965], [30799, 0.09083087850001448], [30811, 0.0917437415000677], [30823, 0.09389209150003808], [30847, 0.09546117849981783], [30859, 0.09319823499981794], [30871, 0.09140120899996873], [30883, 0.09432979049984169], [30895, 0.09213016599983348], [30907, 0.09216864250015533], [30919, 0.09320182216667187], [30931, 0.09485913899993648], [30943, 0.09505563649997839], [30955, 0.08962124000004223], [30967, 0.10064569550002034], [30979, 0.09619561566667774], [30991, 0.09430367750007917], [31003, 0.09137942274992383], [31015, 0.09175175149994175], [31027, 0.09492966049992901], [31039, 0.08900525700005346], [31051, 0.0937612643333523], [32095, 0.09048753699971712], [32107, 0.0915679805000309], [32119, 0.09185263483330648], [32131, 0.09036425524993774], [32143, 0.09473522249997283], [32155, 0.09162258024991843], [32167, 0.09095867950001472], [32179, 0.09249031499984994], [32191, 0.09110554383323688], [32203, 0.08817283949997545], [32215, 0.08847211675004019], [32227, 0.0877971103332887], [32251, 0.08835845925011654], [32263, 0.09492718474996309], [32275, 0.08941206199991332], [32299, 0.09231115225009034], [32311, 0.09261046500008281], [32323, 0.09185070449984778], [32335, 0.10118569999985993], [32347, 0.08764631762488762], [32359, 0.0929397823748559], [32371, 0.08718239600011657], [32383, 0.09577848550020462], [32395, 0.087883113000089], [32407, 0.08858560200019383], [32419, 0.09329585766666544], [32431, 0.09057865049999236], [32443, 0.08566393799992511], [32575, 0.08455698949978796], [32587, 0.0858711170000106], [32599, 0.10649530750000243], [32611, 0.08984982500010119], [32623, 0.10147732999985237], [32635, 0.08808923600008711], [32647, 0.09011498600000323], [32659, 0.11431768199986436], [32839, 0.0878089010000167], [32851, 0.08642941350001365], [32863, 0.0880192502500563], [32875, 0.08633472550013721], [32887, 0.08778675200005637], [32899, 0.08761860124991472], [32911, 0.08658486900003481], [32923, 0.08894351199990069], [32995, 0.08867423900005633], [33007, 0.08592099949964904], [33019, 0.0850065714998891], [33031, 0.08765888250013631], [33043, 0.08765605649989539], [33055, 0.08866874899990762], [33067, 0.0856680602501001], [33079, 0.0860746470000322], [33091, 0.08838329225000052], [33103, 0.08641928599990933], [33115, 0.08615335774993582], [33127, 0.08738894049997725], [33139, 0.08871444699991571], [33151, 0.08670004149985289], [33187, 0.08504686100013714], [33199, 0.08892486549996192], [33211, 0.0879570062501216], [33223, 0.08759751076065658], [33235, 0.08821282805286683], [33271, 0.08962119300008453], [33307, 0.09027793375003057], [33319, 0.08790172262513352], [33331, 0.08300136999991992], [33343, 0.0848814473999937], [33355, 0.09372771475000263], [33367, 0.08851851099999901], [33379, 0.0829164652501504], [33391, 0.08813480349999736], [33403, 0.0861969262501816], [33415, 0.08311812050010303], [33427, 0.08733272599965858], [33439, 0.08876306250010657], [33451, 0.09251093650027542], [33463, 0.08699970749989916], [33523, 0.08587819100000615], [33535, 0.08579460149996976], [33547, 0.08519359162499995], [33559, 0.08953946350004571], [33655, 0.08784932899993692], [33715, 0.08692710437497908], [33727, 0.08859231750000163], [33739, 0.08589995074999024], [33763, 0.08989900650021809], [33775, 0.09385356250004406], [33811, 0.08388549750009133], [33823, 0.08908139049988979], [33835, 0.0890069412498633], [34039, 0.08573835075003444], [34051, 0.08599484324997775], [34063, 0.08724508925013197], [34075, 0.08733451500006595], [34087, 0.09194643450007334], [34123, 0.08717030716661611], [34135, 0.08663618550008323], [34147, 0.0842736249999992], [34159, 0.08587825999995857], [34171, 0.08380639699987569]] \ No newline at end of file +[[29227, 0.09478870425016339], [29239, 0.0976536071249825], [29251, 0.0826927361666397], [29263, 0.08277377475008052], [29287, 0.07348355525016359], [29299, 0.07721154850003131], [29323, 0.08158954224995796], [29335, 0.07873750950003948], [29347, 0.08189096399996743], [29359, 0.0825261055001647], [29371, 0.08130026349999753], [29383, 0.08263014533334474], [29395, 0.08280527249985425], [29407, 0.08185438199996042], [29419, 0.07803645250002471], [29431, 0.078104508000024], [29443, 0.09107633400003579], [29455, 0.1068374473750282], [29467, 0.09877301966669923], [29479, 0.10268417699990096], [29551, 0.10988462966671857], [29563, 0.08671401499987041], [29575, 0.08106368300013855], [29599, 0.08373336449994895], [29611, 0.08726142999989861], [29623, 0.08311004350014173], [29647, 0.0830284952501188], [29659, 0.08324847187492423], [29671, 0.08334030699991975], [29743, 0.08347652250006377], [29755, 0.08336472475014034], [29767, 0.08372406962502055], [29779, 0.09050625449992822], [29791, 0.09432888262512051], [29803, 0.09193730274989775], [29815, 0.09371881849992861], [29827, 0.09433644199975788], [29839, 0.09587161549984557], [29851, 0.10380746675002683], [29863, 0.09145573150021846], [29875, 0.09528725950008265], [30007, 0.09640336850009135], [30019, 0.097825131499917], [30031, 0.09267724599999383], [30043, 0.09208397099996546], [30055, 0.09309591624992208], [30067, 0.09199744000011378], [30079, 0.09334699483334437], [30091, 0.09283687849995204], [30103, 0.09182261800015112], [30115, 0.09739284316674457], [30127, 0.09477923099999923], [30139, 0.0935723580001877], [30151, 0.0974714460000996], [30163, 0.09138864416672732], [30175, 0.09465969174993916], [30187, 0.09281458824978017], [30199, 0.09117422850007036], [30211, 0.10826790283325256], [30223, 0.09522084075007342], [30235, 0.09344945233328872], [30247, 0.09067090350004037], [30259, 0.10065457625000818], [30271, 0.09655862024999351], [30511, 0.0997677438998835], [30523, 0.09533522133354684], [30535, 0.09207715900009816], [30547, 0.09342887880002308], [30559, 0.09276900466670668], [30571, 0.09617912983352046], [30583, 0.09640437200005181], [30595, 0.09014292074994046], [30619, 0.110781227499956], [30631, 0.09089894716665488], [30643, 0.09192636533331704], [30655, 0.09890133062509676], [30667, 0.10501632074999634], [30679, 0.09446970750013861], [30691, 0.11135853550013053], [30703, 0.09078166650010644], [30715, 0.09512494049999987], [30727, 0.09192834750012935], [30739, 0.09946921983328139], [30751, 0.09155261637505419], [30763, 0.09450930166652445], [30787, 0.09790173216651965], [30799, 0.09083087850001448], [30811, 0.0917437415000677], [30823, 0.09389209150003808], [30847, 0.09546117849981783], [30859, 0.09319823499981794], [30871, 0.09140120899996873], [30883, 0.09432979049984169], [30895, 0.09213016599983348], [30907, 0.09216864250015533], [30919, 0.09320182216667187], [30931, 0.09485913899993648], [30943, 0.09505563649997839], [30955, 0.08962124000004223], [30967, 0.10064569550002034], [30979, 0.09619561566667774], [30991, 0.09430367750007917], [31003, 0.09137942274992383], [31015, 0.09175175149994175], [31027, 0.09492966049992901], [31039, 0.08900525700005346], [31051, 0.0937612643333523], [32095, 0.09048753699971712], [32107, 0.0915679805000309], [32119, 0.09185263483330648], [32131, 0.09036425524993774], [32143, 0.09473522249997283], [32155, 0.09162258024991843], [32167, 0.09095867950001472], [32179, 0.09249031499984994], [32191, 0.09110554383323688], [32203, 0.08817283949997545], [32215, 0.08847211675004019], [32227, 0.0877971103332887], [32251, 0.08835845925011654], [32263, 0.09492718474996309], [32275, 0.08941206199991332], [32299, 0.09231115225009034], [32311, 0.09261046500008281], [32323, 0.09185070449984778], [32335, 0.10118569999985993], [32347, 0.08764631762488762], [32359, 0.0929397823748559], [32371, 0.08718239600011657], [32383, 0.09577848550020462], [32395, 0.087883113000089], [32407, 0.08858560200019383], [32419, 0.09329585766666544], [32431, 0.09057865049999236], [32443, 0.08566393799992511], [32575, 0.08455698949978796], [32587, 0.0858711170000106], [32599, 0.10649530750000243], [32611, 0.08984982500010119], [32623, 0.10147732999985237], [32635, 0.08808923600008711], [32647, 0.09011498600000323], [32659, 0.11431768199986436], [32839, 0.0878089010000167], [32851, 0.08642941350001365], [32863, 0.0880192502500563], [32875, 0.08633472550013721], [32887, 0.08778675200005637], [32899, 0.08761860124991472], [32911, 0.08658486900003481], [32923, 0.08894351199990069], [32995, 0.08867423900005633], [33007, 0.08592099949964904], [33019, 0.0850065714998891], [33031, 0.08765888250013631], [33043, 0.08765605649989539], [33055, 0.08866874899990762], [33067, 0.0856680602501001], [33079, 0.0860746470000322], [33091, 0.08838329225000052], [33103, 0.08641928599990933], [33115, 0.08615335774993582], [33127, 0.08738894049997725], [33139, 0.08871444699991571], [33151, 0.08670004149985289], [33187, 0.08504686100013714], [33199, 0.08892486549996192], [33211, 0.0879570062501216], [33223, 0.08759751076065658], [33235, 0.08821282805286683], [33271, 0.08962119300008453], [33307, 0.09027793375003057], [33319, 0.08790172262513352], [33331, 0.08300136999991992], [33343, 0.0848814473999937], [33355, 0.09372771475000263], [33367, 0.08851851099999901], [33379, 0.0829164652501504], [33391, 0.08813480349999736], [33403, 0.0861969262501816], [33415, 0.08311812050010303], [33427, 0.08733272599965858], [33439, 0.08876306250010657], [33451, 0.09251093650027542], [33463, 0.08699970749989916], [33523, 0.08587819100000615], [33535, 0.08579460149996976], [33547, 0.08519359162499995], [33559, 0.08953946350004571], [33655, 0.08784932899993692], [33715, 0.08692710437497908], [33727, 0.08859231750000163], [33739, 0.08589995074999024], [33763, 0.08989900650021809], [33775, 0.09385356250004406], [33811, 0.08388549750009133], [33823, 0.08908139049988979], [33835, 0.0890069412498633], [34039, 0.08573835075003444], [34051, 0.08599484324997775], [34063, 0.08724508925013197], [34075, 0.08733451500006595], [34087, 0.09194643450007334], [34123, 0.08717030716661611], [34135, 0.08663618550008323], [34147, 0.0842736249999992], [34159, 0.08587825999995857], [34171, 0.08407545366655238]] \ No newline at end of file diff --git a/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.track_train_score.json b/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.track_train_score.json index 2f716a3915..488e837bb6 100644 --- a/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.track_train_score.json +++ b/graphs/summary/ensemble.HistGradientBoostingClassifierBenchmark.track_train_score.json @@ -1 +1 @@ -[[29227, 0.9812160155622751], [29239, 0.9812160155622751], [29251, 0.9812160155622752], [29263, 0.9812160155622751], [29287, 0.9812160155622751], [29299, 0.9812160155622751], [29323, 0.9812160155622751], [29335, 0.9812160155622752], [29347, 0.9812160155622751], [29359, 0.9812160155622751], [29371, 0.9812160155622751], [29383, 0.9812160155622752], [29395, 0.9812160155622751], [29407, 0.9812160155622751], [29419, 0.9812160155622752], [29431, 0.9812160155622751], [29443, 0.9812160155622751], [29455, 0.9812160155622751], [29467, 0.9812160155622752], [29479, 0.9812160155622751], [29551, 0.9812160155622752], [29563, 0.9812160155622751], [29575, 0.9812160155622751], [29599, 0.9812160155622751], [29611, 0.9812160155622751], [29623, 0.9812160155622751], [29647, 0.9812160155622751], [29659, 0.9812160155622751], [29671, 0.9812160155622752], [29743, 0.9812160155622751], [29755, 0.9812160155622751], [29767, 0.9812160155622751], [29779, 0.9812160155622751], [29791, 0.9812160155622751], [29803, 0.9812160155622751], [29815, 0.9812160155622751], [29827, 0.9812160155622751], [29839, 0.9812160155622751], [29851, 0.9812160155622751], [29863, 0.9812160155622751], [29875, 0.9812160155622751], [30007, 0.9812160155622751], [30019, 0.9812160155622751], [30031, 0.9812160155622751], [30043, 0.9812160155622751], [30055, 0.9812160155622751], [30067, 0.9812160155622751], [30079, 0.981216015562275], [30091, 0.9812160155622751], [30103, 0.9812160155622751], [30115, 0.9812160155622752], [30127, 0.9812160155622752], [30139, 0.9812160155622751], [30151, 0.9812160155622751], [30163, 0.9812160155622752], [30175, 0.9812160155622751], [30187, 0.9812160155622751], [30199, 0.9812160155622752], [30211, 0.9812160155622752], [30223, 0.9812160155622751], [30235, 0.9812160155622752], [30247, 0.9812160155622752], [30259, 0.9812160155622751], [30271, 0.9812160155622751], [30511, 0.9812160155622751], [30523, 0.9812160155622752], [30535, 0.9812160155622751], [30547, 0.9812160155622751], [30559, 0.9812160155622752], [30571, 0.9812160155622752], [30583, 0.9812160155622751], [30595, 0.9812160155622751], [30619, 0.9812160155622751], [30631, 0.9812160155622752], [30643, 0.9812160155622752], [30655, 0.9812160155622751], [30667, 0.9812160155622751], [30679, 0.9812160155622751], [30691, 0.9812160155622751], [30703, 0.9812160155622751], [30715, 0.9812160155622751], [30727, 0.9812160155622751], [30739, 0.9812160155622752], [30751, 0.9812160155622751], [30763, 0.9812160155622752], [30787, 0.9812160155622752], [30799, 0.9812160155622751], [30811, 0.9812160155622751], [30823, 0.9812160155622752], [30847, 0.9812160155622751], [30859, 0.9812160155622751], [30871, 0.9812160155622751], [30883, 0.9812160155622751], [30895, 0.9812160155622751], [30907, 0.9812160155622751], [30919, 0.9812160155622752], [30931, 0.9812160155622751], [30943, 0.9812160155622751], [30955, 0.9812160155622751], [30967, 0.9812160155622751], [30979, 0.9812160155622752], [30991, 0.9812160155622751], [31003, 0.9812160155622751], [31015, 0.9812160155622751], [31027, 0.9812160155622751], [31039, 0.9812160155622751], [31051, 0.9812160155622752], [32095, 0.9812160155622751], [32107, 0.9812160155622751], [32119, 0.9812160155622752], [32131, 0.9812160155622751], [32143, 0.9812160155622752], [32155, 0.9812160155622751], [32167, 0.9812160155622752], [32179, 0.9812160155622751], [32191, 0.9812160155622752], [32203, 0.9812160155622752], [32215, 0.9812160155622751], [32227, 0.9812160155622752], [32251, 0.9812160155622751], [32263, 0.9812160155622751], [32275, 0.9812160155622752], [32299, 0.9812160155622751], [32311, 0.9812160155622752], [32323, 0.9812160155622751], [32335, 0.9812160155622751], [32347, 0.9812160155622751], [32359, 0.9812160155622751], [32371, 0.9812160155622751], [32383, 0.9812160155622751], [32395, 0.9812160155622751], [32407, 0.9812160155622751], [32419, 0.9812160155622752], [32431, 0.9812160155622751], [32443, 0.9812160155622751], [32575, 0.9812160155622751], [32587, 0.9812160155622751], [32599, 0.9812160155622752], [32611, 0.9812160155622752], [32623, 0.9812160155622751], [32635, 0.9812160155622751], [32647, 0.9812160155622751], [32659, 0.9812160155622751], [32839, 0.9812160155622751], [32851, 0.9812160155622751], [32863, 0.9812160155622751], [32875, 0.9812160155622752], [32887, 0.9812160155622751], [32899, 0.9812160155622751], [32911, 0.9812160155622751], [32923, 0.9812160155622751], [32995, 0.9812160155622751], [33007, 0.9812160155622751], [33019, 0.9812160155622751], [33031, 0.9812160155622751], [33043, 0.9812160155622751], [33055, 0.9812160155622751], [33067, 0.9812160155622751], [33079, 0.9812160155622751], [33091, 0.9812160155622751], [33103, 0.9812160155622751], [33115, 0.9812160155622751], [33127, 0.9812160155622751], [33139, 0.9812160155622751], [33151, 0.9812160155622751], [33187, 0.9812160155622751], [33199, 0.9812160155622751], [33211, 0.9812160155622751], [33223, 0.9812160155622751], [33235, 0.981216015562275], [33271, 0.9812160155622751], [33307, 0.9812160155622751], [33319, 0.9812160155622751], [33331, 0.9812160155622751], [33343, 0.9812160155622751], [33355, 0.9812160155622751], [33367, 0.9812160155622752], [33379, 0.9812160155622751], [33391, 0.9812160155622751], [33403, 0.9812160155622751], [33415, 0.9812160155622751], [33427, 0.9812160155622751], [33439, 0.9812160155622751], [33451, 0.9812160155622751], [33463, 0.9812160155622751], [33523, 0.9812160155622751], [33535, 0.9812160155622751], [33547, 0.9812160155622751], [33559, 0.9812160155622751], [33655, 0.9812160155622751], [33715, 0.9812160155622751], [33727, 0.9812160155622751], [33739, 0.9812160155622751], [33763, 0.9812160155622751], [33775, 0.9812160155622751], [33811, 0.9812160155622751], [33823, 0.9812160155622752], [33835, 0.9812160155622751], [34039, 0.9812160155622751], [34051, 0.9812160155622751], [34063, 0.9812160155622751], [34075, 0.9812160155622751], [34087, 0.9812160155622751], [34123, 0.9812160155622752], [34135, 0.9812160155622751], [34147, 0.9812160155622752], [34159, 0.9812160155622751], [34171, 0.9812160155622751]] \ No newline at end of file +[[29227, 0.9812160155622751], [29239, 0.9812160155622751], [29251, 0.9812160155622752], [29263, 0.9812160155622751], [29287, 0.9812160155622751], [29299, 0.9812160155622751], [29323, 0.9812160155622751], [29335, 0.9812160155622752], [29347, 0.9812160155622751], [29359, 0.9812160155622751], [29371, 0.9812160155622751], [29383, 0.9812160155622752], [29395, 0.9812160155622751], [29407, 0.9812160155622751], [29419, 0.9812160155622752], [29431, 0.9812160155622751], [29443, 0.9812160155622751], [29455, 0.9812160155622751], [29467, 0.9812160155622752], [29479, 0.9812160155622751], [29551, 0.9812160155622752], [29563, 0.9812160155622751], [29575, 0.9812160155622751], [29599, 0.9812160155622751], [29611, 0.9812160155622751], [29623, 0.9812160155622751], [29647, 0.9812160155622751], [29659, 0.9812160155622751], [29671, 0.9812160155622752], [29743, 0.9812160155622751], [29755, 0.9812160155622751], [29767, 0.9812160155622751], [29779, 0.9812160155622751], [29791, 0.9812160155622751], [29803, 0.9812160155622751], [29815, 0.9812160155622751], [29827, 0.9812160155622751], [29839, 0.9812160155622751], [29851, 0.9812160155622751], [29863, 0.9812160155622751], [29875, 0.9812160155622751], [30007, 0.9812160155622751], [30019, 0.9812160155622751], [30031, 0.9812160155622751], [30043, 0.9812160155622751], [30055, 0.9812160155622751], [30067, 0.9812160155622751], [30079, 0.981216015562275], [30091, 0.9812160155622751], [30103, 0.9812160155622751], [30115, 0.9812160155622752], [30127, 0.9812160155622752], [30139, 0.9812160155622751], [30151, 0.9812160155622751], [30163, 0.9812160155622752], [30175, 0.9812160155622751], [30187, 0.9812160155622751], [30199, 0.9812160155622752], [30211, 0.9812160155622752], [30223, 0.9812160155622751], [30235, 0.9812160155622752], [30247, 0.9812160155622752], [30259, 0.9812160155622751], [30271, 0.9812160155622751], [30511, 0.9812160155622751], [30523, 0.9812160155622752], [30535, 0.9812160155622751], [30547, 0.9812160155622751], [30559, 0.9812160155622752], [30571, 0.9812160155622752], [30583, 0.9812160155622751], [30595, 0.9812160155622751], [30619, 0.9812160155622751], [30631, 0.9812160155622752], [30643, 0.9812160155622752], [30655, 0.9812160155622751], [30667, 0.9812160155622751], [30679, 0.9812160155622751], [30691, 0.9812160155622751], [30703, 0.9812160155622751], [30715, 0.9812160155622751], [30727, 0.9812160155622751], [30739, 0.9812160155622752], [30751, 0.9812160155622751], [30763, 0.9812160155622752], [30787, 0.9812160155622752], [30799, 0.9812160155622751], [30811, 0.9812160155622751], [30823, 0.9812160155622752], [30847, 0.9812160155622751], [30859, 0.9812160155622751], [30871, 0.9812160155622751], [30883, 0.9812160155622751], [30895, 0.9812160155622751], [30907, 0.9812160155622751], [30919, 0.9812160155622752], [30931, 0.9812160155622751], [30943, 0.9812160155622751], [30955, 0.9812160155622751], [30967, 0.9812160155622751], [30979, 0.9812160155622752], [30991, 0.9812160155622751], [31003, 0.9812160155622751], [31015, 0.9812160155622751], [31027, 0.9812160155622751], [31039, 0.9812160155622751], [31051, 0.9812160155622752], [32095, 0.9812160155622751], [32107, 0.9812160155622751], [32119, 0.9812160155622752], [32131, 0.9812160155622751], [32143, 0.9812160155622752], [32155, 0.9812160155622751], [32167, 0.9812160155622752], [32179, 0.9812160155622751], [32191, 0.9812160155622752], [32203, 0.9812160155622752], [32215, 0.9812160155622751], [32227, 0.9812160155622752], [32251, 0.9812160155622751], [32263, 0.9812160155622751], [32275, 0.9812160155622752], [32299, 0.9812160155622751], [32311, 0.9812160155622752], [32323, 0.9812160155622751], [32335, 0.9812160155622751], [32347, 0.9812160155622751], [32359, 0.9812160155622751], [32371, 0.9812160155622751], [32383, 0.9812160155622751], [32395, 0.9812160155622751], [32407, 0.9812160155622751], [32419, 0.9812160155622752], [32431, 0.9812160155622751], [32443, 0.9812160155622751], [32575, 0.9812160155622751], [32587, 0.9812160155622751], [32599, 0.9812160155622752], [32611, 0.9812160155622752], [32623, 0.9812160155622751], [32635, 0.9812160155622751], [32647, 0.9812160155622751], [32659, 0.9812160155622751], [32839, 0.9812160155622751], [32851, 0.9812160155622751], [32863, 0.9812160155622751], [32875, 0.9812160155622752], [32887, 0.9812160155622751], [32899, 0.9812160155622751], [32911, 0.9812160155622751], [32923, 0.9812160155622751], [32995, 0.9812160155622751], [33007, 0.9812160155622751], [33019, 0.9812160155622751], [33031, 0.9812160155622751], [33043, 0.9812160155622751], [33055, 0.9812160155622751], [33067, 0.9812160155622751], [33079, 0.9812160155622751], [33091, 0.9812160155622751], [33103, 0.9812160155622751], [33115, 0.9812160155622751], [33127, 0.9812160155622751], [33139, 0.9812160155622751], [33151, 0.9812160155622751], [33187, 0.9812160155622751], [33199, 0.9812160155622751], [33211, 0.9812160155622751], [33223, 0.9812160155622751], [33235, 0.981216015562275], [33271, 0.9812160155622751], [33307, 0.9812160155622751], [33319, 0.9812160155622751], [33331, 0.9812160155622751], [33343, 0.9812160155622751], [33355, 0.9812160155622751], [33367, 0.9812160155622752], [33379, 0.9812160155622751], [33391, 0.9812160155622751], [33403, 0.9812160155622751], [33415, 0.9812160155622751], [33427, 0.9812160155622751], [33439, 0.9812160155622751], [33451, 0.9812160155622751], [33463, 0.9812160155622751], [33523, 0.9812160155622751], [33535, 0.9812160155622751], [33547, 0.9812160155622751], [33559, 0.9812160155622751], [33655, 0.9812160155622751], [33715, 0.9812160155622751], [33727, 0.9812160155622751], [33739, 0.9812160155622751], [33763, 0.9812160155622751], [33775, 0.9812160155622751], [33811, 0.9812160155622751], [33823, 0.9812160155622752], [33835, 0.9812160155622751], [34039, 0.9812160155622751], [34051, 0.9812160155622751], [34063, 0.9812160155622751], [34075, 0.9812160155622751], [34087, 0.9812160155622751], [34123, 0.9812160155622752], [34135, 0.9812160155622751], [34147, 0.9812160155622752], [34159, 0.9812160155622751], [34171, 0.9812160155622752]] \ No newline at end of file diff --git a/graphs/summary/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json b/graphs/summary/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json index c941bd795f..45b796e59d 100644 --- a/graphs/summary/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json +++ b/graphs/summary/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[29227, 271425775.2619144], [29239, 270950093.9472651], [29251, 271339882.2313202], [29263, 270643442.50939006], [29287, 271261479.96042067], [29299, 271271530.0419069], [29323, 270547405.0419344], [29335, 271407649.868367], [29347, 270932485.1816721], [29359, 270490689.64260155], [29371, 270194818.6682852], [29383, 271202029.2338268], [29395, 271293074.2356794], [29407, 270573544.5858556], [29419, 271692295.6995705], [29431, 270762780.65923953], [29443, 270934682.48619145], [29455, 270331790.4764241], [29467, 270628808.31251854], [29479, 270912413.73243856], [29551, 271817858.4914858], [29563, 272489782.80159837], [29575, 270018023.8311659], [29599, 272511505.09311557], [29611, 272086687.5930301], [29623, 272413384.77024066], [29647, 272780457.3803864], [29659, 272162327.2847723], [29671, 272412802.1698602], [29743, 272505025.8431578], [29755, 271595755.4954703], [29767, 272330127.9355482], [29779, 272439786.18337214], [29791, 272691555.15641093], [29803, 272891651.80182624], [29815, 271532763.7084967], [29827, 271554273.8329083], [29839, 272205183.3328739], [29851, 271744214.6961926], [29863, 272022282.477475], [29875, 271752364.34307456], [30007, 272536092.4436878], [30019, 272764023.2135128], [30031, 272139278.57765543], [30043, 272856528.1618178], [30055, 273145697.28059655], [30067, 271730427.00596225], [30079, 272293291.49978215], [30091, 272317240.92514306], [30103, 271909820.2572427], [30115, 272478762.12448627], [30127, 272718345.7647703], [30139, 272450707.4611479], [30151, 273271434.0327485], [30163, 271980415.80683213], [30175, 272738842.0332906], [30187, 273601243.32769644], [30199, 273382977.2269185], [30211, 273541229.91225344], [30223, 273295615.5967646], [30235, 273104550.95014524], [30247, 272536680.2027411], [30259, 272894728.462512], [30271, 272528345.15318], [30511, 272871669.67909265], [30523, 272788990.4084143], [30535, 272948327.8123389], [30547, 273109308.60260093], [30559, 272563453.849034], [30571, 273089673.86582834], [30583, 273204700.6017139], [30595, 272602606.2104399], [30619, 272660929.77068794], [30631, 273429706.28776526], [30643, 272142804.8514859], [30655, 273102176.6515843], [30667, 273202722.83714944], [30679, 272157824.3727638], [30691, 272000647.27129966], [30703, 272029625.76905525], [30715, 273443153.6765707], [30727, 272565241.7040587], [30739, 272704396.3511567], [30751, 272016952.9125267], [30763, 273006368.74083227], [30787, 272916517.0643583], [30799, 272492607.4116494], [30811, 271926377.90224946], [30823, 273201677.0985863], [30847, 273733380.5468075], [30859, 272760526.77473503], [30871, 272422519.16624165], [30883, 271760701.94071025], [30895, 273614324.3562869], [30907, 273310589.21554506], [30919, 272464596.94383806], [30931, 273158679.8822346], [30943, 272534770.7346516], [30955, 273198863.9122055], [30967, 273255147.40635115], [30979, 273777389.4504242], [30991, 273319444.90373504], [31003, 272565995.08878857], [31015, 273769591.8935185], [31027, 272675938.6857607], [31039, 273444630.53240114], [31051, 273114552.10292673], [32095, 322998322.2091028], [32107, 321066222.0349035], [32119, 322267376.8096344], [32131, 321737019.9737487], [32143, 322593996.9037017], [32155, 322443611.88025695], [32167, 321167805.59164214], [32179, 320875191.46516085], [32191, 321453613.0125269], [32203, 322649718.68863493], [32215, 325098124.14103854], [32227, 324240180.81900287], [32251, 324546817.86499655], [32263, 325003334.2218656], [32275, 325252015.21378565], [32299, 325862007.15264827], [32311, 333336165.0932242], [32323, 331708020.735543], [32335, 331945488.3073645], [32347, 332609938.9988383], [32359, 333509597.7235959], [32371, 332116403.8243554], [32383, 332162084.570022], [32395, 331935224.05445117], [32407, 332249757.0623759], [32419, 332552488.4164107], [32431, 332479959.16960645], [32443, 333425035.04922736], [32575, 327258537.734788], [32587, 327921947.94489115], [32599, 327835977.68013877], [32611, 328272595.31370145], [32623, 328953692.9827505], [32635, 328370957.62078506], [32647, 327135106.86238503], [32659, 328195658.8745234], [32839, 329829832.27604], [32851, 329963544.6244135], [32863, 330180315.1697625], [32875, 330313508.97852945], [32887, 328381086.52144665], [32899, 330250774.09697837], [32911, 329892271.9165354], [32923, 329906296.49502295], [32995, 330169392.6318713], [33007, 329906713.8958831], [33019, 329686943.8013587], [33031, 330195844.78413016], [33043, 330012812.07557833], [33055, 328995030.2554814], [33067, 329984676.0303981], [33079, 330317789.0465461], [33091, 357909715.87032235], [33103, 356839679.8965644], [33115, 356134921.13354594], [33127, 356904148.2755704], [33139, 357720461.8783728], [33151, 357897311.90137815], [33187, 328746945.8417054], [33199, 330038489.1961566], [33211, 328176993.71082944], [33223, 315147181.5960041], [33235, 304213886.04853696], [33271, 287067282.8569833], [33307, 272677118.1057529], [33319, 272546781.4331894], [33331, 273170916.1316783], [33343, 277194965.1558669], [33355, 277927557.56529546], [33367, 273586800.87445134], [33379, 283035025.91097814], [33391, 280507110.9028399], [33403, 274322728.1047113], [33415, 274459924.12226564], [33427, 274359443.67949516], [33439, 275226661.6899493], [33451, 280039789.89972836], [33463, 270437973.40465957], [33523, 275300874.06069344], [33535, 276464587.15552175], [33547, 279304066.82887965], [33559, 268309501.67238674], [33655, 268916552.3380579], [33715, 268685129.526179], [33727, 268878529.5517457], [33739, 268615409.3919357], [33763, 268950862.9627471], [33775, 268903781.5758243], [33811, 268537239.741493], [33823, 268482545.6645585], [33835, 268218661.01532203], [34039, 268287220.7723602], [34051, 268418217.28378314], [34063, 268774262.25693583], [34075, 268438645.2704551], [34087, 268253319.1141836], [34123, 268605209.43441576], [34135, 268944884.80401343], [34147, 268347917.6847628], [34159, 268491168.4593346], [34171, 268510294.3298403]] \ No newline at end of file +[[29227, 271425775.2619144], [29239, 270950093.9472651], [29251, 271339882.2313202], [29263, 270643442.50939006], [29287, 271261479.96042067], [29299, 271271530.0419069], [29323, 270547405.0419344], [29335, 271407649.868367], [29347, 270932485.1816721], [29359, 270490689.64260155], [29371, 270194818.6682852], [29383, 271202029.2338268], [29395, 271293074.2356794], [29407, 270573544.5858556], [29419, 271692295.6995705], [29431, 270762780.65923953], [29443, 270934682.48619145], [29455, 270331790.4764241], [29467, 270628808.31251854], [29479, 270912413.73243856], [29551, 271817858.4914858], [29563, 272489782.80159837], [29575, 270018023.8311659], [29599, 272511505.09311557], [29611, 272086687.5930301], [29623, 272413384.77024066], [29647, 272780457.3803864], [29659, 272162327.2847723], [29671, 272412802.1698602], [29743, 272505025.8431578], [29755, 271595755.4954703], [29767, 272330127.9355482], [29779, 272439786.18337214], [29791, 272691555.15641093], [29803, 272891651.80182624], [29815, 271532763.7084967], [29827, 271554273.8329083], [29839, 272205183.3328739], [29851, 271744214.6961926], [29863, 272022282.477475], [29875, 271752364.34307456], [30007, 272536092.4436878], [30019, 272764023.2135128], [30031, 272139278.57765543], [30043, 272856528.1618178], [30055, 273145697.28059655], [30067, 271730427.00596225], [30079, 272293291.49978215], [30091, 272317240.92514306], [30103, 271909820.2572427], [30115, 272478762.12448627], [30127, 272718345.7647703], [30139, 272450707.4611479], [30151, 273271434.0327485], [30163, 271980415.80683213], [30175, 272738842.0332906], [30187, 273601243.32769644], [30199, 273382977.2269185], [30211, 273541229.91225344], [30223, 273295615.5967646], [30235, 273104550.95014524], [30247, 272536680.2027411], [30259, 272894728.462512], [30271, 272528345.15318], [30511, 272871669.67909265], [30523, 272788990.4084143], [30535, 272948327.8123389], [30547, 273109308.60260093], [30559, 272563453.849034], [30571, 273089673.86582834], [30583, 273204700.6017139], [30595, 272602606.2104399], [30619, 272660929.77068794], [30631, 273429706.28776526], [30643, 272142804.8514859], [30655, 273102176.6515843], [30667, 273202722.83714944], [30679, 272157824.3727638], [30691, 272000647.27129966], [30703, 272029625.76905525], [30715, 273443153.6765707], [30727, 272565241.7040587], [30739, 272704396.3511567], [30751, 272016952.9125267], [30763, 273006368.74083227], [30787, 272916517.0643583], [30799, 272492607.4116494], [30811, 271926377.90224946], [30823, 273201677.0985863], [30847, 273733380.5468075], [30859, 272760526.77473503], [30871, 272422519.16624165], [30883, 271760701.94071025], [30895, 273614324.3562869], [30907, 273310589.21554506], [30919, 272464596.94383806], [30931, 273158679.8822346], [30943, 272534770.7346516], [30955, 273198863.9122055], [30967, 273255147.40635115], [30979, 273777389.4504242], [30991, 273319444.90373504], [31003, 272565995.08878857], [31015, 273769591.8935185], [31027, 272675938.6857607], [31039, 273444630.53240114], [31051, 273114552.10292673], [32095, 322998322.2091028], [32107, 321066222.0349035], [32119, 322267376.8096344], [32131, 321737019.9737487], [32143, 322593996.9037017], [32155, 322443611.88025695], [32167, 321167805.59164214], [32179, 320875191.46516085], [32191, 321453613.0125269], [32203, 322649718.68863493], [32215, 325098124.14103854], [32227, 324240180.81900287], [32251, 324546817.86499655], [32263, 325003334.2218656], [32275, 325252015.21378565], [32299, 325862007.15264827], [32311, 333336165.0932242], [32323, 331708020.735543], [32335, 331945488.3073645], [32347, 332609938.9988383], [32359, 333509597.7235959], [32371, 332116403.8243554], [32383, 332162084.570022], [32395, 331935224.05445117], [32407, 332249757.0623759], [32419, 332552488.4164107], [32431, 332479959.16960645], [32443, 333425035.04922736], [32575, 327258537.734788], [32587, 327921947.94489115], [32599, 327835977.68013877], [32611, 328272595.31370145], [32623, 328953692.9827505], [32635, 328370957.62078506], [32647, 327135106.86238503], [32659, 328195658.8745234], [32839, 329829832.27604], [32851, 329963544.6244135], [32863, 330180315.1697625], [32875, 330313508.97852945], [32887, 328381086.52144665], [32899, 330250774.09697837], [32911, 329892271.9165354], [32923, 329906296.49502295], [32995, 330169392.6318713], [33007, 329906713.8958831], [33019, 329686943.8013587], [33031, 330195844.78413016], [33043, 330012812.07557833], [33055, 328995030.2554814], [33067, 329984676.0303981], [33079, 330317789.0465461], [33091, 357909715.87032235], [33103, 356839679.8965644], [33115, 356134921.13354594], [33127, 356904148.2755704], [33139, 357720461.8783728], [33151, 357897311.90137815], [33187, 328746945.8417054], [33199, 330038489.1961566], [33211, 328176993.71082944], [33223, 315147181.5960041], [33235, 304213886.04853696], [33271, 287067282.8569833], [33307, 272677118.1057529], [33319, 272546781.4331894], [33331, 273170916.1316783], [33343, 277194965.1558669], [33355, 277927557.56529546], [33367, 273586800.87445134], [33379, 283035025.91097814], [33391, 280507110.9028399], [33403, 274322728.1047113], [33415, 274459924.12226564], [33427, 274359443.67949516], [33439, 275226661.6899493], [33451, 280039789.89972836], [33463, 270437973.40465957], [33523, 275300874.06069344], [33535, 276464587.15552175], [33547, 279304066.82887965], [33559, 268309501.67238674], [33655, 268916552.3380579], [33715, 268685129.526179], [33727, 268878529.5517457], [33739, 268615409.3919357], [33763, 268950862.9627471], [33775, 268903781.5758243], [33811, 268537239.741493], [33823, 268482545.6645585], [33835, 268218661.01532203], [34039, 268287220.7723602], [34051, 268418217.28378314], [34063, 268774262.25693583], [34075, 268438645.2704551], [34087, 268253319.1141836], [34123, 268605209.43441576], [34135, 268944884.80401343], [34147, 268347917.6847628], [34159, 268491168.4593346], [34171, 268387029.92450896]] \ No newline at end of file diff --git a/graphs/summary/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json b/graphs/summary/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json index 554469082e..98fbe8b56a 100644 --- a/graphs/summary/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json +++ b/graphs/summary/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[29227, 257549318.90484428], [29239, 257446014.91623366], [29251, 257742901.77496555], [29263, 257725321.45476758], [29287, 257751623.40359837], [29299, 257616854.51200426], [29323, 257528272.17622972], [29335, 257761383.05182216], [29347, 257280228.37038404], [29359, 257017538.6622145], [29371, 257232977.84980312], [29383, 257237559.95483413], [29395, 257069492.2099564], [29407, 257039109.8585338], [29419, 257238207.48409674], [29431, 257585064.11934334], [29443, 257941763.12192646], [29455, 257460212.2681663], [29467, 257585532.8093532], [29479, 257458959.80973276], [29551, 257749391.04205275], [29563, 258071281.549086], [29575, 257001800.51816088], [29599, 258508538.61266974], [29611, 258537447.3850919], [29623, 258485154.86497325], [29647, 258677662.7686029], [29659, 258499505.7220862], [29671, 258336053.22267565], [29743, 258470791.78622967], [29755, 258636709.37488052], [29767, 258591628.43872458], [29779, 258391470.9810894], [29791, 258493135.7516268], [29803, 258611966.9281386], [29815, 258609205.76515532], [29827, 258561159.89067274], [29839, 258587137.84807995], [29851, 258509006.597578], [29863, 258555524.77456108], [29875, 258790119.66403875], [30007, 258583369.5515744], [30019, 258673736.6585236], [30031, 258539399.3105687], [30043, 258517921.83084247], [30055, 258633794.74957752], [30067, 258617976.70791405], [30079, 258768857.9665222], [30091, 258828343.02029407], [30103, 258619131.29525307], [30115, 258926513.40393496], [30127, 258822046.81430256], [30139, 258863007.77110034], [30151, 259021714.37989223], [30163, 259091578.7817138], [30175, 259162933.03462666], [30187, 259270432.53080976], [30199, 259109502.4161906], [30211, 259136849.91400638], [30223, 259268932.67082518], [30235, 259276119.70906425], [30247, 259284097.16197094], [30259, 259214062.91721714], [30271, 259197383.59611136], [30511, 259295398.5847537], [30523, 258990399.04836276], [30535, 259150828.65205705], [30547, 259117349.366558], [30559, 259006727.1875905], [30571, 259119673.97112295], [30583, 259034085.3480742], [30595, 259248842.24152112], [30619, 259165936.71719012], [30631, 259233112.5739303], [30643, 259001450.21994564], [30655, 259194068.20756134], [30667, 259227527.56345958], [30679, 258970563.34803498], [30691, 258972630.07909697], [30703, 258990950.11176848], [30715, 259199892.65767312], [30727, 259305107.6385828], [30739, 258946209.87574923], [30751, 259152092.2933378], [30763, 259768665.69727263], [30787, 259122629.17164493], [30799, 259172884.65944254], [30811, 258965455.68694407], [30823, 259254670.114041], [30847, 259433071.6580843], [30859, 259162455.72432324], [30871, 259207906.29268336], [30883, 259228848.79260832], [30895, 259425673.65901762], [30907, 259099833.71137872], [30919, 259045663.81779766], [30931, 259596291.86588275], [30943, 259317004.37517065], [30955, 259248200.84468782], [30967, 259366445.04442197], [30979, 259343582.98487678], [30991, 259480424.06285438], [31003, 259343859.9558224], [31015, 259491552.17496663], [31027, 259132854.42220896], [31039, 259046623.45200473], [31051, 259382023.94972575], [32095, 275128701.8422194], [32107, 274811801.3558353], [32119, 275320920.5900616], [32131, 275018089.3333035], [32143, 275247387.45178777], [32155, 274519894.9410974], [32167, 275043621.7560226], [32179, 274336567.767588], [32191, 274872605.7305257], [32203, 276091781.9219343], [32215, 278081083.7050251], [32227, 277833599.6119145], [32251, 277794423.49054253], [32263, 278021677.9980649], [32275, 277877523.93810874], [32299, 277855805.4323183], [32311, 285943168.4832421], [32323, 285780787.9734962], [32335, 285450298.4399114], [32347, 285815396.1697191], [32359, 286029647.5940339], [32371, 285915170.26319927], [32383, 285686801.36212677], [32395, 286053878.07801914], [32407, 286076380.21440136], [32419, 285698236.8820445], [32431, 286012273.85447663], [32443, 286521123.68062633], [32575, 281100364.60367924], [32587, 280775412.0710249], [32599, 281131837.5856049], [32611, 281073074.2094347], [32623, 281330991.24798584], [32635, 280669681.4648514], [32647, 281291584.0727388], [32659, 281303840.426931], [32839, 281611084.4212465], [32851, 282098280.4626875], [32863, 282126525.73021466], [32875, 282151270.73509485], [32887, 282543244.74032336], [32899, 282376135.5857698], [32911, 282173997.62899894], [32923, 282276258.3406231], [32995, 282505459.7373504], [33007, 282196179.39259744], [33019, 282128915.50573575], [33031, 281779667.37414986], [33043, 282313356.01691496], [33055, 282385318.3781071], [33067, 282245486.5884255], [33079, 282622959.4042665], [33091, 308855151.9825983], [33103, 308563058.31331694], [33115, 308993796.52501595], [33127, 308031173.14544916], [33139, 308503371.58502465], [33151, 308648905.1004389], [33187, 282783230.1279457], [33199, 282174021.99497914], [33211, 282189765.3361019], [33223, 279933583.439679], [33235, 276910145.16897213], [33271, 270999942.82814854], [33307, 277402736.7601385], [33319, 277193369.13573265], [33331, 277683832.5764399], [33343, 277558877.21571785], [33355, 277996379.12643856], [33367, 278221173.8850464], [33379, 278580599.7045716], [33391, 278838110.1862758], [33403, 278750562.2159803], [33415, 279483213.47422534], [33427, 278775778.4765189], [33439, 280041195.0368898], [33451, 274826910.42576337], [33463, 274987893.7896755], [33523, 274909198.9780265], [33535, 274965342.34343535], [33547, 274472252.4941803], [33559, 272985819.2227825], [33655, 273549262.05380905], [33715, 273324750.6982022], [33727, 273358262.9289998], [33739, 273038089.88641655], [33763, 273455798.16337293], [33775, 273342537.3062482], [33811, 273479292.45023], [33823, 273095185.67257243], [33835, 272965277.04972076], [34039, 272771132.20325685], [34051, 273229934.00652057], [34063, 273362301.42144465], [34075, 272859060.14926755], [34087, 273021560.06345177], [34123, 273212547.6898487], [34135, 273569391.78764343], [34147, 273041393.1098854], [34159, 273087479.742033], [34171, 273090009.5389561]] \ No newline at end of file +[[29227, 257549318.90484428], [29239, 257446014.91623366], [29251, 257742901.77496555], [29263, 257725321.45476758], [29287, 257751623.40359837], [29299, 257616854.51200426], [29323, 257528272.17622972], [29335, 257761383.05182216], [29347, 257280228.37038404], [29359, 257017538.6622145], [29371, 257232977.84980312], [29383, 257237559.95483413], [29395, 257069492.2099564], [29407, 257039109.8585338], [29419, 257238207.48409674], [29431, 257585064.11934334], [29443, 257941763.12192646], [29455, 257460212.2681663], [29467, 257585532.8093532], [29479, 257458959.80973276], [29551, 257749391.04205275], [29563, 258071281.549086], [29575, 257001800.51816088], [29599, 258508538.61266974], [29611, 258537447.3850919], [29623, 258485154.86497325], [29647, 258677662.7686029], [29659, 258499505.7220862], [29671, 258336053.22267565], [29743, 258470791.78622967], [29755, 258636709.37488052], [29767, 258591628.43872458], [29779, 258391470.9810894], [29791, 258493135.7516268], [29803, 258611966.9281386], [29815, 258609205.76515532], [29827, 258561159.89067274], [29839, 258587137.84807995], [29851, 258509006.597578], [29863, 258555524.77456108], [29875, 258790119.66403875], [30007, 258583369.5515744], [30019, 258673736.6585236], [30031, 258539399.3105687], [30043, 258517921.83084247], [30055, 258633794.74957752], [30067, 258617976.70791405], [30079, 258768857.9665222], [30091, 258828343.02029407], [30103, 258619131.29525307], [30115, 258926513.40393496], [30127, 258822046.81430256], [30139, 258863007.77110034], [30151, 259021714.37989223], [30163, 259091578.7817138], [30175, 259162933.03462666], [30187, 259270432.53080976], [30199, 259109502.4161906], [30211, 259136849.91400638], [30223, 259268932.67082518], [30235, 259276119.70906425], [30247, 259284097.16197094], [30259, 259214062.91721714], [30271, 259197383.59611136], [30511, 259295398.5847537], [30523, 258990399.04836276], [30535, 259150828.65205705], [30547, 259117349.366558], [30559, 259006727.1875905], [30571, 259119673.97112295], [30583, 259034085.3480742], [30595, 259248842.24152112], [30619, 259165936.71719012], [30631, 259233112.5739303], [30643, 259001450.21994564], [30655, 259194068.20756134], [30667, 259227527.56345958], [30679, 258970563.34803498], [30691, 258972630.07909697], [30703, 258990950.11176848], [30715, 259199892.65767312], [30727, 259305107.6385828], [30739, 258946209.87574923], [30751, 259152092.2933378], [30763, 259768665.69727263], [30787, 259122629.17164493], [30799, 259172884.65944254], [30811, 258965455.68694407], [30823, 259254670.114041], [30847, 259433071.6580843], [30859, 259162455.72432324], [30871, 259207906.29268336], [30883, 259228848.79260832], [30895, 259425673.65901762], [30907, 259099833.71137872], [30919, 259045663.81779766], [30931, 259596291.86588275], [30943, 259317004.37517065], [30955, 259248200.84468782], [30967, 259366445.04442197], [30979, 259343582.98487678], [30991, 259480424.06285438], [31003, 259343859.9558224], [31015, 259491552.17496663], [31027, 259132854.42220896], [31039, 259046623.45200473], [31051, 259382023.94972575], [32095, 275128701.8422194], [32107, 274811801.3558353], [32119, 275320920.5900616], [32131, 275018089.3333035], [32143, 275247387.45178777], [32155, 274519894.9410974], [32167, 275043621.7560226], [32179, 274336567.767588], [32191, 274872605.7305257], [32203, 276091781.9219343], [32215, 278081083.7050251], [32227, 277833599.6119145], [32251, 277794423.49054253], [32263, 278021677.9980649], [32275, 277877523.93810874], [32299, 277855805.4323183], [32311, 285943168.4832421], [32323, 285780787.9734962], [32335, 285450298.4399114], [32347, 285815396.1697191], [32359, 286029647.5940339], [32371, 285915170.26319927], [32383, 285686801.36212677], [32395, 286053878.07801914], [32407, 286076380.21440136], [32419, 285698236.8820445], [32431, 286012273.85447663], [32443, 286521123.68062633], [32575, 281100364.60367924], [32587, 280775412.0710249], [32599, 281131837.5856049], [32611, 281073074.2094347], [32623, 281330991.24798584], [32635, 280669681.4648514], [32647, 281291584.0727388], [32659, 281303840.426931], [32839, 281611084.4212465], [32851, 282098280.4626875], [32863, 282126525.73021466], [32875, 282151270.73509485], [32887, 282543244.74032336], [32899, 282376135.5857698], [32911, 282173997.62899894], [32923, 282276258.3406231], [32995, 282505459.7373504], [33007, 282196179.39259744], [33019, 282128915.50573575], [33031, 281779667.37414986], [33043, 282313356.01691496], [33055, 282385318.3781071], [33067, 282245486.5884255], [33079, 282622959.4042665], [33091, 308855151.9825983], [33103, 308563058.31331694], [33115, 308993796.52501595], [33127, 308031173.14544916], [33139, 308503371.58502465], [33151, 308648905.1004389], [33187, 282783230.1279457], [33199, 282174021.99497914], [33211, 282189765.3361019], [33223, 279933583.439679], [33235, 276910145.16897213], [33271, 270999942.82814854], [33307, 277402736.7601385], [33319, 277193369.13573265], [33331, 277683832.5764399], [33343, 277558877.21571785], [33355, 277996379.12643856], [33367, 278221173.8850464], [33379, 278580599.7045716], [33391, 278838110.1862758], [33403, 278750562.2159803], [33415, 279483213.47422534], [33427, 278775778.4765189], [33439, 280041195.0368898], [33451, 274826910.42576337], [33463, 274987893.7896755], [33523, 274909198.9780265], [33535, 274965342.34343535], [33547, 274472252.4941803], [33559, 272985819.2227825], [33655, 273549262.05380905], [33715, 273324750.6982022], [33727, 273358262.9289998], [33739, 273038089.88641655], [33763, 273455798.16337293], [33775, 273342537.3062482], [33811, 273479292.45023], [33823, 273095185.67257243], [33835, 272965277.04972076], [34039, 272771132.20325685], [34051, 273229934.00652057], [34063, 273362301.42144465], [34075, 272859060.14926755], [34087, 273021560.06345177], [34123, 273212547.6898487], [34135, 273569391.78764343], [34147, 273041393.1098854], [34159, 273087479.742033], [34171, 272957926.16790366]] \ No newline at end of file diff --git a/graphs/summary/ensemble.RandomForestClassifierBenchmark.time_fit.json b/graphs/summary/ensemble.RandomForestClassifierBenchmark.time_fit.json index 4fde6dbafd..ccf340316f 100644 --- a/graphs/summary/ensemble.RandomForestClassifierBenchmark.time_fit.json +++ b/graphs/summary/ensemble.RandomForestClassifierBenchmark.time_fit.json @@ -1 +1 @@ -[[29227, 5.2494295903378365], [29239, 5.167874789117803], [29251, 3.911916831484905], [29263, 3.9252864475859894], [29287, 3.914331347024356], [29299, 3.913786765664403], [29323, 3.928025528758], [29335, 3.930639050841387], [29347, 3.922314040981611], [29359, 3.951394244461249], [29371, 3.910031379674899], [29383, 3.928648824377032], [29395, 3.9185871745547587], [29407, 3.933426084059132], [29419, 3.909676269866585], [29431, 3.913090589464838], [29443, 6.22076336469135], [29455, 6.056050519448021], [29467, 6.192319136521668], [29479, 5.824871100022303], [29551, 6.190022065175988], [29563, 5.225370637625769], [29575, 4.932592904295614], [29599, 4.963900011600256], [29611, 5.142781735771365], [29623, 5.1245331244904735], [29647, 5.0559817197141825], [29659, 5.104969187645118], [29671, 5.029395294945494], [29743, 5.17569472144454], [29755, 5.149769538582101], [29767, 5.146001196636471], [29779, 6.10086621245099], [29791, 5.119318352508049], [29803, 5.151983184439289], [29815, 5.333867480272377], [29827, 5.216783772295259], [29839, 5.217873493983091], [29851, 5.210194015618015], [29863, 5.1035066779304366], [29875, 5.271341898802595], [30007, 5.354938418266194], [30019, 5.178320293212856], [30031, 5.238077072979798], [30043, 5.500752990769082], [30055, 5.092998175892544], [30067, 5.115180968987277], [30079, 5.322730098319981], [30091, 5.074289602152468], [30103, 5.3742652772114665], [30115, 5.258027254238614], [30127, 5.071340021384198], [30139, 5.3869441971211565], [30151, 5.039235252620874], [30163, 5.329833889992126], [30175, 5.336888719229423], [30187, 5.079243853096214], [30199, 5.089351787653101], [30211, 5.192312766896286], [30223, 5.310334612004071], [30235, 5.208611828042446], [30247, 5.426047593043801], [30259, 5.432102652592759], [30271, 5.337547071780158], [30511, 5.27160821456349], [30523, 5.09611769541582], [30535, 5.066779764621771], [30547, 5.074718683716277], [30559, 5.222574276983141], [30571, 5.0869521601567795], [30583, 5.244035138799753], [30595, 5.303547816621624], [30619, 5.3492113128889205], [30631, 5.059235402046064], [30643, 5.18622415461471], [30655, 5.175102748128993], [30667, 5.111948272907151], [30679, 5.335251984422182], [30691, 5.346983008744932], [30703, 5.439073831223609], [30715, 5.450110661775399], [30727, 5.2004381946798315], [30739, 5.254862688733729], [30751, 5.258370905960535], [30763, 5.219225573794748], [30787, 5.128016481429901], [30799, 5.458482390124804], [30811, 5.172592646418293], [30823, 5.127922758474383], [30847, 5.647109288726951], [30859, 4.93936258381548], [30871, 5.219079141826107], [30883, 5.307925017564093], [30895, 5.177071361638325], [30907, 5.28843325586623], [30919, 5.148352908134227], [30931, 5.027055453224336], [30943, 4.627577508333735], [30955, 5.219822039280558], [30967, 5.003292641943685], [30979, 5.153167371236455], [30991, 5.224062444728809], [31003, 4.899480855035464], [31015, 5.080475025614255], [31027, 5.38505730714808], [31039, 5.413576631956629], [31051, 5.027179076264409], [32095, 6.0353588121226815], [32107, 6.27735512503747], [32119, 6.146033004936361], [32131, 6.151886660455664], [32143, 6.085237502027496], [32155, 6.167626386727447], [32167, 6.221715675655287], [32179, 5.893268765378564], [32191, 6.059364799832047], [32203, 6.149029891329508], [32215, 6.108980599926173], [32227, 6.046715561127982], [32251, 6.103143512961973], [32263, 6.210550599124075], [32275, 6.033928256474233], [32299, 6.1619069263394906], [32311, 6.0912639290533095], [32323, 5.802028483670418], [32335, 5.904689499831146], [32347, 6.168032991392976], [32359, 6.077819014818216], [32371, 6.033534094460645], [32383, 6.134837853057717], [32395, 6.4530769995472275], [32407, 6.407867293692699], [32419, 6.125736593959068], [32431, 7.189257368390152], [32443, 6.606088885590856], [32575, 6.786295830104762], [32587, 6.567868153361802], [32599, 8.080078044937592], [32611, 8.112280720755777], [32623, 8.41507452484582], [32635, 8.726290978890818], [32647, 8.520276999607926], [32659, 8.501691743575307], [32839, 8.208061054159], [32851, 7.848647959911696], [32863, 8.02809332704312], [32875, 7.783293267926982], [32887, 7.762957086367041], [32899, 7.992214971759301], [32911, 7.634705608836725], [32923, 7.917408531317043], [32995, 8.01953320753667], [33007, 7.947609208411921], [33019, 7.972952288520954], [33031, 8.08205865145795], [33043, 8.084825067419855], [33055, 7.668771310110769], [33067, 8.241365822343125], [33079, 7.933817648265456], [33091, 8.051573025471853], [33103, 8.088857820368837], [33115, 8.108911157710278], [33127, 8.022571867912061], [33139, 8.154411107941993], [33151, 8.08103527066536], [33187, 7.931640204123595], [33199, 8.167030349376613], [33211, 7.868155912044196], [33223, 7.602845155718725], [33235, 6.843189765289497], [33271, 5.816390990524681], [33307, 6.639977464278246], [33319, 5.604529393984155], [33331, 5.599551844704078], [33343, 5.6760994381960606], [33355, 5.486591941892391], [33367, 5.781778231667307], [33379, 5.490166151008033], [33391, 5.704264882757089], [33403, 5.425321367956283], [33415, 5.526833690680481], [33427, 5.5989857441717605], [33439, 5.791551973377795], [33451, 5.372076413693631], [33463, 5.802061594681834], [33523, 5.70669197689057], [33535, 5.651384935996627], [33547, 5.695863005266683], [33559, 33.08641072102611], [33655, 31.62857173589212], [33715, 31.971504768157075], [33727, 18.454815149820504], [33739, 5.890593977516335], [33763, 5.833576288391502], [33775, 5.9394886858219555], [33811, 5.743202899885525], [33823, 5.678940357809824], [33835, 5.722769389042298], [34039, 33.094462839304185], [34051, 30.97466923695363], [34063, 32.35237615966909], [34075, 34.304509737424176], [34087, 32.85419273234811], [34123, 5.609494562402578], [34135, 5.672453622203122], [34147, 5.556491277766791], [34159, 5.58195525339163], [34171, 5.614414215083826]] \ No newline at end of file +[[29227, 5.2494295903378365], [29239, 5.167874789117803], [29251, 3.911916831484905], [29263, 3.9252864475859894], [29287, 3.914331347024356], [29299, 3.913786765664403], [29323, 3.928025528758], [29335, 3.930639050841387], [29347, 3.922314040981611], [29359, 3.951394244461249], [29371, 3.910031379674899], [29383, 3.928648824377032], [29395, 3.9185871745547587], [29407, 3.933426084059132], [29419, 3.909676269866585], [29431, 3.913090589464838], [29443, 6.22076336469135], [29455, 6.056050519448021], [29467, 6.192319136521668], [29479, 5.824871100022303], [29551, 6.190022065175988], [29563, 5.225370637625769], [29575, 4.932592904295614], [29599, 4.963900011600256], [29611, 5.142781735771365], [29623, 5.1245331244904735], [29647, 5.0559817197141825], [29659, 5.104969187645118], [29671, 5.029395294945494], [29743, 5.17569472144454], [29755, 5.149769538582101], [29767, 5.146001196636471], [29779, 6.10086621245099], [29791, 5.119318352508049], [29803, 5.151983184439289], [29815, 5.333867480272377], [29827, 5.216783772295259], [29839, 5.217873493983091], [29851, 5.210194015618015], [29863, 5.1035066779304366], [29875, 5.271341898802595], [30007, 5.354938418266194], [30019, 5.178320293212856], [30031, 5.238077072979798], [30043, 5.500752990769082], [30055, 5.092998175892544], [30067, 5.115180968987277], [30079, 5.322730098319981], [30091, 5.074289602152468], [30103, 5.3742652772114665], [30115, 5.258027254238614], [30127, 5.071340021384198], [30139, 5.3869441971211565], [30151, 5.039235252620874], [30163, 5.329833889992126], [30175, 5.336888719229423], [30187, 5.079243853096214], [30199, 5.089351787653101], [30211, 5.192312766896286], [30223, 5.310334612004071], [30235, 5.208611828042446], [30247, 5.426047593043801], [30259, 5.432102652592759], [30271, 5.337547071780158], [30511, 5.27160821456349], [30523, 5.09611769541582], [30535, 5.066779764621771], [30547, 5.074718683716277], [30559, 5.222574276983141], [30571, 5.0869521601567795], [30583, 5.244035138799753], [30595, 5.303547816621624], [30619, 5.3492113128889205], [30631, 5.059235402046064], [30643, 5.18622415461471], [30655, 5.175102748128993], [30667, 5.111948272907151], [30679, 5.335251984422182], [30691, 5.346983008744932], [30703, 5.439073831223609], [30715, 5.450110661775399], [30727, 5.2004381946798315], [30739, 5.254862688733729], [30751, 5.258370905960535], [30763, 5.219225573794748], [30787, 5.128016481429901], [30799, 5.458482390124804], [30811, 5.172592646418293], [30823, 5.127922758474383], [30847, 5.647109288726951], [30859, 4.93936258381548], [30871, 5.219079141826107], [30883, 5.307925017564093], [30895, 5.177071361638325], [30907, 5.28843325586623], [30919, 5.148352908134227], [30931, 5.027055453224336], [30943, 4.627577508333735], [30955, 5.219822039280558], [30967, 5.003292641943685], [30979, 5.153167371236455], [30991, 5.224062444728809], [31003, 4.899480855035464], [31015, 5.080475025614255], [31027, 5.38505730714808], [31039, 5.413576631956629], [31051, 5.027179076264409], [32095, 6.0353588121226815], [32107, 6.27735512503747], [32119, 6.146033004936361], [32131, 6.151886660455664], [32143, 6.085237502027496], [32155, 6.167626386727447], [32167, 6.221715675655287], [32179, 5.893268765378564], [32191, 6.059364799832047], [32203, 6.149029891329508], [32215, 6.108980599926173], [32227, 6.046715561127982], [32251, 6.103143512961973], [32263, 6.210550599124075], [32275, 6.033928256474233], [32299, 6.1619069263394906], [32311, 6.0912639290533095], [32323, 5.802028483670418], [32335, 5.904689499831146], [32347, 6.168032991392976], [32359, 6.077819014818216], [32371, 6.033534094460645], [32383, 6.134837853057717], [32395, 6.4530769995472275], [32407, 6.407867293692699], [32419, 6.125736593959068], [32431, 7.189257368390152], [32443, 6.606088885590856], [32575, 6.786295830104762], [32587, 6.567868153361802], [32599, 8.080078044937592], [32611, 8.112280720755777], [32623, 8.41507452484582], [32635, 8.726290978890818], [32647, 8.520276999607926], [32659, 8.501691743575307], [32839, 8.208061054159], [32851, 7.848647959911696], [32863, 8.02809332704312], [32875, 7.783293267926982], [32887, 7.762957086367041], [32899, 7.992214971759301], [32911, 7.634705608836725], [32923, 7.917408531317043], [32995, 8.01953320753667], [33007, 7.947609208411921], [33019, 7.972952288520954], [33031, 8.08205865145795], [33043, 8.084825067419855], [33055, 7.668771310110769], [33067, 8.241365822343125], [33079, 7.933817648265456], [33091, 8.051573025471853], [33103, 8.088857820368837], [33115, 8.108911157710278], [33127, 8.022571867912061], [33139, 8.154411107941993], [33151, 8.08103527066536], [33187, 7.931640204123595], [33199, 8.167030349376613], [33211, 7.868155912044196], [33223, 7.602845155718725], [33235, 6.843189765289497], [33271, 5.816390990524681], [33307, 6.639977464278246], [33319, 5.604529393984155], [33331, 5.599551844704078], [33343, 5.6760994381960606], [33355, 5.486591941892391], [33367, 5.781778231667307], [33379, 5.490166151008033], [33391, 5.704264882757089], [33403, 5.425321367956283], [33415, 5.526833690680481], [33427, 5.5989857441717605], [33439, 5.791551973377795], [33451, 5.372076413693631], [33463, 5.802061594681834], [33523, 5.70669197689057], [33535, 5.651384935996627], [33547, 5.695863005266683], [33559, 33.08641072102611], [33655, 31.62857173589212], [33715, 31.971504768157075], [33727, 18.454815149820504], [33739, 5.890593977516335], [33763, 5.833576288391502], [33775, 5.9394886858219555], [33811, 5.743202899885525], [33823, 5.678940357809824], [33835, 5.722769389042298], [34039, 33.094462839304185], [34051, 30.97466923695363], [34063, 32.35237615966909], [34075, 34.304509737424176], [34087, 32.85419273234811], [34123, 5.609494562402578], [34135, 5.672453622203122], [34147, 5.556491277766791], [34159, 5.58195525339163], [34171, 5.704075140968928]] \ No newline at end of file diff --git a/graphs/summary/ensemble.RandomForestClassifierBenchmark.time_predict.json b/graphs/summary/ensemble.RandomForestClassifierBenchmark.time_predict.json index 6463544f52..632b049cc9 100644 --- a/graphs/summary/ensemble.RandomForestClassifierBenchmark.time_predict.json +++ b/graphs/summary/ensemble.RandomForestClassifierBenchmark.time_predict.json @@ -1 +1 @@ -[[29227, 0.48070633192161927], [29239, 0.48387655744627495], [29251, 0.27340220267175647], [29263, 0.2756250977209125], [29287, 0.27627068856900117], [29299, 0.27502844386183256], [29323, 0.2746573848139762], [29335, 0.2718507389019185], [29347, 0.27111330597718475], [29359, 0.27167039953703026], [29371, 0.2663841061944605], [29383, 0.27421903606187387], [29395, 0.2735717702245414], [29407, 0.2721602024917552], [29419, 0.27087866860433446], [29431, 0.2743758368394032], [29443, 0.5038061820174042], [29455, 0.5228208729996666], [29467, 0.5379908438692107], [29479, 0.5294408753372166], [29551, 0.5240536205006828], [29563, 0.46045188313711954], [29575, 0.45229212328530355], [29599, 0.444259969441421], [29611, 0.46187402754357604], [29623, 0.45165638187906765], [29647, 0.4556107336986363], [29659, 0.44345518226656455], [29671, 0.45067042182268224], [29743, 0.45787798754151565], [29755, 0.46270274422566715], [29767, 0.46080966584209787], [29779, 0.5422372310523359], [29791, 0.4809091703603008], [29803, 0.47402051338972073], [29815, 0.4934847737221061], [29827, 0.49476658507131477], [29839, 0.5206540668955181], [29851, 0.4785248684337292], [29863, 0.4740801942391524], [29875, 0.4808525220990037], [30007, 0.49820185338950906], [30019, 0.48574649270781534], [30031, 0.5022527792770359], [30043, 0.4960472205471138], [30055, 0.4887050241828028], [30067, 0.48950415519881124], [30079, 0.4907708926330434], [30091, 0.48691098683384226], [30103, 0.524261043820581], [30115, 0.5007159047812254], [30127, 0.50077619550458], [30139, 0.489309319289818], [30151, 0.48492293811068515], [30163, 0.5018745089316686], [30175, 0.5010432493648982], [30187, 0.4808193596906086], [30199, 0.478911007438513], [30211, 0.4900588376439192], [30223, 0.5022189673977462], [30235, 0.49247042754294973], [30247, 0.4909055420873953], [30259, 0.5124722905892711], [30271, 0.5010951131464347], [30511, 0.4973614401411563], [30523, 0.4976023989743406], [30535, 0.4898105838122373], [30547, 0.49159839278558176], [30559, 0.48682142819167934], [30571, 0.491922200998939], [30583, 0.5040512252708077], [30595, 0.4841043696898755], [30619, 0.4998884715164155], [30631, 0.4946214958366477], [30643, 0.4965632959732109], [30655, 0.49585911483150097], [30667, 0.49821626926971807], [30679, 0.4908858530691943], [30691, 0.5075413407852248], [30703, 0.5136972184987284], [30715, 0.48407816102975587], [30727, 0.49578348020890406], [30739, 0.4960182086234887], [30751, 0.48916818884980806], [30763, 0.49696006032345635], [30787, 0.4874985180242784], [30799, 0.49798281040207815], [30811, 0.4822123557663096], [30823, 0.4912243079590617], [30847, 0.5071949282940682], [30859, 0.46586238578520994], [30871, 0.499383448828479], [30883, 0.5227132176575371], [30895, 0.4788087832180249], [30907, 0.4993454748486299], [30919, 0.5119081903606247], [30931, 0.49531268578381454], [30943, 0.4765636486162115], [30955, 0.49951672380239576], [30967, 0.48892245504133147], [30979, 0.5052006182060708], [30991, 0.4918622862024654], [31003, 0.48610396827973884], [31015, 0.5042510671141509], [31027, 0.5229981365517798], [31039, 0.5072370829986507], [31051, 0.4864419973036332], [32095, 0.505874073265043], [32107, 0.48834231478543694], [32119, 0.4829320759874031], [32131, 0.5021011393596719], [32143, 0.49241473336605734], [32155, 0.48773617922394796], [32167, 0.5011253745556195], [32179, 0.47188177106016044], [32191, 0.48949531982169153], [32203, 0.48355454877428267], [32215, 0.48878341512720314], [32227, 0.4793586946561212], [32251, 0.4670179465219596], [32263, 0.46716345078422583], [32275, 0.4724101618099499], [32299, 0.4790807546074044], [32311, 0.47009826928814763], [32323, 0.48258583135862293], [32335, 0.45748030901022274], [32347, 0.4714531247699658], [32359, 0.46960233483282077], [32371, 0.4748974733574732], [32383, 0.4779390184998111], [32395, 0.48835698415702283], [32407, 0.4972688340148824], [32419, 0.47235072513541027], [32431, 0.4763833019304933], [32443, 0.48913149774381726], [32575, 0.4966271835029826], [32587, 0.48096981986504733], [32599, 0.4858639603544617], [32611, 0.48528769513251246], [32623, 0.49093616056741196], [32635, 0.47720393650514104], [32647, 0.4751621503381899], [32659, 0.47795351787218554], [32839, 0.47527181248319594], [32851, 0.4746246462345243], [32863, 0.4793089019223477], [32875, 0.48818343810648684], [32887, 0.466235531408531], [32899, 0.47022100727849087], [32911, 0.4554726602539842], [32923, 0.4933718183243493], [32995, 0.47773466664746284], [33007, 0.4653475414653391], [33019, 0.4908413021350605], [33031, 0.47406737864041815], [33043, 0.4685945292731537], [33055, 0.463523571437405], [33067, 0.49043211970003364], [33079, 0.4683778235189235], [33091, 0.46525068291774907], [33103, 0.4673916145672043], [33115, 0.4740732608818375], [33127, 0.5010398974438287], [33139, 0.47985528483114515], [33151, 0.4877977884091903], [33187, 0.46569648259984897], [33199, 0.47144449339002037], [33211, 0.47656244885213295], [33223, 0.4646607711946152], [33235, 0.46533453341345404], [33271, 0.4620046328152006], [33307, 0.48489460551628627], [33319, 0.470468709862092], [33331, 0.46053836312964397], [33343, 0.47399421734268044], [33355, 0.4830099614866952], [33367, 0.46064707461654925], [33379, 0.4760344504029531], [33391, 0.46736434470412064], [33403, 0.47068643681178524], [33415, 0.47429813253497105], [33427, 0.4668252622563845], [33439, 0.4824932124710022], [33451, 0.4715027273883254], [33463, 0.49486077427698544], [33523, 0.49043173774857307], [33535, 0.488557237152897], [33547, 0.491088009428777], [33559, 0.48631332530564375], [33655, 0.49318333786038787], [33715, 0.49518231835894366], [33727, 0.5034663547476763], [33739, 0.49679389906570126], [33763, 0.48580650459335295], [33775, 0.5131024212932289], [33811, 0.5193118641563188], [33823, 0.49679268043960095], [33835, 0.5052660256978428], [34039, 0.5018452279361533], [34051, 0.49832607912496796], [34063, 0.5085778957619342], [34075, 0.5155958319596511], [34087, 0.5188014884638852], [34123, 0.5037957201706753], [34135, 0.5001301595424444], [34147, 0.5176687394341588], [34159, 0.5148830463221223], [34171, 0.5078586359616518]] \ No newline at end of file +[[29227, 0.48070633192161927], [29239, 0.48387655744627495], [29251, 0.27340220267175647], [29263, 0.2756250977209125], [29287, 0.27627068856900117], [29299, 0.27502844386183256], [29323, 0.2746573848139762], [29335, 0.2718507389019185], [29347, 0.27111330597718475], [29359, 0.27167039953703026], [29371, 0.2663841061944605], [29383, 0.27421903606187387], [29395, 0.2735717702245414], [29407, 0.2721602024917552], [29419, 0.27087866860433446], [29431, 0.2743758368394032], [29443, 0.5038061820174042], [29455, 0.5228208729996666], [29467, 0.5379908438692107], [29479, 0.5294408753372166], [29551, 0.5240536205006828], [29563, 0.46045188313711954], [29575, 0.45229212328530355], [29599, 0.444259969441421], [29611, 0.46187402754357604], [29623, 0.45165638187906765], [29647, 0.4556107336986363], [29659, 0.44345518226656455], [29671, 0.45067042182268224], [29743, 0.45787798754151565], [29755, 0.46270274422566715], [29767, 0.46080966584209787], [29779, 0.5422372310523359], [29791, 0.4809091703603008], [29803, 0.47402051338972073], [29815, 0.4934847737221061], [29827, 0.49476658507131477], [29839, 0.5206540668955181], [29851, 0.4785248684337292], [29863, 0.4740801942391524], [29875, 0.4808525220990037], [30007, 0.49820185338950906], [30019, 0.48574649270781534], [30031, 0.5022527792770359], [30043, 0.4960472205471138], [30055, 0.4887050241828028], [30067, 0.48950415519881124], [30079, 0.4907708926330434], [30091, 0.48691098683384226], [30103, 0.524261043820581], [30115, 0.5007159047812254], [30127, 0.50077619550458], [30139, 0.489309319289818], [30151, 0.48492293811068515], [30163, 0.5018745089316686], [30175, 0.5010432493648982], [30187, 0.4808193596906086], [30199, 0.478911007438513], [30211, 0.4900588376439192], [30223, 0.5022189673977462], [30235, 0.49247042754294973], [30247, 0.4909055420873953], [30259, 0.5124722905892711], [30271, 0.5010951131464347], [30511, 0.4973614401411563], [30523, 0.4976023989743406], [30535, 0.4898105838122373], [30547, 0.49159839278558176], [30559, 0.48682142819167934], [30571, 0.491922200998939], [30583, 0.5040512252708077], [30595, 0.4841043696898755], [30619, 0.4998884715164155], [30631, 0.4946214958366477], [30643, 0.4965632959732109], [30655, 0.49585911483150097], [30667, 0.49821626926971807], [30679, 0.4908858530691943], [30691, 0.5075413407852248], [30703, 0.5136972184987284], [30715, 0.48407816102975587], [30727, 0.49578348020890406], [30739, 0.4960182086234887], [30751, 0.48916818884980806], [30763, 0.49696006032345635], [30787, 0.4874985180242784], [30799, 0.49798281040207815], [30811, 0.4822123557663096], [30823, 0.4912243079590617], [30847, 0.5071949282940682], [30859, 0.46586238578520994], [30871, 0.499383448828479], [30883, 0.5227132176575371], [30895, 0.4788087832180249], [30907, 0.4993454748486299], [30919, 0.5119081903606247], [30931, 0.49531268578381454], [30943, 0.4765636486162115], [30955, 0.49951672380239576], [30967, 0.48892245504133147], [30979, 0.5052006182060708], [30991, 0.4918622862024654], [31003, 0.48610396827973884], [31015, 0.5042510671141509], [31027, 0.5229981365517798], [31039, 0.5072370829986507], [31051, 0.4864419973036332], [32095, 0.505874073265043], [32107, 0.48834231478543694], [32119, 0.4829320759874031], [32131, 0.5021011393596719], [32143, 0.49241473336605734], [32155, 0.48773617922394796], [32167, 0.5011253745556195], [32179, 0.47188177106016044], [32191, 0.48949531982169153], [32203, 0.48355454877428267], [32215, 0.48878341512720314], [32227, 0.4793586946561212], [32251, 0.4670179465219596], [32263, 0.46716345078422583], [32275, 0.4724101618099499], [32299, 0.4790807546074044], [32311, 0.47009826928814763], [32323, 0.48258583135862293], [32335, 0.45748030901022274], [32347, 0.4714531247699658], [32359, 0.46960233483282077], [32371, 0.4748974733574732], [32383, 0.4779390184998111], [32395, 0.48835698415702283], [32407, 0.4972688340148824], [32419, 0.47235072513541027], [32431, 0.4763833019304933], [32443, 0.48913149774381726], [32575, 0.4966271835029826], [32587, 0.48096981986504733], [32599, 0.4858639603544617], [32611, 0.48528769513251246], [32623, 0.49093616056741196], [32635, 0.47720393650514104], [32647, 0.4751621503381899], [32659, 0.47795351787218554], [32839, 0.47527181248319594], [32851, 0.4746246462345243], [32863, 0.4793089019223477], [32875, 0.48818343810648684], [32887, 0.466235531408531], [32899, 0.47022100727849087], [32911, 0.4554726602539842], [32923, 0.4933718183243493], [32995, 0.47773466664746284], [33007, 0.4653475414653391], [33019, 0.4908413021350605], [33031, 0.47406737864041815], [33043, 0.4685945292731537], [33055, 0.463523571437405], [33067, 0.49043211970003364], [33079, 0.4683778235189235], [33091, 0.46525068291774907], [33103, 0.4673916145672043], [33115, 0.4740732608818375], [33127, 0.5010398974438287], [33139, 0.47985528483114515], [33151, 0.4877977884091903], [33187, 0.46569648259984897], [33199, 0.47144449339002037], [33211, 0.47656244885213295], [33223, 0.4646607711946152], [33235, 0.46533453341345404], [33271, 0.4620046328152006], [33307, 0.48489460551628627], [33319, 0.470468709862092], [33331, 0.46053836312964397], [33343, 0.47399421734268044], [33355, 0.4830099614866952], [33367, 0.46064707461654925], [33379, 0.4760344504029531], [33391, 0.46736434470412064], [33403, 0.47068643681178524], [33415, 0.47429813253497105], [33427, 0.4668252622563845], [33439, 0.4824932124710022], [33451, 0.4715027273883254], [33463, 0.49486077427698544], [33523, 0.49043173774857307], [33535, 0.488557237152897], [33547, 0.491088009428777], [33559, 0.48631332530564375], [33655, 0.49318333786038787], [33715, 0.49518231835894366], [33727, 0.5034663547476763], [33739, 0.49679389906570126], [33763, 0.48580650459335295], [33775, 0.5131024212932289], [33811, 0.5193118641563188], [33823, 0.49679268043960095], [33835, 0.5052660256978428], [34039, 0.5018452279361533], [34051, 0.49832607912496796], [34063, 0.5085778957619342], [34075, 0.5155958319596511], [34087, 0.5188014884638852], [34123, 0.5037957201706753], [34135, 0.5001301595424444], [34147, 0.5176687394341588], [34159, 0.5148830463221223], [34171, 0.5080776939057106]] \ No newline at end of file diff --git a/graphs/summary/ensemble.RandomForestClassifierBenchmark.track_test_score.json b/graphs/summary/ensemble.RandomForestClassifierBenchmark.track_test_score.json index fc5e41c117..2a4a42e6e4 100644 --- a/graphs/summary/ensemble.RandomForestClassifierBenchmark.track_test_score.json +++ b/graphs/summary/ensemble.RandomForestClassifierBenchmark.track_test_score.json @@ -1 +1 @@ -[[29227, 0.8091879779378292], [29239, 0.8058169222583781], [29251, 0.8023424138958895], [29263, 0.8069922343802204], [29287, 0.8073974316333994], [29299, 0.8080773172492276], [29323, 0.8062989246804774], [29335, 0.8052407759291804], [29347, 0.8062248725913632], [29359, 0.8113932485642692], [29371, 0.80701405855544], [29383, 0.8058153138042953], [29395, 0.8031703820395347], [29407, 0.8045852225292319], [29419, 0.8078569963113927], [29431, 0.8043907331299313], [29443, 0.80367872497261], [29455, 0.8039019052674025], [29467, 0.8083040366850929], [29479, 0.8113009018320206], [29551, 0.806488697087691], [29563, 0.8099386932279989], [29575, 0.8070581377518103], [29599, 0.8099329904864926], [29611, 0.8053834394091318], [29623, 0.8004251378098883], [29647, 0.8037925779640638], [29659, 0.8052510753341379], [29671, 0.8044698602745766], [29743, 0.8079809354851806], [29755, 0.8102376595420246], [29767, 0.8052717392905945], [29779, 0.8094076862928625], [29791, 0.8055526540735141], [29803, 0.8049537910123253], [29815, 0.8050264232436584], [29827, 0.8055526778360115], [29839, 0.8093737426906559], [29851, 0.8019103918485169], [29863, 0.8043290057985241], [29875, 0.8033664312678546], [30007, 0.8078053641920582], [30019, 0.8058607479677904], [30031, 0.8047452038353446], [30043, 0.8033059149099224], [30055, 0.8040889946918044], [30067, 0.8058241844700816], [30079, 0.8073916289819053], [30091, 0.8042176468126203], [30103, 0.812562501210878], [30115, 0.80805942503001], [30127, 0.8070560756968349], [30139, 0.8055739170633635], [30151, 0.8043883867679558], [30163, 0.8032753038924944], [30175, 0.8090948018432519], [30187, 0.8052394244218144], [30199, 0.8050377077523777], [30211, 0.8049317617299127], [30223, 0.8060981399088958], [30235, 0.8021749713732474], [30247, 0.8053104283987839], [30259, 0.808152165061881], [30271, 0.8102932228188653], [30511, 0.8081406270742784], [30523, 0.8059966903753272], [30535, 0.8064903819357677], [30547, 0.8050271662618573], [30559, 0.8095393991095042], [30571, 0.8054887409144214], [30583, 0.8091803082402753], [30595, 0.8092760428051038], [30619, 0.8070213013984234], [30631, 0.8068453541195626], [30643, 0.8056764799853603], [30655, 0.8040022428659886], [30667, 0.8052132833862851], [30679, 0.8039322714529187], [30691, 0.8077263319405555], [30703, 0.8080507752013683], [30715, 0.8041931303501566], [30727, 0.8040636291655835], [30739, 0.8066709380005457], [30751, 0.8093658931411287], [30763, 0.8065273584611895], [30787, 0.806939958857614], [30799, 0.8114694075321675], [30811, 0.8027970715317005], [30823, 0.808970242402324], [30847, 0.8078485414702115], [30859, 0.8086421728989098], [30871, 0.8086553220125863], [30883, 0.8140385244728083], [30895, 0.8086405726136916], [30907, 0.8024660794118027], [30919, 0.805900641113408], [30931, 0.8097161139681947], [30943, 0.8079320735045756], [30955, 0.8065217491519903], [30967, 0.8049356696286152], [30979, 0.8031409888170898], [30991, 0.8097381977513488], [31003, 0.8119545132743426], [31015, 0.8082884063365707], [31027, 0.8103408264878944], [31039, 0.802773172260243], [31051, 0.8062965960117844], [32095, 0.8070571214095682], [32107, 0.8067479309436674], [32119, 0.805324211972109], [32131, 0.8031758647441136], [32143, 0.8035577948155721], [32155, 0.8083011871307688], [32167, 0.8081060291199306], [32179, 0.8074749670869036], [32191, 0.8010121918507235], [32203, 0.8055341152997029], [32215, 0.8058274685989], [32227, 0.8048966340274183], [32251, 0.8046587733168582], [32263, 0.8095842875507456], [32275, 0.8079363961852225], [32299, 0.8044981473967896], [32311, 0.8038764054262599], [32323, 0.7986630072228169], [32335, 0.8067500034377788], [32347, 0.8047973027701434], [32359, 0.8084040285635328], [32371, 0.811151431083598], [32383, 0.8110984677777151], [32395, 0.8029571480357939], [32407, 0.8100094171552412], [32419, 0.8065213769260673], [32431, 0.8061873352212002], [32443, 0.8164568504368943], [32575, 0.8080905160892853], [32587, 0.8069458483583892], [32599, 0.8064993503227463], [32611, 0.8067832206147402], [32623, 0.80879046086143], [32635, 0.804211445839886], [32647, 0.8028234656232203], [32659, 0.8100632023299976], [32839, 0.8067811385509064], [32851, 0.8045288363233183], [32863, 0.8058885031957856], [32875, 0.8041681315057326], [32887, 0.8024216815571577], [32899, 0.8062693710777646], [32911, 0.8020376931572418], [32923, 0.8091774444737307], [32995, 0.81324901327617], [33007, 0.808890818966964], [33019, 0.8035590249303491], [33031, 0.8052826688257965], [33043, 0.8083597673766173], [33055, 0.8057325380734567], [33067, 0.8069544591149768], [33079, 0.8103559481988503], [33091, 0.804975653936961], [33103, 0.8094431872002195], [33115, 0.8094646846334279], [33127, 0.8142306725023118], [33139, 0.8035483634482556], [33151, 0.8004732227227473], [33187, 0.8097749102906392], [33199, 0.8070243554873024], [33211, 0.8041459986141813], [33223, 0.8066400857032592], [33235, 0.8057880541530192], [33271, 0.8066439105244355], [33307, 0.8033215904631477], [33319, 0.8046933041741745], [33331, 0.817503427258315], [33343, 0.8047918601817141], [33355, 0.8071517894182657], [33367, 0.8044855200874723], [33379, 0.8071617219409197], [33391, 0.8052817698605143], [33403, 0.8067213620468738], [33415, 0.8145098595884697], [33427, 0.807636750028149], [33439, 0.8062770049385486], [33451, 0.8092282741414265], [33463, 0.8059030321231287], [33523, 0.8084113542638163], [33535, 0.8086185685894567], [33547, 0.8064573029634827], [33559, 0.8054932229838616], [33655, 0.8022763856555649], [33715, 0.8053687983943603], [33727, 0.8050184229944607], [33739, 0.8074606628861649], [33763, 0.8063761211583589], [33775, 0.8056087237500089], [33811, 0.8051070461421655], [33823, 0.8122674228183119], [33835, 0.8022775454040072], [34039, 0.8055846253008878], [34051, 0.8108861984968135], [34063, 0.8127848475216588], [34075, 0.8049780546807059], [34087, 0.8040736043508079], [34123, 0.8034049019817409], [34135, 0.8124402635332886], [34147, 0.8055029070646028], [34159, 0.8048718450025687], [34171, 0.8035319018620999]] \ No newline at end of file +[[29227, 0.8091879779378292], [29239, 0.8058169222583781], [29251, 0.8023424138958895], [29263, 0.8069922343802204], [29287, 0.8073974316333994], [29299, 0.8080773172492276], [29323, 0.8062989246804774], [29335, 0.8052407759291804], [29347, 0.8062248725913632], [29359, 0.8113932485642692], [29371, 0.80701405855544], [29383, 0.8058153138042953], [29395, 0.8031703820395347], [29407, 0.8045852225292319], [29419, 0.8078569963113927], [29431, 0.8043907331299313], [29443, 0.80367872497261], [29455, 0.8039019052674025], [29467, 0.8083040366850929], [29479, 0.8113009018320206], [29551, 0.806488697087691], [29563, 0.8099386932279989], [29575, 0.8070581377518103], [29599, 0.8099329904864926], [29611, 0.8053834394091318], [29623, 0.8004251378098883], [29647, 0.8037925779640638], [29659, 0.8052510753341379], [29671, 0.8044698602745766], [29743, 0.8079809354851806], [29755, 0.8102376595420246], [29767, 0.8052717392905945], [29779, 0.8094076862928625], [29791, 0.8055526540735141], [29803, 0.8049537910123253], [29815, 0.8050264232436584], [29827, 0.8055526778360115], [29839, 0.8093737426906559], [29851, 0.8019103918485169], [29863, 0.8043290057985241], [29875, 0.8033664312678546], [30007, 0.8078053641920582], [30019, 0.8058607479677904], [30031, 0.8047452038353446], [30043, 0.8033059149099224], [30055, 0.8040889946918044], [30067, 0.8058241844700816], [30079, 0.8073916289819053], [30091, 0.8042176468126203], [30103, 0.812562501210878], [30115, 0.80805942503001], [30127, 0.8070560756968349], [30139, 0.8055739170633635], [30151, 0.8043883867679558], [30163, 0.8032753038924944], [30175, 0.8090948018432519], [30187, 0.8052394244218144], [30199, 0.8050377077523777], [30211, 0.8049317617299127], [30223, 0.8060981399088958], [30235, 0.8021749713732474], [30247, 0.8053104283987839], [30259, 0.808152165061881], [30271, 0.8102932228188653], [30511, 0.8081406270742784], [30523, 0.8059966903753272], [30535, 0.8064903819357677], [30547, 0.8050271662618573], [30559, 0.8095393991095042], [30571, 0.8054887409144214], [30583, 0.8091803082402753], [30595, 0.8092760428051038], [30619, 0.8070213013984234], [30631, 0.8068453541195626], [30643, 0.8056764799853603], [30655, 0.8040022428659886], [30667, 0.8052132833862851], [30679, 0.8039322714529187], [30691, 0.8077263319405555], [30703, 0.8080507752013683], [30715, 0.8041931303501566], [30727, 0.8040636291655835], [30739, 0.8066709380005457], [30751, 0.8093658931411287], [30763, 0.8065273584611895], [30787, 0.806939958857614], [30799, 0.8114694075321675], [30811, 0.8027970715317005], [30823, 0.808970242402324], [30847, 0.8078485414702115], [30859, 0.8086421728989098], [30871, 0.8086553220125863], [30883, 0.8140385244728083], [30895, 0.8086405726136916], [30907, 0.8024660794118027], [30919, 0.805900641113408], [30931, 0.8097161139681947], [30943, 0.8079320735045756], [30955, 0.8065217491519903], [30967, 0.8049356696286152], [30979, 0.8031409888170898], [30991, 0.8097381977513488], [31003, 0.8119545132743426], [31015, 0.8082884063365707], [31027, 0.8103408264878944], [31039, 0.802773172260243], [31051, 0.8062965960117844], [32095, 0.8070571214095682], [32107, 0.8067479309436674], [32119, 0.805324211972109], [32131, 0.8031758647441136], [32143, 0.8035577948155721], [32155, 0.8083011871307688], [32167, 0.8081060291199306], [32179, 0.8074749670869036], [32191, 0.8010121918507235], [32203, 0.8055341152997029], [32215, 0.8058274685989], [32227, 0.8048966340274183], [32251, 0.8046587733168582], [32263, 0.8095842875507456], [32275, 0.8079363961852225], [32299, 0.8044981473967896], [32311, 0.8038764054262599], [32323, 0.7986630072228169], [32335, 0.8067500034377788], [32347, 0.8047973027701434], [32359, 0.8084040285635328], [32371, 0.811151431083598], [32383, 0.8110984677777151], [32395, 0.8029571480357939], [32407, 0.8100094171552412], [32419, 0.8065213769260673], [32431, 0.8061873352212002], [32443, 0.8164568504368943], [32575, 0.8080905160892853], [32587, 0.8069458483583892], [32599, 0.8064993503227463], [32611, 0.8067832206147402], [32623, 0.80879046086143], [32635, 0.804211445839886], [32647, 0.8028234656232203], [32659, 0.8100632023299976], [32839, 0.8067811385509064], [32851, 0.8045288363233183], [32863, 0.8058885031957856], [32875, 0.8041681315057326], [32887, 0.8024216815571577], [32899, 0.8062693710777646], [32911, 0.8020376931572418], [32923, 0.8091774444737307], [32995, 0.81324901327617], [33007, 0.808890818966964], [33019, 0.8035590249303491], [33031, 0.8052826688257965], [33043, 0.8083597673766173], [33055, 0.8057325380734567], [33067, 0.8069544591149768], [33079, 0.8103559481988503], [33091, 0.804975653936961], [33103, 0.8094431872002195], [33115, 0.8094646846334279], [33127, 0.8142306725023118], [33139, 0.8035483634482556], [33151, 0.8004732227227473], [33187, 0.8097749102906392], [33199, 0.8070243554873024], [33211, 0.8041459986141813], [33223, 0.8066400857032592], [33235, 0.8057880541530192], [33271, 0.8066439105244355], [33307, 0.8033215904631477], [33319, 0.8046933041741745], [33331, 0.817503427258315], [33343, 0.8047918601817141], [33355, 0.8071517894182657], [33367, 0.8044855200874723], [33379, 0.8071617219409197], [33391, 0.8052817698605143], [33403, 0.8067213620468738], [33415, 0.8145098595884697], [33427, 0.807636750028149], [33439, 0.8062770049385486], [33451, 0.8092282741414265], [33463, 0.8059030321231287], [33523, 0.8084113542638163], [33535, 0.8086185685894567], [33547, 0.8064573029634827], [33559, 0.8054932229838616], [33655, 0.8022763856555649], [33715, 0.8053687983943603], [33727, 0.8050184229944607], [33739, 0.8074606628861649], [33763, 0.8063761211583589], [33775, 0.8056087237500089], [33811, 0.8051070461421655], [33823, 0.8122674228183119], [33835, 0.8022775454040072], [34039, 0.8055846253008878], [34051, 0.8108861984968135], [34063, 0.8127848475216588], [34075, 0.8049780546807059], [34087, 0.8040736043508079], [34123, 0.8034049019817409], [34135, 0.8124402635332886], [34147, 0.8055029070646028], [34159, 0.8048718450025687], [34171, 0.8045238050157826]] \ No newline at end of file diff --git a/graphs/summary/ensemble.RandomForestClassifierBenchmark.track_train_score.json b/graphs/summary/ensemble.RandomForestClassifierBenchmark.track_train_score.json index 61176e6d36..ceafaaa437 100644 --- a/graphs/summary/ensemble.RandomForestClassifierBenchmark.track_train_score.json +++ b/graphs/summary/ensemble.RandomForestClassifierBenchmark.track_train_score.json @@ -1 +1 @@ -[[29227, 0.9982128223207863], [29239, 0.9981717343868488], [29251, 0.9981638485215028], [29263, 0.998270672720736], [29287, 0.99824446801637], [29299, 0.9984066301250377], [29323, 0.9982679769470406], [29335, 0.9982356393910243], [29347, 0.9981363885632176], [29359, 0.9983985460144681], [29371, 0.9983460261494365], [29383, 0.9982995112612197], [29395, 0.9981426489638346], [29407, 0.9982509844403888], [29419, 0.9982672561366241], [29431, 0.9982412094397943], [29443, 0.9981314894974078], [29455, 0.9981551672729049], [29467, 0.9982709089578637], [29479, 0.9979998512576577], [29551, 0.998278518508045], [29563, 0.9979169041151009], [29575, 0.9984422847107086], [29599, 0.998125637863502], [29611, 0.9980419345143438], [29623, 0.9984674376564064], [29647, 0.9982538857533398], [29659, 0.9981081619327529], [29671, 0.9981019766009386], [29743, 0.99838474718206], [29755, 0.9981973042611412], [29767, 0.9982390447077052], [29779, 0.9981502909097575], [29791, 0.9985682385906853], [29803, 0.9982152583196604], [29815, 0.9982285688159415], [29827, 0.9985110043140707], [29839, 0.9981699909595628], [29851, 0.9981167786104405], [29863, 0.9982927599048855], [29875, 0.9983087974914427], [30007, 0.9981203127537028], [30019, 0.9983115097059343], [30031, 0.9980781637453309], [30043, 0.9982040694370963], [30055, 0.9982769859795757], [30067, 0.9983276266306713], [30079, 0.9983966213061083], [30091, 0.9980180549939413], [30103, 0.9983102514171941], [30115, 0.9982102018004072], [30127, 0.9981653256082205], [30139, 0.9982896165835028], [30151, 0.9981399189863996], [30163, 0.998222702163773], [30175, 0.9983492583530276], [30187, 0.998444637319641], [30199, 0.998400524481978], [30211, 0.9982419445632346], [30223, 0.9982719478160911], [30235, 0.9983670400680071], [30247, 0.9981750811091511], [30259, 0.9981188177475517], [30271, 0.9981758147499209], [30511, 0.9982227108238846], [30523, 0.9982021756197788], [30535, 0.9981152803283007], [30547, 0.9983929027467313], [30559, 0.9982584052251212], [30571, 0.9980768323216055], [30583, 0.9982447697785146], [30595, 0.9981904280796641], [30619, 0.9982077371649282], [30631, 0.9983568766418579], [30643, 0.9985155725257545], [30655, 0.9983579656707694], [30667, 0.9981513624754427], [30679, 0.9981904205601817], [30691, 0.9978834948471417], [30703, 0.9984232634296883], [30715, 0.9983694699931902], [30727, 0.9982914541690031], [30739, 0.9981609276400775], [30751, 0.9982149965992226], [30763, 0.9982594700793438], [30787, 0.9981835072756803], [30799, 0.9981395230386909], [30811, 0.9982322213371667], [30823, 0.9983458551404434], [30847, 0.9981711240534392], [30859, 0.9981750586077911], [30871, 0.9982186954353182], [30883, 0.9981842371006716], [30895, 0.9981668233691046], [30907, 0.9984258717501052], [30919, 0.9983994347614099], [30931, 0.9982405707589728], [30943, 0.9984343799351405], [30955, 0.9982354637961708], [30967, 0.9981596696212057], [30979, 0.9982316824719201], [30991, 0.998333124335345], [31003, 0.9983286953064758], [31015, 0.9985658612748527], [31027, 0.9983895990679543], [31039, 0.9982244223910789], [31051, 0.9983815960788694], [32095, 0.9981868907655636], [32107, 0.9980653343945345], [32119, 0.9981486980029725], [32131, 0.9981646803306172], [32143, 0.9985270761122994], [32155, 0.9981650942972653], [32167, 0.9983797062344659], [32179, 0.9982885382484061], [32191, 0.9982361288909786], [32203, 0.9981861432880413], [32215, 0.9982342368342599], [32227, 0.9980687570536845], [32251, 0.9984800302546576], [32263, 0.998353212900071], [32275, 0.9981595406607441], [32299, 0.998159278922079], [32311, 0.9983014716348183], [32323, 0.9984433485484606], [32335, 0.9985433615907887], [32347, 0.9982824060916591], [32359, 0.9981962189635145], [32371, 0.9984048385616227], [32383, 0.9983966622652478], [32395, 0.9982865251383147], [32407, 0.9982304827538139], [32419, 0.9981145229838572], [32431, 0.9982172548250094], [32443, 0.9983526489567592], [32575, 0.9980529691495201], [32587, 0.9980094256871714], [32599, 0.9985002071229516], [32611, 0.9981598230415368], [32623, 0.9982494237271522], [32635, 0.998399945919846], [32647, 0.998307831269468], [32659, 0.9981425573906937], [32839, 0.9981859208063583], [32851, 0.9984549720374452], [32863, 0.9980993688289658], [32875, 0.9983360904092398], [32887, 0.9985501861434528], [32899, 0.9980227066897169], [32911, 0.9983528266164421], [32923, 0.9983853260711789], [32995, 0.9984464031664708], [33007, 0.9977879997552984], [33019, 0.9983529701506842], [33031, 0.9982644839767291], [33043, 0.9981291488332593], [33055, 0.9982099009667237], [33067, 0.998275042798781], [33079, 0.9982744961954696], [33091, 0.9981291191180955], [33103, 0.9979762597144142], [33115, 0.9983064929873916], [33127, 0.9982054269283778], [33139, 0.9981007759610514], [33151, 0.9984119573019743], [33187, 0.9984142821493639], [33199, 0.9982222996194017], [33211, 0.9982944859964584], [33223, 0.998315472167439], [33235, 0.9983579307619044], [33271, 0.9983741827093787], [33307, 0.9984245604243414], [33319, 0.9983974470911663], [33331, 0.9982303816899951], [33343, 0.9982724565379444], [33355, 0.9983079084273769], [33367, 0.9982533637141531], [33379, 0.998280930604015], [33391, 0.9981320757254227], [33403, 0.9980962370019804], [33415, 0.9981141509560184], [33427, 0.9982139107942566], [33439, 0.9981851970600446], [33451, 0.9982568911961444], [33463, 0.9984867846420422], [33523, 0.9983294201350494], [33535, 0.9982801586418679], [33547, 0.9981023677526591], [33559, 0.9985883570484102], [33655, 0.9980160511103993], [33715, 0.998361698757867], [33727, 0.9982876630241335], [33739, 0.9984172489819625], [33763, 0.998155745594639], [33775, 0.9981926949529686], [33811, 0.9984361465630262], [33823, 0.9982638840374132], [33835, 0.998312726839129], [34039, 0.9981432072216794], [34051, 0.9982556356863106], [34063, 0.9984106534167275], [34075, 0.9982014712751377], [34087, 0.9982180380921305], [34123, 0.9981788611480438], [34135, 0.9982593507708366], [34147, 0.9982459291614818], [34159, 0.9983600142341136], [34171, 0.9983008771279716]] \ No newline at end of file +[[29227, 0.9982128223207863], [29239, 0.9981717343868488], [29251, 0.9981638485215028], [29263, 0.998270672720736], [29287, 0.99824446801637], [29299, 0.9984066301250377], [29323, 0.9982679769470406], [29335, 0.9982356393910243], [29347, 0.9981363885632176], [29359, 0.9983985460144681], [29371, 0.9983460261494365], [29383, 0.9982995112612197], [29395, 0.9981426489638346], [29407, 0.9982509844403888], [29419, 0.9982672561366241], [29431, 0.9982412094397943], [29443, 0.9981314894974078], [29455, 0.9981551672729049], [29467, 0.9982709089578637], [29479, 0.9979998512576577], [29551, 0.998278518508045], [29563, 0.9979169041151009], [29575, 0.9984422847107086], [29599, 0.998125637863502], [29611, 0.9980419345143438], [29623, 0.9984674376564064], [29647, 0.9982538857533398], [29659, 0.9981081619327529], [29671, 0.9981019766009386], [29743, 0.99838474718206], [29755, 0.9981973042611412], [29767, 0.9982390447077052], [29779, 0.9981502909097575], [29791, 0.9985682385906853], [29803, 0.9982152583196604], [29815, 0.9982285688159415], [29827, 0.9985110043140707], [29839, 0.9981699909595628], [29851, 0.9981167786104405], [29863, 0.9982927599048855], [29875, 0.9983087974914427], [30007, 0.9981203127537028], [30019, 0.9983115097059343], [30031, 0.9980781637453309], [30043, 0.9982040694370963], [30055, 0.9982769859795757], [30067, 0.9983276266306713], [30079, 0.9983966213061083], [30091, 0.9980180549939413], [30103, 0.9983102514171941], [30115, 0.9982102018004072], [30127, 0.9981653256082205], [30139, 0.9982896165835028], [30151, 0.9981399189863996], [30163, 0.998222702163773], [30175, 0.9983492583530276], [30187, 0.998444637319641], [30199, 0.998400524481978], [30211, 0.9982419445632346], [30223, 0.9982719478160911], [30235, 0.9983670400680071], [30247, 0.9981750811091511], [30259, 0.9981188177475517], [30271, 0.9981758147499209], [30511, 0.9982227108238846], [30523, 0.9982021756197788], [30535, 0.9981152803283007], [30547, 0.9983929027467313], [30559, 0.9982584052251212], [30571, 0.9980768323216055], [30583, 0.9982447697785146], [30595, 0.9981904280796641], [30619, 0.9982077371649282], [30631, 0.9983568766418579], [30643, 0.9985155725257545], [30655, 0.9983579656707694], [30667, 0.9981513624754427], [30679, 0.9981904205601817], [30691, 0.9978834948471417], [30703, 0.9984232634296883], [30715, 0.9983694699931902], [30727, 0.9982914541690031], [30739, 0.9981609276400775], [30751, 0.9982149965992226], [30763, 0.9982594700793438], [30787, 0.9981835072756803], [30799, 0.9981395230386909], [30811, 0.9982322213371667], [30823, 0.9983458551404434], [30847, 0.9981711240534392], [30859, 0.9981750586077911], [30871, 0.9982186954353182], [30883, 0.9981842371006716], [30895, 0.9981668233691046], [30907, 0.9984258717501052], [30919, 0.9983994347614099], [30931, 0.9982405707589728], [30943, 0.9984343799351405], [30955, 0.9982354637961708], [30967, 0.9981596696212057], [30979, 0.9982316824719201], [30991, 0.998333124335345], [31003, 0.9983286953064758], [31015, 0.9985658612748527], [31027, 0.9983895990679543], [31039, 0.9982244223910789], [31051, 0.9983815960788694], [32095, 0.9981868907655636], [32107, 0.9980653343945345], [32119, 0.9981486980029725], [32131, 0.9981646803306172], [32143, 0.9985270761122994], [32155, 0.9981650942972653], [32167, 0.9983797062344659], [32179, 0.9982885382484061], [32191, 0.9982361288909786], [32203, 0.9981861432880413], [32215, 0.9982342368342599], [32227, 0.9980687570536845], [32251, 0.9984800302546576], [32263, 0.998353212900071], [32275, 0.9981595406607441], [32299, 0.998159278922079], [32311, 0.9983014716348183], [32323, 0.9984433485484606], [32335, 0.9985433615907887], [32347, 0.9982824060916591], [32359, 0.9981962189635145], [32371, 0.9984048385616227], [32383, 0.9983966622652478], [32395, 0.9982865251383147], [32407, 0.9982304827538139], [32419, 0.9981145229838572], [32431, 0.9982172548250094], [32443, 0.9983526489567592], [32575, 0.9980529691495201], [32587, 0.9980094256871714], [32599, 0.9985002071229516], [32611, 0.9981598230415368], [32623, 0.9982494237271522], [32635, 0.998399945919846], [32647, 0.998307831269468], [32659, 0.9981425573906937], [32839, 0.9981859208063583], [32851, 0.9984549720374452], [32863, 0.9980993688289658], [32875, 0.9983360904092398], [32887, 0.9985501861434528], [32899, 0.9980227066897169], [32911, 0.9983528266164421], [32923, 0.9983853260711789], [32995, 0.9984464031664708], [33007, 0.9977879997552984], [33019, 0.9983529701506842], [33031, 0.9982644839767291], [33043, 0.9981291488332593], [33055, 0.9982099009667237], [33067, 0.998275042798781], [33079, 0.9982744961954696], [33091, 0.9981291191180955], [33103, 0.9979762597144142], [33115, 0.9983064929873916], [33127, 0.9982054269283778], [33139, 0.9981007759610514], [33151, 0.9984119573019743], [33187, 0.9984142821493639], [33199, 0.9982222996194017], [33211, 0.9982944859964584], [33223, 0.998315472167439], [33235, 0.9983579307619044], [33271, 0.9983741827093787], [33307, 0.9984245604243414], [33319, 0.9983974470911663], [33331, 0.9982303816899951], [33343, 0.9982724565379444], [33355, 0.9983079084273769], [33367, 0.9982533637141531], [33379, 0.998280930604015], [33391, 0.9981320757254227], [33403, 0.9980962370019804], [33415, 0.9981141509560184], [33427, 0.9982139107942566], [33439, 0.9981851970600446], [33451, 0.9982568911961444], [33463, 0.9984867846420422], [33523, 0.9983294201350494], [33535, 0.9982801586418679], [33547, 0.9981023677526591], [33559, 0.9985883570484102], [33655, 0.9980160511103993], [33715, 0.998361698757867], [33727, 0.9982876630241335], [33739, 0.9984172489819625], [33763, 0.998155745594639], [33775, 0.9981926949529686], [33811, 0.9984361465630262], [33823, 0.9982638840374132], [33835, 0.998312726839129], [34039, 0.9981432072216794], [34051, 0.9982556356863106], [34063, 0.9984106534167275], [34075, 0.9982014712751377], [34087, 0.9982180380921305], [34123, 0.9981788611480438], [34135, 0.9982593507708366], [34147, 0.9982459291614818], [34159, 0.9983600142341136], [34171, 0.9984179126103657]] \ No newline at end of file diff --git a/graphs/summary/linear_model.ElasticNetBenchmark.peakmem_fit.json b/graphs/summary/linear_model.ElasticNetBenchmark.peakmem_fit.json index 44402c385a..53bace7a68 100644 --- a/graphs/summary/linear_model.ElasticNetBenchmark.peakmem_fit.json +++ b/graphs/summary/linear_model.ElasticNetBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 494424263.887413], [29225, 490170871.055939], [29239, 490284944.20020884], [29253, 490315930.1156513], [29267, 490387395.0527699], [29281, 490667427.3060934], [29295, 490479165.1681075], [29309, 490523319.78962505], [29323, 490407198.6197065], [29337, 490818481.02114373], [29351, 489341139.0443334], [29365, 489223635.47283214], [29379, 489597665.0513499], [29393, 489554720.0681822], [29407, 489426300.94461143], [29421, 489355886.5133283], [29435, 490046942.8143584], [29449, 490034420.4031908], [29463, 490042805.3846796], [29477, 490054546.3421895], [29547, 490515057.5207555], [29561, 490181679.26916957], [29575, 489518617.0887432], [29603, 491427472.8485458], [29617, 491385022.86603177], [29631, 492124366.91416264], [29645, 491820418.7816124], [29659, 491614485.91588235], [29673, 491473237.71635365], [29743, 491520725.5310582], [29757, 491688286.35511076], [29771, 491495201.7953478], [29785, 491615678.42660713], [29799, 491798636.1467865], [29813, 491843017.549841], [29827, 492342121.58361894], [29841, 491709780.6076981], [29855, 491412706.4012351], [29869, 492014448.66533005], [30009, 491935027.3107256], [30023, 492014428.5637778], [30037, 491662312.3164708], [30051, 491432461.7935506], [30065, 491586183.7376458], [30079, 491574687.21584606], [30093, 491521353.2427809], [30107, 491582107.23116857], [30121, 491727408.783021], [30135, 491500142.61053854], [30149, 491863957.4758947], [30163, 492071665.14486694], [30177, 492508736.674651], [30191, 492367007.89785635], [30205, 492488350.9480216], [30219, 492409392.4534894], [30233, 492084868.753012], [30247, 492317903.8209429], [30261, 492035404.60846937], [30513, 492523813.47294456], [30527, 492473029.66459286], [30541, 492052664.241502], [30555, 491946370.41368866], [30569, 492055305.2983328], [30583, 492331174.0826049], [30597, 491832534.01285076], [30625, 492217878.26086354], [30639, 492433596.32682264], [30653, 492032463.0915225], [30667, 492827966.2071549], [30681, 493509729.2941611], [30695, 492064380.39266306], [30709, 492208978.6763617], [30723, 492060768.8395485], [30737, 492048251.9584497], [30751, 492242773.0866956], [30765, 492785804.459974], [30779, 492076357.37290674], [30793, 492253226.555851], [30807, 492516800.56512797], [30821, 492621538.16004086], [30835, 492957901.2181211], [30849, 492347025.3969089], [30863, 492383586.0263903], [30877, 492422581.237291], [30891, 492551070.5507549], [30905, 492212418.91397774], [30919, 492429119.0304291], [30933, 492555191.99969125], [30947, 492510362.3035923], [30961, 492494556.40690446], [30975, 492281704.53394055], [30989, 492405710.0694389], [31003, 492381486.5398134], [31017, 492580070.15731114], [31031, 492659350.25857234], [31045, 492442454.15958476], [32095, 512588479.39827573], [32109, 512260215.9267326], [32123, 512421925.4933093], [32137, 512311151.2337653], [32151, 512359970.8567891], [32165, 512476918.79389703], [32179, 512043372.0975828], [32193, 512507668.61841697], [32207, 514547926.96215034], [32221, 516915270.3453668], [32235, 517346786.4931783], [32249, 516653544.6721448], [32263, 516799961.0571027], [32277, 516811166.4210442], [32305, 518335990.14014554], [32319, 522089122.3098076], [32333, 522065980.45503575], [32347, 522112754.7915428], [32361, 522121721.8903518], [32375, 521762916.8393627], [32389, 521941787.8464575], [32403, 522088984.3191828], [32417, 521943658.4024407], [32431, 522119520.0507815], [32445, 522365380.2392815], [32585, 522615215.8080453], [32599, 522625637.56246656], [32613, 522701326.28549194], [32627, 522914486.94157034], [32641, 522654818.8376248], [32655, 522530248.7920552], [32851, 524008235.79285336], [32865, 524013456.50791776], [32879, 523978945.5572481], [32893, 524192672.9947045], [32907, 524063136.91513497], [32921, 523849159.9434005], [32991, 524160414.5254627], [33005, 524006100.1671411], [33019, 523464682.5605816], [33033, 523846302.158408], [33047, 524202533.5050022], [33061, 524451976.24919057], [33075, 524406025.1570502], [33089, 548368557.6986783], [33103, 572365259.7572279], [33117, 572524800.1164186], [33131, 571857378.4312959], [33145, 572761957.6024126], [33159, 572673118.2665321], [33187, 524942668.8242475], [33201, 524542603.18099856], [33215, 522593061.601383], [33229, 517240866.95237374], [33243, 517172104.6577132], [33271, 509212564.5710532], [33299, 509503812.1756981], [33313, 510039277.67950165], [33327, 510224585.93643636], [33341, 510389844.9443076], [33355, 510707914.53079504], [33369, 511491284.203759], [33383, 511965378.8368125], [33397, 512345903.47834444], [33411, 512562146.20958376], [33425, 512626571.69804466], [33439, 514218773.6070256], [33453, 506251468.6634176], [33467, 506278915.9513298], [33523, 506576054.9544816], [33537, 506723394.0697729], [33551, 505632996.88546044], [33649, 504399618.85944647], [33705, 503553133.4365413], [33719, 503960813.9002117], [33733, 503846900.0994794], [33747, 503590786.6335497], [33761, 504003254.3990458], [33775, 503735978.88996613], [33803, 504121063.3068522], [33817, 503388325.35863847], [33831, 503550630.417195], [33845, 503247233.708991], [34041, 503169123.6753149], [34055, 503462425.74773973], [34069, 503404619.9208982], [34083, 503040640.1672023], [34125, 503282346.00624937], [34139, 503547862.383339], [34153, 503200670.577399], [34167, 503317425.2541452]] \ No newline at end of file +[[28511, 494424263.887413], [29225, 490170871.055939], [29239, 490284944.20020884], [29253, 490315930.1156513], [29267, 490387395.0527699], [29281, 490667427.3060934], [29295, 490479165.1681075], [29309, 490523319.78962505], [29323, 490407198.6197065], [29337, 490818481.02114373], [29351, 489341139.0443334], [29365, 489223635.47283214], [29379, 489597665.0513499], [29393, 489554720.0681822], [29407, 489426300.94461143], [29421, 489355886.5133283], [29435, 490046942.8143584], [29449, 490034420.4031908], [29463, 490042805.3846796], [29477, 490054546.3421895], [29547, 490515057.5207555], [29561, 490181679.26916957], [29575, 489518617.0887432], [29603, 491427472.8485458], [29617, 491385022.86603177], [29631, 492124366.91416264], [29645, 491820418.7816124], [29659, 491614485.91588235], [29673, 491473237.71635365], [29743, 491520725.5310582], [29757, 491688286.35511076], [29771, 491495201.7953478], [29785, 491615678.42660713], [29799, 491798636.1467865], [29813, 491843017.549841], [29827, 492342121.58361894], [29841, 491709780.6076981], [29855, 491412706.4012351], [29869, 492014448.66533005], [30009, 491935027.3107256], [30023, 492014428.5637778], [30037, 491662312.3164708], [30051, 491432461.7935506], [30065, 491586183.7376458], [30079, 491574687.21584606], [30093, 491521353.2427809], [30107, 491582107.23116857], [30121, 491727408.783021], [30135, 491500142.61053854], [30149, 491863957.4758947], [30163, 492071665.14486694], [30177, 492508736.674651], [30191, 492367007.89785635], [30205, 492488350.9480216], [30219, 492409392.4534894], [30233, 492084868.753012], [30247, 492317903.8209429], [30261, 492035404.60846937], [30513, 492523813.47294456], [30527, 492473029.66459286], [30541, 492052664.241502], [30555, 491946370.41368866], [30569, 492055305.2983328], [30583, 492331174.0826049], [30597, 491832534.01285076], [30625, 492217878.26086354], [30639, 492433596.32682264], [30653, 492032463.0915225], [30667, 492827966.2071549], [30681, 493509729.2941611], [30695, 492064380.39266306], [30709, 492208978.6763617], [30723, 492060768.8395485], [30737, 492048251.9584497], [30751, 492242773.0866956], [30765, 492785804.459974], [30779, 492076357.37290674], [30793, 492253226.555851], [30807, 492516800.56512797], [30821, 492621538.16004086], [30835, 492957901.2181211], [30849, 492347025.3969089], [30863, 492383586.0263903], [30877, 492422581.237291], [30891, 492551070.5507549], [30905, 492212418.91397774], [30919, 492429119.0304291], [30933, 492555191.99969125], [30947, 492510362.3035923], [30961, 492494556.40690446], [30975, 492281704.53394055], [30989, 492405710.0694389], [31003, 492381486.5398134], [31017, 492580070.15731114], [31031, 492659350.25857234], [31045, 492442454.15958476], [32095, 512588479.39827573], [32109, 512260215.9267326], [32123, 512421925.4933093], [32137, 512311151.2337653], [32151, 512359970.8567891], [32165, 512476918.79389703], [32179, 512043372.0975828], [32193, 512507668.61841697], [32207, 514547926.96215034], [32221, 516915270.3453668], [32235, 517346786.4931783], [32249, 516653544.6721448], [32263, 516799961.0571027], [32277, 516811166.4210442], [32305, 518335990.14014554], [32319, 522089122.3098076], [32333, 522065980.45503575], [32347, 522112754.7915428], [32361, 522121721.8903518], [32375, 521762916.8393627], [32389, 521941787.8464575], [32403, 522088984.3191828], [32417, 521943658.4024407], [32431, 522119520.0507815], [32445, 522365380.2392815], [32585, 522615215.8080453], [32599, 522625637.56246656], [32613, 522701326.28549194], [32627, 522914486.94157034], [32641, 522654818.8376248], [32655, 522530248.7920552], [32851, 524008235.79285336], [32865, 524013456.50791776], [32879, 523978945.5572481], [32893, 524192672.9947045], [32907, 524063136.91513497], [32921, 523849159.9434005], [32991, 524160414.5254627], [33005, 524006100.1671411], [33019, 523464682.5605816], [33033, 523846302.158408], [33047, 524202533.5050022], [33061, 524451976.24919057], [33075, 524406025.1570502], [33089, 548368557.6986783], [33103, 572365259.7572279], [33117, 572524800.1164186], [33131, 571857378.4312959], [33145, 572761957.6024126], [33159, 572673118.2665321], [33187, 524942668.8242475], [33201, 524542603.18099856], [33215, 522593061.601383], [33229, 517240866.95237374], [33243, 517172104.6577132], [33271, 509212564.5710532], [33299, 509503812.1756981], [33313, 510039277.67950165], [33327, 510224585.93643636], [33341, 510389844.9443076], [33355, 510707914.53079504], [33369, 511491284.203759], [33383, 511965378.8368125], [33397, 512345903.47834444], [33411, 512562146.20958376], [33425, 512626571.69804466], [33439, 514218773.6070256], [33453, 506251468.6634176], [33467, 506278915.9513298], [33523, 506576054.9544816], [33537, 506723394.0697729], [33551, 505632996.88546044], [33649, 504399618.85944647], [33705, 503553133.4365413], [33719, 503960813.9002117], [33733, 503846900.0994794], [33747, 503590786.6335497], [33761, 504003254.3990458], [33775, 503735978.88996613], [33803, 504121063.3068522], [33817, 503388325.35863847], [33831, 503550630.417195], [33845, 503247233.708991], [34041, 503169123.6753149], [34055, 503462425.74773973], [34069, 503404619.9208982], [34083, 503040640.1672023], [34125, 503282346.00624937], [34139, 503547862.383339], [34153, 503200670.577399], [34167, 503251260.98142993]] \ No newline at end of file diff --git a/graphs/summary/linear_model.ElasticNetBenchmark.peakmem_predict.json b/graphs/summary/linear_model.ElasticNetBenchmark.peakmem_predict.json index b3d33c3700..152573509d 100644 --- a/graphs/summary/linear_model.ElasticNetBenchmark.peakmem_predict.json +++ b/graphs/summary/linear_model.ElasticNetBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28511, 278332844.5292575], [29225, 274473309.0801873], [29239, 274297743.82752454], [29253, 273488005.1245749], [29267, 274064642.8760518], [29281, 274447847.68056417], [29295, 274469133.0657963], [29309, 274034405.5869295], [29323, 274144722.7776482], [29337, 274414144.2033772], [29351, 273542662.8202012], [29365, 273413271.9545891], [29379, 273757240.2886883], [29393, 273865896.9822864], [29407, 273287078.3841313], [29421, 273566498.1674793], [29435, 274294947.5238157], [29449, 275039971.97343713], [29463, 274985773.80907995], [29477, 275169773.28379375], [29547, 275298886.50170267], [29561, 275120684.73108125], [29575, 274703221.726682], [29603, 276298975.56536597], [29617, 276065592.1390355], [29631, 276199013.9264968], [29645, 276423410.48286164], [29659, 276152277.83499616], [29673, 276026066.13259494], [29743, 276355900.74316883], [29757, 276288540.71987677], [29771, 276237961.2331216], [29785, 276097566.0918822], [29799, 276520206.5690744], [29813, 276380985.1519179], [29827, 276619245.0832491], [29841, 276451175.19583815], [29855, 276000972.1142821], [29869, 276286159.32963437], [30009, 276214205.5101089], [30023, 276465665.29206145], [30037, 276235953.8680194], [30051, 276453375.832951], [30065, 276474524.2501186], [30079, 276546182.0918197], [30093, 276104252.3959744], [30107, 276232627.8068475], [30121, 276499379.10728985], [30135, 276458824.56121457], [30149, 276557472.52852404], [30163, 276934543.4005775], [30177, 277095939.0078661], [30191, 276963899.2863465], [30205, 277054969.5251507], [30219, 277047293.26381665], [30233, 276482416.92573464], [30247, 277090749.7249619], [30261, 276557967.7721965], [30513, 277181796.6118665], [30527, 276951758.11109173], [30541, 276776194.2868969], [30555, 276857716.101134], [30569, 276812566.0832529], [30583, 277033989.24749494], [30597, 276870964.2287116], [30625, 277049968.0955277], [30639, 277071133.984231], [30653, 276808072.6410772], [30667, 276875631.33915204], [30681, 276983856.10601133], [30695, 277170006.39607257], [30709, 276976378.8090308], [30723, 277023095.54225147], [30737, 277019895.0878329], [30751, 277084766.3168316], [30765, 277594755.8230994], [30779, 276917964.6549909], [30793, 277027146.24428016], [30807, 277082682.1654825], [30821, 277291068.40253985], [30835, 277377558.9586869], [30849, 277193454.8908628], [30863, 277377474.19187367], [30877, 277343888.7546658], [30891, 277349976.88799447], [30905, 277337503.95594084], [30919, 277021493.8891732], [30933, 277183914.4533719], [30947, 277310019.5327065], [30961, 277141771.86528045], [30975, 277232456.9749139], [30989, 277343713.1700664], [31003, 277549224.5071073], [31017, 277366202.6818004], [31031, 277218757.1928503], [31045, 277209211.9963677], [32095, 293064785.4886245], [32109, 292926991.1862904], [32123, 293098486.47524405], [32137, 293150622.5150048], [32151, 292982236.71597826], [32165, 293009382.60331196], [32179, 292818749.6642982], [32193, 293228164.4567672], [32207, 294935982.5790218], [32221, 296893581.99960905], [32235, 296628213.7203705], [32249, 296677761.8615715], [32263, 296542794.83926946], [32277, 296313734.36557037], [32305, 297864174.9249895], [32319, 300810768.63390476], [32333, 300759578.33826953], [32347, 300674920.9943951], [32361, 300770636.2561143], [32375, 300998702.5266215], [32389, 300547056.28356075], [32403, 300747910.54519904], [32417, 300731355.44482213], [32431, 300669030.77859753], [32445, 301096035.19915766], [32585, 301117686.9773104], [32599, 301102733.8956701], [32613, 301227604.15341574], [32627, 301399437.3348823], [32641, 301158527.520698], [32655, 301196044.03604054], [32851, 302460186.91218483], [32865, 302438934.23841053], [32879, 302527041.0035413], [32893, 302652873.97215134], [32907, 302683726.47016543], [32921, 302888608.2736332], [32991, 302800147.7038284], [33005, 302678508.2460513], [33019, 302287116.1641745], [33033, 302842734.8588158], [33047, 302857728.02486444], [33061, 303119557.5019434], [33075, 302865003.6832597], [33089, 308046397.2865869], [33103, 313318408.44929403], [33117, 313565877.3030678], [33131, 313153792.74054384], [33145, 313791279.82039416], [33159, 313821607.2802752], [33187, 303237135.03009194], [33201, 303056831.8730078], [33215, 301332889.46180844], [33229, 296433614.1854687], [33243, 296458139.5527674], [33271, 289444356.22888404], [33299, 289998733.3131721], [33313, 290393942.56255627], [33327, 290341896.7512261], [33341, 290648877.43290526], [33355, 291184858.7253851], [33369, 291730590.7567098], [33383, 291975118.6942917], [33397, 292164939.78598094], [33411, 292237493.7789004], [33425, 292484183.1239891], [33439, 293851063.10953254], [33453, 287371049.44134814], [33467, 287487519.3318409], [33523, 287691076.400632], [33537, 287701534.197632], [33551, 286900492.0688342], [33649, 285217010.44261503], [33705, 284905565.92975616], [33719, 285287196.83383405], [33733, 285204036.3634164], [33747, 285163787.3157506], [33761, 285286597.28397185], [33775, 284775322.9818766], [33803, 285197193.66064215], [33817, 284549351.6399973], [33831, 284858492.59496546], [33845, 284793181.38572675], [34041, 284361134.5023854], [34055, 284973446.02850616], [34069, 284588237.8959307], [34083, 284835156.5959241], [34125, 284868889.0564477], [34139, 284851411.67583555], [34153, 284672468.8535646], [34167, 284693412.03624046]] \ No newline at end of file +[[28511, 278332844.5292575], [29225, 274473309.0801873], [29239, 274297743.82752454], [29253, 273488005.1245749], [29267, 274064642.8760518], [29281, 274447847.68056417], [29295, 274469133.0657963], [29309, 274034405.5869295], [29323, 274144722.7776482], [29337, 274414144.2033772], [29351, 273542662.8202012], [29365, 273413271.9545891], [29379, 273757240.2886883], [29393, 273865896.9822864], [29407, 273287078.3841313], [29421, 273566498.1674793], [29435, 274294947.5238157], [29449, 275039971.97343713], [29463, 274985773.80907995], [29477, 275169773.28379375], [29547, 275298886.50170267], [29561, 275120684.73108125], [29575, 274703221.726682], [29603, 276298975.56536597], [29617, 276065592.1390355], [29631, 276199013.9264968], [29645, 276423410.48286164], [29659, 276152277.83499616], [29673, 276026066.13259494], [29743, 276355900.74316883], [29757, 276288540.71987677], [29771, 276237961.2331216], [29785, 276097566.0918822], [29799, 276520206.5690744], [29813, 276380985.1519179], [29827, 276619245.0832491], [29841, 276451175.19583815], [29855, 276000972.1142821], [29869, 276286159.32963437], [30009, 276214205.5101089], [30023, 276465665.29206145], [30037, 276235953.8680194], [30051, 276453375.832951], [30065, 276474524.2501186], [30079, 276546182.0918197], [30093, 276104252.3959744], [30107, 276232627.8068475], [30121, 276499379.10728985], [30135, 276458824.56121457], [30149, 276557472.52852404], [30163, 276934543.4005775], [30177, 277095939.0078661], [30191, 276963899.2863465], [30205, 277054969.5251507], [30219, 277047293.26381665], [30233, 276482416.92573464], [30247, 277090749.7249619], [30261, 276557967.7721965], [30513, 277181796.6118665], [30527, 276951758.11109173], [30541, 276776194.2868969], [30555, 276857716.101134], [30569, 276812566.0832529], [30583, 277033989.24749494], [30597, 276870964.2287116], [30625, 277049968.0955277], [30639, 277071133.984231], [30653, 276808072.6410772], [30667, 276875631.33915204], [30681, 276983856.10601133], [30695, 277170006.39607257], [30709, 276976378.8090308], [30723, 277023095.54225147], [30737, 277019895.0878329], [30751, 277084766.3168316], [30765, 277594755.8230994], [30779, 276917964.6549909], [30793, 277027146.24428016], [30807, 277082682.1654825], [30821, 277291068.40253985], [30835, 277377558.9586869], [30849, 277193454.8908628], [30863, 277377474.19187367], [30877, 277343888.7546658], [30891, 277349976.88799447], [30905, 277337503.95594084], [30919, 277021493.8891732], [30933, 277183914.4533719], [30947, 277310019.5327065], [30961, 277141771.86528045], [30975, 277232456.9749139], [30989, 277343713.1700664], [31003, 277549224.5071073], [31017, 277366202.6818004], [31031, 277218757.1928503], [31045, 277209211.9963677], [32095, 293064785.4886245], [32109, 292926991.1862904], [32123, 293098486.47524405], [32137, 293150622.5150048], [32151, 292982236.71597826], [32165, 293009382.60331196], [32179, 292818749.6642982], [32193, 293228164.4567672], [32207, 294935982.5790218], [32221, 296893581.99960905], [32235, 296628213.7203705], [32249, 296677761.8615715], [32263, 296542794.83926946], [32277, 296313734.36557037], [32305, 297864174.9249895], [32319, 300810768.63390476], [32333, 300759578.33826953], [32347, 300674920.9943951], [32361, 300770636.2561143], [32375, 300998702.5266215], [32389, 300547056.28356075], [32403, 300747910.54519904], [32417, 300731355.44482213], [32431, 300669030.77859753], [32445, 301096035.19915766], [32585, 301117686.9773104], [32599, 301102733.8956701], [32613, 301227604.15341574], [32627, 301399437.3348823], [32641, 301158527.520698], [32655, 301196044.03604054], [32851, 302460186.91218483], [32865, 302438934.23841053], [32879, 302527041.0035413], [32893, 302652873.97215134], [32907, 302683726.47016543], [32921, 302888608.2736332], [32991, 302800147.7038284], [33005, 302678508.2460513], [33019, 302287116.1641745], [33033, 302842734.8588158], [33047, 302857728.02486444], [33061, 303119557.5019434], [33075, 302865003.6832597], [33089, 308046397.2865869], [33103, 313318408.44929403], [33117, 313565877.3030678], [33131, 313153792.74054384], [33145, 313791279.82039416], [33159, 313821607.2802752], [33187, 303237135.03009194], [33201, 303056831.8730078], [33215, 301332889.46180844], [33229, 296433614.1854687], [33243, 296458139.5527674], [33271, 289444356.22888404], [33299, 289998733.3131721], [33313, 290393942.56255627], [33327, 290341896.7512261], [33341, 290648877.43290526], [33355, 291184858.7253851], [33369, 291730590.7567098], [33383, 291975118.6942917], [33397, 292164939.78598094], [33411, 292237493.7789004], [33425, 292484183.1239891], [33439, 293851063.10953254], [33453, 287371049.44134814], [33467, 287487519.3318409], [33523, 287691076.400632], [33537, 287701534.197632], [33551, 286900492.0688342], [33649, 285217010.44261503], [33705, 284905565.92975616], [33719, 285287196.83383405], [33733, 285204036.3634164], [33747, 285163787.3157506], [33761, 285286597.28397185], [33775, 284775322.9818766], [33803, 285197193.66064215], [33817, 284549351.6399973], [33831, 284858492.59496546], [33845, 284793181.38572675], [34041, 284361134.5023854], [34055, 284973446.02850616], [34069, 284588237.8959307], [34083, 284835156.5959241], [34125, 284868889.0564477], [34139, 284851411.67583555], [34153, 284672468.8535646], [34167, 284709441.8714706]] \ No newline at end of file diff --git a/graphs/summary/linear_model.ElasticNetBenchmark.time_fit.json b/graphs/summary/linear_model.ElasticNetBenchmark.time_fit.json index eb2ed2bb2b..0947269e9d 100644 --- a/graphs/summary/linear_model.ElasticNetBenchmark.time_fit.json +++ b/graphs/summary/linear_model.ElasticNetBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 1.1598071333960587], [29225, 1.889667239734585], [29239, 1.9489318031803797], [29253, 1.2579517613804736], [29267, 1.2098664790308704], [29281, 1.356461685308073], [29295, 1.3121615682460392], [29309, 1.4026915327238707], [29323, 1.234950809526361], [29337, 1.2649808843754222], [29351, 1.2911993614447275], [29365, 1.4435075659324246], [29379, 1.280936462177225], [29393, 1.317665362981898], [29407, 1.2664569970460473], [29421, 1.2703656989041139], [29435, 1.379353066022001], [29449, 2.4164832812844512], [29463, 2.3175257958377236], [29477, 2.00784153202784], [29547, 2.458691631379774], [29561, 2.149889615459599], [29575, 1.8318871935810808], [29603, 1.8003839319472097], [29617, 1.8192515589245823], [29631, 1.8581344221254363], [29645, 1.8506390549252965], [29659, 1.8140882188246348], [29673, 1.828903219308274], [29743, 1.8024792557446545], [29757, 1.8565042398403708], [29771, 1.8438214001515214], [29785, 1.95882557480129], [29799, 2.002080285141908], [29813, 2.081645401281177], [29827, 2.1226941524640948], [29841, 1.8531516163904205], [29855, 2.084264425623668], [29869, 1.9892823376203916], [30009, 2.0389672437130395], [30023, 2.068913470549647], [30037, 1.9790815499159429], [30051, 2.096730890555066], [30065, 1.8908037142644183], [30079, 2.003490955699549], [30093, 1.8933002968576942], [30107, 2.0484811005430905], [30121, 1.893672936632835], [30135, 2.0287941379660084], [30149, 2.131738402673024], [30163, 2.0599313891478386], [30177, 2.0098162521633487], [30191, 2.0751095113956017], [30205, 2.0184873245530692], [30219, 2.0314281414831856], [30233, 1.9656835614572299], [30247, 1.995122811257982], [30261, 1.9772137114445842], [30513, 2.070404055660756], [30527, 1.904697488321562], [30541, 1.9744489062375126], [30555, 2.0821140071359125], [30569, 2.012455620662945], [30583, 1.9167583756129223], [30597, 1.9396369885569804], [30625, 2.155662708929294], [30639, 1.899765546966052], [30653, 2.031433256807057], [30667, 2.049055890909661], [30681, 2.0071495265607693], [30695, 2.011893900979047], [30709, 1.8415638349837744], [30723, 1.8731981997562424], [30737, 2.129143138221769], [30751, 1.9807064192221278], [30765, 1.9180040051791678], [30779, 1.7704577997538524], [30793, 1.95522724642487], [30807, 2.0415475507778416], [30821, 2.06889335435378], [30835, 2.2042126032516527], [30849, 2.1783318881284495], [30863, 1.9983685192700404], [30877, 2.044253767131402], [30891, 1.8558977260715266], [30905, 1.9280258905223335], [30919, 2.1110006444346685], [30933, 2.0490247878413674], [30947, 1.9448428231588197], [30961, 1.9535441818176738], [30975, 1.8888364376605158], [30989, 1.968616200454824], [31003, 1.720174596567638], [31017, 2.057490895164972], [31031, 2.000892480896871], [31045, 1.7833773465140519], [32095, 1.8134049581398972], [32109, 1.8362137380066113], [32123, 1.8411727092757313], [32137, 1.8216258632777933], [32151, 1.812873685023141], [32165, 1.8697560535479725], [32179, 1.8821389922941065], [32193, 1.88592747136443], [32207, 1.8671879243027727], [32221, 1.867642674215866], [32235, 1.8997960707194042], [32249, 1.9208095087947417], [32263, 1.8981388499131229], [32277, 1.7138635456272002], [32305, 1.783795532340794], [32319, 1.71731987397141], [32333, 1.8912965872746226], [32347, 1.8235839609774809], [32361, 1.913248305589658], [32375, 1.647931583835522], [32389, 2.011228242426207], [32403, 1.8269197594510609], [32417, 1.971292461151658], [32431, 1.8649201003369256], [32445, 1.665645762701322], [32585, 1.8863737164703], [32599, 1.7926496027218957], [32613, 1.7562188830162244], [32627, 1.7701954353449942], [32641, 1.7640849625926964], [32655, 1.8152408361069086], [32851, 1.91964335021533], [32865, 1.8715125658957819], [32879, 1.9111724580536815], [32893, 1.8534498656304248], [32907, 1.8900760732583903], [32921, 1.8697945132554632], [32991, 1.8430737533346446], [33005, 1.943577587315561], [33019, 1.8439632372970456], [33033, 1.862037193243943], [33047, 1.944293733373945], [33061, 1.9566437831810681], [33075, 1.86252227115265], [33089, 1.8921801001807588], [33103, 1.9189841880418654], [33117, 1.864419743007922], [33131, 1.8873840797120036], [33145, 1.864641566662136], [33159, 1.8482710819003367], [33187, 2.01210589489047], [33201, 1.877273791065161], [33215, 1.895620290768226], [33229, 1.9934249965146154], [33243, 2.0231054724595974], [33271, 2.1430696418564774], [33299, 2.0262642041788554], [33313, 1.9970098404186674], [33327, 1.956239084521033], [33341, 1.9871520206470819], [33355, 1.9873339537242452], [33369, 2.016760856436967], [33383, 1.966343990597088], [33397, 2.063942204306005], [33411, 1.9886397435198155], [33425, 1.9490653163651672], [33439, 1.9863785916191565], [33453, 2.018642718506784], [33467, 2.0514593222688258], [33523, 2.014166040529127], [33537, 2.0329617933022264], [33551, 2.0918730595397066], [33649, 2.0329591768784008], [33705, 1.9667639102407024], [33719, 2.0294739946678066], [33733, 2.012763810688755], [33747, 1.9693872658907448], [33761, 2.166621585630006], [33775, 1.8835019075455564], [33803, 1.9257426954915877], [33817, 1.9376771321763713], [33831, 1.9563372505876495], [33845, 1.9207187950308835], [34041, 1.9552644134937864], [34055, 1.965473168956595], [34069, 2.0324547177580343], [34083, 1.9766782432584913], [34125, 1.9685143565017278], [34139, 2.0324260314150044], [34153, 1.949208184303141], [34167, 1.9838380569156955]] \ No newline at end of file +[[28511, 1.1598071333960587], [29225, 1.889667239734585], [29239, 1.9489318031803797], [29253, 1.2579517613804736], [29267, 1.2098664790308704], [29281, 1.356461685308073], [29295, 1.3121615682460392], [29309, 1.4026915327238707], [29323, 1.234950809526361], [29337, 1.2649808843754222], [29351, 1.2911993614447275], [29365, 1.4435075659324246], [29379, 1.280936462177225], [29393, 1.317665362981898], [29407, 1.2664569970460473], [29421, 1.2703656989041139], [29435, 1.379353066022001], [29449, 2.4164832812844512], [29463, 2.3175257958377236], [29477, 2.00784153202784], [29547, 2.458691631379774], [29561, 2.149889615459599], [29575, 1.8318871935810808], [29603, 1.8003839319472097], [29617, 1.8192515589245823], [29631, 1.8581344221254363], [29645, 1.8506390549252965], [29659, 1.8140882188246348], [29673, 1.828903219308274], [29743, 1.8024792557446545], [29757, 1.8565042398403708], [29771, 1.8438214001515214], [29785, 1.95882557480129], [29799, 2.002080285141908], [29813, 2.081645401281177], [29827, 2.1226941524640948], [29841, 1.8531516163904205], [29855, 2.084264425623668], [29869, 1.9892823376203916], [30009, 2.0389672437130395], [30023, 2.068913470549647], [30037, 1.9790815499159429], [30051, 2.096730890555066], [30065, 1.8908037142644183], [30079, 2.003490955699549], [30093, 1.8933002968576942], [30107, 2.0484811005430905], [30121, 1.893672936632835], [30135, 2.0287941379660084], [30149, 2.131738402673024], [30163, 2.0599313891478386], [30177, 2.0098162521633487], [30191, 2.0751095113956017], [30205, 2.0184873245530692], [30219, 2.0314281414831856], [30233, 1.9656835614572299], [30247, 1.995122811257982], [30261, 1.9772137114445842], [30513, 2.070404055660756], [30527, 1.904697488321562], [30541, 1.9744489062375126], [30555, 2.0821140071359125], [30569, 2.012455620662945], [30583, 1.9167583756129223], [30597, 1.9396369885569804], [30625, 2.155662708929294], [30639, 1.899765546966052], [30653, 2.031433256807057], [30667, 2.049055890909661], [30681, 2.0071495265607693], [30695, 2.011893900979047], [30709, 1.8415638349837744], [30723, 1.8731981997562424], [30737, 2.129143138221769], [30751, 1.9807064192221278], [30765, 1.9180040051791678], [30779, 1.7704577997538524], [30793, 1.95522724642487], [30807, 2.0415475507778416], [30821, 2.06889335435378], [30835, 2.2042126032516527], [30849, 2.1783318881284495], [30863, 1.9983685192700404], [30877, 2.044253767131402], [30891, 1.8558977260715266], [30905, 1.9280258905223335], [30919, 2.1110006444346685], [30933, 2.0490247878413674], [30947, 1.9448428231588197], [30961, 1.9535441818176738], [30975, 1.8888364376605158], [30989, 1.968616200454824], [31003, 1.720174596567638], [31017, 2.057490895164972], [31031, 2.000892480896871], [31045, 1.7833773465140519], [32095, 1.8134049581398972], [32109, 1.8362137380066113], [32123, 1.8411727092757313], [32137, 1.8216258632777933], [32151, 1.812873685023141], [32165, 1.8697560535479725], [32179, 1.8821389922941065], [32193, 1.88592747136443], [32207, 1.8671879243027727], [32221, 1.867642674215866], [32235, 1.8997960707194042], [32249, 1.9208095087947417], [32263, 1.8981388499131229], [32277, 1.7138635456272002], [32305, 1.783795532340794], [32319, 1.71731987397141], [32333, 1.8912965872746226], [32347, 1.8235839609774809], [32361, 1.913248305589658], [32375, 1.647931583835522], [32389, 2.011228242426207], [32403, 1.8269197594510609], [32417, 1.971292461151658], [32431, 1.8649201003369256], [32445, 1.665645762701322], [32585, 1.8863737164703], [32599, 1.7926496027218957], [32613, 1.7562188830162244], [32627, 1.7701954353449942], [32641, 1.7640849625926964], [32655, 1.8152408361069086], [32851, 1.91964335021533], [32865, 1.8715125658957819], [32879, 1.9111724580536815], [32893, 1.8534498656304248], [32907, 1.8900760732583903], [32921, 1.8697945132554632], [32991, 1.8430737533346446], [33005, 1.943577587315561], [33019, 1.8439632372970456], [33033, 1.862037193243943], [33047, 1.944293733373945], [33061, 1.9566437831810681], [33075, 1.86252227115265], [33089, 1.8921801001807588], [33103, 1.9189841880418654], [33117, 1.864419743007922], [33131, 1.8873840797120036], [33145, 1.864641566662136], [33159, 1.8482710819003367], [33187, 2.01210589489047], [33201, 1.877273791065161], [33215, 1.895620290768226], [33229, 1.9934249965146154], [33243, 2.0231054724595974], [33271, 2.1430696418564774], [33299, 2.0262642041788554], [33313, 1.9970098404186674], [33327, 1.956239084521033], [33341, 1.9871520206470819], [33355, 1.9873339537242452], [33369, 2.016760856436967], [33383, 1.966343990597088], [33397, 2.063942204306005], [33411, 1.9886397435198155], [33425, 1.9490653163651672], [33439, 1.9863785916191565], [33453, 2.018642718506784], [33467, 2.0514593222688258], [33523, 2.014166040529127], [33537, 2.0329617933022264], [33551, 2.0918730595397066], [33649, 2.0329591768784008], [33705, 1.9667639102407024], [33719, 2.0294739946678066], [33733, 2.012763810688755], [33747, 1.9693872658907448], [33761, 2.166621585630006], [33775, 1.8835019075455564], [33803, 1.9257426954915877], [33817, 1.9376771321763713], [33831, 1.9563372505876495], [33845, 1.9207187950308835], [34041, 1.9552644134937864], [34055, 1.965473168956595], [34069, 2.0324547177580343], [34083, 1.9766782432584913], [34125, 1.9685143565017278], [34139, 2.0324260314150044], [34153, 1.949208184303141], [34167, 1.9883712363627928]] \ No newline at end of file diff --git a/graphs/summary/linear_model.ElasticNetBenchmark.time_predict.json b/graphs/summary/linear_model.ElasticNetBenchmark.time_predict.json index cbdabbae2d..cedbc3f5ba 100644 --- a/graphs/summary/linear_model.ElasticNetBenchmark.time_predict.json +++ b/graphs/summary/linear_model.ElasticNetBenchmark.time_predict.json @@ -1 +1 @@ -[[28511, 0.027208729408311625], [29225, 0.025479400835031512], [29239, 0.029351940322285608], [29253, 0.02896174268620526], [29267, 0.0265530375300063], [29281, 0.029855256118469745], [29295, 0.029354922314850287], [29309, 0.029734122056448965], [29323, 0.02815018984664157], [29337, 0.02654995347315298], [29351, 0.028795908942572657], [29365, 0.031985822277356836], [29379, 0.02977584236300828], [29393, 0.029629276741139004], [29407, 0.027716094927008314], [29421, 0.028066271799381606], [29435, 0.03008229422907055], [29449, 0.030654536180149433], [29463, 0.0320186617945631], [29477, 0.0290805201216325], [29547, 0.03075775550677636], [29561, 0.026524667072740152], [29575, 0.026801293566409843], [29603, 0.025841223697476462], [29617, 0.025880547444610554], [29631, 0.026731214903914398], [29645, 0.02606820715466017], [29659, 0.025458157474618548], [29673, 0.025714232199155928], [29743, 0.02581153070231631], [29757, 0.02660198171888975], [29771, 0.02677707163116818], [29785, 0.02955854214784278], [29799, 0.02849090148613964], [29813, 0.028982253279870855], [29827, 0.029245565751209117], [29841, 0.02726663428392361], [29855, 0.028037503257807385], [29869, 0.029434258860512492], [30009, 0.02840795763380214], [30023, 0.027459054615896587], [30037, 0.02904962229646144], [30051, 0.028559138531721772], [30065, 0.027121245959751388], [30079, 0.0306861484435269], [30093, 0.029234975906994684], [30107, 0.027558769968777125], [30121, 0.026995105444210885], [30135, 0.028701777753952065], [30149, 0.028284649921731818], [30163, 0.027506774918233154], [30177, 0.027350171616337807], [30191, 0.02763379879033586], [30205, 0.029490961348195486], [30219, 0.028816158918118017], [30233, 0.02947120525609072], [30247, 0.027190629279284357], [30261, 0.027028766657361585], [30513, 0.028468600389864603], [30527, 0.02876687232321388], [30541, 0.02720151381749159], [30555, 0.02839854587198186], [30569, 0.029192641863644085], [30583, 0.025765211901329542], [30597, 0.026242959083945118], [30625, 0.029967058999278706], [30639, 0.026739616042625723], [30653, 0.028054994204577566], [30667, 0.02704070700577253], [30681, 0.027501525216779347], [30695, 0.02975422528134046], [30709, 0.025369381068287712], [30723, 0.02969395529781684], [30737, 0.02966026797589982], [30751, 0.029048317720586102], [30765, 0.026061704443240075], [30779, 0.024638460990327616], [30793, 0.027286374570778357], [30807, 0.028673436168122318], [30821, 0.02862124257736321], [30835, 0.028480620131147914], [30849, 0.029826492564480406], [30863, 0.027822460699318013], [30877, 0.028670892426791446], [30891, 0.026995556788502736], [30905, 0.03021427127992353], [30919, 0.029536246003527698], [30933, 0.027729342474569277], [30947, 0.02624088740672803], [30961, 0.02837109284351827], [30975, 0.02871677842721814], [30989, 0.028571559058955014], [31003, 0.0262504833630575], [31017, 0.025921928205344964], [31031, 0.02999927726669737], [31045, 0.026693430193096668], [32095, 0.019062019111987343], [32109, 0.01958545653530406], [32123, 0.019177325547248457], [32137, 0.01874414208534512], [32151, 0.018768606901581247], [32165, 0.01942805083680251], [32179, 0.01877033946654973], [32193, 0.018990545040218007], [32207, 0.019001109733418255], [32221, 0.01952178752651282], [32235, 0.019375216684440977], [32249, 0.019448061406699288], [32263, 0.018841534219472746], [32277, 0.018320934604395215], [32305, 0.019007846864948722], [32319, 0.017955939738857993], [32333, 0.021429665599471685], [32347, 0.01950039276826037], [32361, 0.019119990454105118], [32375, 0.021212144502638346], [32389, 0.019537674667733172], [32403, 0.017859677614575027], [32417, 0.020181974228625794], [32431, 0.019466865800314617], [32445, 0.020876173012205564], [32585, 0.018308481530493536], [32599, 0.01860328573372831], [32613, 0.018786672623516174], [32627, 0.020034623258038547], [32641, 0.017694302634736876], [32655, 0.019137778018294384], [32851, 0.01883673398643533], [32865, 0.018317686596619528], [32879, 0.01880565034630465], [32893, 0.018801563265335552], [32907, 0.01865708621641393], [32921, 0.017670101508942455], [32991, 0.018388830414887522], [33005, 0.018772399475304884], [33019, 0.01944094192196047], [33033, 0.019332889548009567], [33047, 0.019412304597178562], [33061, 0.0186291404934822], [33075, 0.018116207231455444], [33089, 0.018720419534431175], [33103, 0.018993120822176805], [33117, 0.018641890085101573], [33131, 0.019021176009825988], [33145, 0.019552886827338124], [33159, 0.019322382888560103], [33187, 0.019260246180180754], [33201, 0.018595263582343882], [33215, 0.018942449807660872], [33229, 0.019518964821562616], [33243, 0.018991472460961348], [33271, 0.019855014898391053], [33299, 0.018091035911890343], [33313, 0.019059936541633796], [33327, 0.018585794971192227], [33341, 0.019109884999587243], [33355, 0.01818242607847549], [33369, 0.01848279247513186], [33383, 0.019375784675947378], [33397, 0.0177884488015373], [33411, 0.017294788040497566], [33425, 0.017522318826489056], [33439, 0.018159218365629705], [33453, 0.020131732281235326], [33467, 0.020570152906247384], [33523, 0.018865876769656228], [33537, 0.017616814975108256], [33551, 0.01786003812240872], [33649, 0.018905156671442835], [33705, 0.019445964040779775], [33719, 0.018918867307086466], [33733, 0.020264274599165945], [33747, 0.01923891477747381], [33761, 0.0201728967452464], [33775, 0.020384847723135167], [33803, 0.020088120635297465], [33817, 0.018330780765616485], [33831, 0.019583236942318834], [33845, 0.017719648041838742], [34041, 0.019317791141156157], [34055, 0.01994605643482907], [34069, 0.0202681233353082], [34083, 0.020172298806803615], [34125, 0.019118115450245592], [34139, 0.020128480648897464], [34153, 0.019527120789699936], [34167, 0.01938104258850211]] \ No newline at end of file +[[28511, 0.027208729408311625], [29225, 0.025479400835031512], [29239, 0.029351940322285608], [29253, 0.02896174268620526], [29267, 0.0265530375300063], [29281, 0.029855256118469745], [29295, 0.029354922314850287], [29309, 0.029734122056448965], [29323, 0.02815018984664157], [29337, 0.02654995347315298], [29351, 0.028795908942572657], [29365, 0.031985822277356836], [29379, 0.02977584236300828], [29393, 0.029629276741139004], [29407, 0.027716094927008314], [29421, 0.028066271799381606], [29435, 0.03008229422907055], [29449, 0.030654536180149433], [29463, 0.0320186617945631], [29477, 0.0290805201216325], [29547, 0.03075775550677636], [29561, 0.026524667072740152], [29575, 0.026801293566409843], [29603, 0.025841223697476462], [29617, 0.025880547444610554], [29631, 0.026731214903914398], [29645, 0.02606820715466017], [29659, 0.025458157474618548], [29673, 0.025714232199155928], [29743, 0.02581153070231631], [29757, 0.02660198171888975], [29771, 0.02677707163116818], [29785, 0.02955854214784278], [29799, 0.02849090148613964], [29813, 0.028982253279870855], [29827, 0.029245565751209117], [29841, 0.02726663428392361], [29855, 0.028037503257807385], [29869, 0.029434258860512492], [30009, 0.02840795763380214], [30023, 0.027459054615896587], [30037, 0.02904962229646144], [30051, 0.028559138531721772], [30065, 0.027121245959751388], [30079, 0.0306861484435269], [30093, 0.029234975906994684], [30107, 0.027558769968777125], [30121, 0.026995105444210885], [30135, 0.028701777753952065], [30149, 0.028284649921731818], [30163, 0.027506774918233154], [30177, 0.027350171616337807], [30191, 0.02763379879033586], [30205, 0.029490961348195486], [30219, 0.028816158918118017], [30233, 0.02947120525609072], [30247, 0.027190629279284357], [30261, 0.027028766657361585], [30513, 0.028468600389864603], [30527, 0.02876687232321388], [30541, 0.02720151381749159], [30555, 0.02839854587198186], [30569, 0.029192641863644085], [30583, 0.025765211901329542], [30597, 0.026242959083945118], [30625, 0.029967058999278706], [30639, 0.026739616042625723], [30653, 0.028054994204577566], [30667, 0.02704070700577253], [30681, 0.027501525216779347], [30695, 0.02975422528134046], [30709, 0.025369381068287712], [30723, 0.02969395529781684], [30737, 0.02966026797589982], [30751, 0.029048317720586102], [30765, 0.026061704443240075], [30779, 0.024638460990327616], [30793, 0.027286374570778357], [30807, 0.028673436168122318], [30821, 0.02862124257736321], [30835, 0.028480620131147914], [30849, 0.029826492564480406], [30863, 0.027822460699318013], [30877, 0.028670892426791446], [30891, 0.026995556788502736], [30905, 0.03021427127992353], [30919, 0.029536246003527698], [30933, 0.027729342474569277], [30947, 0.02624088740672803], [30961, 0.02837109284351827], [30975, 0.02871677842721814], [30989, 0.028571559058955014], [31003, 0.0262504833630575], [31017, 0.025921928205344964], [31031, 0.02999927726669737], [31045, 0.026693430193096668], [32095, 0.019062019111987343], [32109, 0.01958545653530406], [32123, 0.019177325547248457], [32137, 0.01874414208534512], [32151, 0.018768606901581247], [32165, 0.01942805083680251], [32179, 0.01877033946654973], [32193, 0.018990545040218007], [32207, 0.019001109733418255], [32221, 0.01952178752651282], [32235, 0.019375216684440977], [32249, 0.019448061406699288], [32263, 0.018841534219472746], [32277, 0.018320934604395215], [32305, 0.019007846864948722], [32319, 0.017955939738857993], [32333, 0.021429665599471685], [32347, 0.01950039276826037], [32361, 0.019119990454105118], [32375, 0.021212144502638346], [32389, 0.019537674667733172], [32403, 0.017859677614575027], [32417, 0.020181974228625794], [32431, 0.019466865800314617], [32445, 0.020876173012205564], [32585, 0.018308481530493536], [32599, 0.01860328573372831], [32613, 0.018786672623516174], [32627, 0.020034623258038547], [32641, 0.017694302634736876], [32655, 0.019137778018294384], [32851, 0.01883673398643533], [32865, 0.018317686596619528], [32879, 0.01880565034630465], [32893, 0.018801563265335552], [32907, 0.01865708621641393], [32921, 0.017670101508942455], [32991, 0.018388830414887522], [33005, 0.018772399475304884], [33019, 0.01944094192196047], [33033, 0.019332889548009567], [33047, 0.019412304597178562], [33061, 0.0186291404934822], [33075, 0.018116207231455444], [33089, 0.018720419534431175], [33103, 0.018993120822176805], [33117, 0.018641890085101573], [33131, 0.019021176009825988], [33145, 0.019552886827338124], [33159, 0.019322382888560103], [33187, 0.019260246180180754], [33201, 0.018595263582343882], [33215, 0.018942449807660872], [33229, 0.019518964821562616], [33243, 0.018991472460961348], [33271, 0.019855014898391053], [33299, 0.018091035911890343], [33313, 0.019059936541633796], [33327, 0.018585794971192227], [33341, 0.019109884999587243], [33355, 0.01818242607847549], [33369, 0.01848279247513186], [33383, 0.019375784675947378], [33397, 0.0177884488015373], [33411, 0.017294788040497566], [33425, 0.017522318826489056], [33439, 0.018159218365629705], [33453, 0.020131732281235326], [33467, 0.020570152906247384], [33523, 0.018865876769656228], [33537, 0.017616814975108256], [33551, 0.01786003812240872], [33649, 0.018905156671442835], [33705, 0.019445964040779775], [33719, 0.018918867307086466], [33733, 0.020264274599165945], [33747, 0.01923891477747381], [33761, 0.0201728967452464], [33775, 0.020384847723135167], [33803, 0.020088120635297465], [33817, 0.018330780765616485], [33831, 0.019583236942318834], [33845, 0.017719648041838742], [34041, 0.019317791141156157], [34055, 0.01994605643482907], [34069, 0.0202681233353082], [34083, 0.020172298806803615], [34125, 0.019118115450245592], [34139, 0.020128480648897464], [34153, 0.019527120789699936], [34167, 0.019259000377158792]] \ No newline at end of file diff --git a/graphs/summary/linear_model.ElasticNetBenchmark.track_test_score.json b/graphs/summary/linear_model.ElasticNetBenchmark.track_test_score.json index efee0812d3..bb7c5d2af7 100644 --- a/graphs/summary/linear_model.ElasticNetBenchmark.track_test_score.json +++ b/graphs/summary/linear_model.ElasticNetBenchmark.track_test_score.json @@ -1 +1 @@ -[[28511, 0.9348210310434274], [29225, 0.9350888385274114], [29239, 0.9346870992471497], [29253, 0.9350038059285638], [29267, 0.9347076745775325], [29281, 0.9351151083059869], [29295, 0.9348493784894133], [29309, 0.9349923264705371], [29323, 0.9349337868378607], [29337, 0.9347986768517241], [29351, 0.9347333367384113], [29365, 0.9348539587285956], [29379, 0.9345852320146644], [29393, 0.934498843939498], [29407, 0.9348062248691685], [29421, 0.9347686647307364], [29435, 0.9346675367616291], [29449, 0.9346306426746848], [29463, 0.9347383491790288], [29477, 0.9344748977518461], [29547, 0.9345713654990614], [29561, 0.93465845826895], [29575, 0.9349892273053014], [29603, 0.9346596377521348], [29617, 0.9348904014707928], [29631, 0.934936420618748], [29645, 0.9347194981453733], [29659, 0.9348454253649694], [29673, 0.9348729641881711], [29743, 0.9348395509587373], [29757, 0.9344930395743893], [29771, 0.9348882350240284], [29785, 0.9347443669301021], [29799, 0.934637104915141], [29813, 0.9347255272050743], [29827, 0.9347625838047615], [29841, 0.935073436754402], [29855, 0.9349334913387716], [29869, 0.9347287562265654], [30009, 0.9349875208495365], [30023, 0.9348471327443264], [30037, 0.9348189667523922], [30051, 0.9347082524280425], [30065, 0.9348294181720127], [30079, 0.9347964671007337], [30093, 0.9347682250150307], [30107, 0.9347015814245377], [30121, 0.934854166751229], [30135, 0.934837541294745], [30149, 0.9350084185449115], [30163, 0.93460952561964], [30177, 0.9349561923148588], [30191, 0.9345827989965663], [30205, 0.9351501785992989], [30219, 0.9349490702480387], [30233, 0.9348956593017007], [30247, 0.9348567285351199], [30261, 0.9346977273802136], [30513, 0.9349122641047434], [30527, 0.9349493731793339], [30541, 0.9348473528563112], [30555, 0.9348996331354629], [30569, 0.9349058887328939], [30583, 0.9346398424947508], [30597, 0.9350015701236932], [30625, 0.9350858102702236], [30639, 0.9348726777631888], [30653, 0.9349132524084802], [30667, 0.935297119438416], [30681, 0.9347590398054652], [30695, 0.9346755126024583], [30709, 0.934548574153501], [30723, 0.9348589597059602], [30737, 0.9348414275907267], [30751, 0.9348234562146864], [30765, 0.934800597314101], [30779, 0.9352243418521065], [30793, 0.9348727855720548], [30807, 0.9348671936027217], [30821, 0.9347022873643354], [30835, 0.9355001419145015], [30849, 0.9357357944943518], [30863, 0.9349988594168719], [30877, 0.9352003000182247], [30891, 0.9352705731747551], [30905, 0.9346682260115138], [30919, 0.9345886445950816], [30933, 0.9347293971807864], [30947, 0.9346488419658012], [30961, 0.9346685911539819], [30975, 0.9349834508719177], [30989, 0.9349022515403473], [31003, 0.9347396724655759], [31017, 0.9342740041143425], [31031, 0.9350808755223943], [31045, 0.9349706166809336], [32095, 0.9347414184256704], [32109, 0.9347646857030273], [32123, 0.9348650583615717], [32137, 0.934947601059832], [32151, 0.9349830907493488], [32165, 0.9350802283104002], [32179, 0.9353765816295381], [32193, 0.9348505118003704], [32207, 0.9349717401108935], [32221, 0.9349687272377595], [32235, 0.9351408313101188], [32249, 0.9352020804903505], [32263, 0.9349208520086465], [32277, 0.9345439239737189], [32305, 0.9349625240243178], [32319, 0.9350645999725898], [32333, 0.9346905030815966], [32347, 0.9348159782553808], [32361, 0.9348776445721443], [32375, 0.9345700628162315], [32389, 0.9348802705671172], [32403, 0.9346035106946126], [32417, 0.9349290330874016], [32431, 0.9345764885256373], [32445, 0.934749480421679], [32585, 0.9347725958466765], [32599, 0.9349567568835052], [32613, 0.9345790865520504], [32627, 0.9344142463136267], [32641, 0.9347323484484709], [32655, 0.934822893305804], [32851, 0.9343330663762152], [32865, 0.9347833322280279], [32879, 0.9348904591256159], [32893, 0.934762233416162], [32907, 0.9351342538967562], [32921, 0.9349044396470033], [32991, 0.9347707753578361], [33005, 0.9348787453167832], [33019, 0.9347731694280119], [33033, 0.9350822419120198], [33047, 0.9348942499364247], [33061, 0.9346588137263212], [33075, 0.9352658005488291], [33089, 0.9345594091911161], [33103, 0.9346657025817179], [33117, 0.9350206289496141], [33131, 0.9348168547226618], [33145, 0.9354026629565743], [33159, 0.9351764927811882], [33187, 0.9347434896152952], [33201, 0.9348540971032681], [33215, 0.9348055716449813], [33229, 0.9347848791229161], [33243, 0.9349449679567953], [33271, 0.9348421866713962], [33299, 0.9348326545427516], [33313, 0.9348026359273811], [33327, 0.9348780024986394], [33341, 0.9346258737819128], [33355, 0.9348206723972906], [33369, 0.9347759870468769], [33383, 0.9347531332021788], [33397, 0.9347445485412961], [33411, 0.9349128533914571], [33425, 0.9348448118834315], [33439, 0.9349670899779796], [33453, 0.934280457120366], [33467, 0.9345293561620818], [33523, 0.9347931415642431], [33537, 0.9348686861952543], [33551, 0.9348898552490561], [33649, 0.9344940725343811], [33705, 0.9347979663923733], [33719, 0.9347902072717876], [33733, 0.9343387860344943], [33747, 0.9351631164727172], [33761, 0.9352122877156057], [33775, 0.9350313712874629], [33803, 0.9350864582615885], [33817, 0.9348519314799836], [33831, 0.9346220061426078], [33845, 0.9344540059260172], [34041, 0.9348689192344845], [34055, 0.934540736999491], [34069, 0.9348861592548835], [34083, 0.9349901484667528], [34125, 0.9349010859069278], [34139, 0.9347613747859681], [34153, 0.9350097035585522], [34167, 0.9347374450282712]] \ No newline at end of file +[[28511, 0.9348210310434274], [29225, 0.9350888385274114], [29239, 0.9346870992471497], [29253, 0.9350038059285638], [29267, 0.9347076745775325], [29281, 0.9351151083059869], [29295, 0.9348493784894133], [29309, 0.9349923264705371], [29323, 0.9349337868378607], [29337, 0.9347986768517241], [29351, 0.9347333367384113], [29365, 0.9348539587285956], [29379, 0.9345852320146644], [29393, 0.934498843939498], [29407, 0.9348062248691685], [29421, 0.9347686647307364], [29435, 0.9346675367616291], [29449, 0.9346306426746848], [29463, 0.9347383491790288], [29477, 0.9344748977518461], [29547, 0.9345713654990614], [29561, 0.93465845826895], [29575, 0.9349892273053014], [29603, 0.9346596377521348], [29617, 0.9348904014707928], [29631, 0.934936420618748], [29645, 0.9347194981453733], [29659, 0.9348454253649694], [29673, 0.9348729641881711], [29743, 0.9348395509587373], [29757, 0.9344930395743893], [29771, 0.9348882350240284], [29785, 0.9347443669301021], [29799, 0.934637104915141], [29813, 0.9347255272050743], [29827, 0.9347625838047615], [29841, 0.935073436754402], [29855, 0.9349334913387716], [29869, 0.9347287562265654], [30009, 0.9349875208495365], [30023, 0.9348471327443264], [30037, 0.9348189667523922], [30051, 0.9347082524280425], [30065, 0.9348294181720127], [30079, 0.9347964671007337], [30093, 0.9347682250150307], [30107, 0.9347015814245377], [30121, 0.934854166751229], [30135, 0.934837541294745], [30149, 0.9350084185449115], [30163, 0.93460952561964], [30177, 0.9349561923148588], [30191, 0.9345827989965663], [30205, 0.9351501785992989], [30219, 0.9349490702480387], [30233, 0.9348956593017007], [30247, 0.9348567285351199], [30261, 0.9346977273802136], [30513, 0.9349122641047434], [30527, 0.9349493731793339], [30541, 0.9348473528563112], [30555, 0.9348996331354629], [30569, 0.9349058887328939], [30583, 0.9346398424947508], [30597, 0.9350015701236932], [30625, 0.9350858102702236], [30639, 0.9348726777631888], [30653, 0.9349132524084802], [30667, 0.935297119438416], [30681, 0.9347590398054652], [30695, 0.9346755126024583], [30709, 0.934548574153501], [30723, 0.9348589597059602], [30737, 0.9348414275907267], [30751, 0.9348234562146864], [30765, 0.934800597314101], [30779, 0.9352243418521065], [30793, 0.9348727855720548], [30807, 0.9348671936027217], [30821, 0.9347022873643354], [30835, 0.9355001419145015], [30849, 0.9357357944943518], [30863, 0.9349988594168719], [30877, 0.9352003000182247], [30891, 0.9352705731747551], [30905, 0.9346682260115138], [30919, 0.9345886445950816], [30933, 0.9347293971807864], [30947, 0.9346488419658012], [30961, 0.9346685911539819], [30975, 0.9349834508719177], [30989, 0.9349022515403473], [31003, 0.9347396724655759], [31017, 0.9342740041143425], [31031, 0.9350808755223943], [31045, 0.9349706166809336], [32095, 0.9347414184256704], [32109, 0.9347646857030273], [32123, 0.9348650583615717], [32137, 0.934947601059832], [32151, 0.9349830907493488], [32165, 0.9350802283104002], [32179, 0.9353765816295381], [32193, 0.9348505118003704], [32207, 0.9349717401108935], [32221, 0.9349687272377595], [32235, 0.9351408313101188], [32249, 0.9352020804903505], [32263, 0.9349208520086465], [32277, 0.9345439239737189], [32305, 0.9349625240243178], [32319, 0.9350645999725898], [32333, 0.9346905030815966], [32347, 0.9348159782553808], [32361, 0.9348776445721443], [32375, 0.9345700628162315], [32389, 0.9348802705671172], [32403, 0.9346035106946126], [32417, 0.9349290330874016], [32431, 0.9345764885256373], [32445, 0.934749480421679], [32585, 0.9347725958466765], [32599, 0.9349567568835052], [32613, 0.9345790865520504], [32627, 0.9344142463136267], [32641, 0.9347323484484709], [32655, 0.934822893305804], [32851, 0.9343330663762152], [32865, 0.9347833322280279], [32879, 0.9348904591256159], [32893, 0.934762233416162], [32907, 0.9351342538967562], [32921, 0.9349044396470033], [32991, 0.9347707753578361], [33005, 0.9348787453167832], [33019, 0.9347731694280119], [33033, 0.9350822419120198], [33047, 0.9348942499364247], [33061, 0.9346588137263212], [33075, 0.9352658005488291], [33089, 0.9345594091911161], [33103, 0.9346657025817179], [33117, 0.9350206289496141], [33131, 0.9348168547226618], [33145, 0.9354026629565743], [33159, 0.9351764927811882], [33187, 0.9347434896152952], [33201, 0.9348540971032681], [33215, 0.9348055716449813], [33229, 0.9347848791229161], [33243, 0.9349449679567953], [33271, 0.9348421866713962], [33299, 0.9348326545427516], [33313, 0.9348026359273811], [33327, 0.9348780024986394], [33341, 0.9346258737819128], [33355, 0.9348206723972906], [33369, 0.9347759870468769], [33383, 0.9347531332021788], [33397, 0.9347445485412961], [33411, 0.9349128533914571], [33425, 0.9348448118834315], [33439, 0.9349670899779796], [33453, 0.934280457120366], [33467, 0.9345293561620818], [33523, 0.9347931415642431], [33537, 0.9348686861952543], [33551, 0.9348898552490561], [33649, 0.9344940725343811], [33705, 0.9347979663923733], [33719, 0.9347902072717876], [33733, 0.9343387860344943], [33747, 0.9351631164727172], [33761, 0.9352122877156057], [33775, 0.9350313712874629], [33803, 0.9350864582615885], [33817, 0.9348519314799836], [33831, 0.9346220061426078], [33845, 0.9344540059260172], [34041, 0.9348689192344845], [34055, 0.934540736999491], [34069, 0.9348861592548835], [34083, 0.9349901484667528], [34125, 0.9349010859069278], [34139, 0.9347613747859681], [34153, 0.9350097035585522], [34167, 0.9347887646101812]] \ No newline at end of file diff --git a/graphs/summary/linear_model.ElasticNetBenchmark.track_train_score.json b/graphs/summary/linear_model.ElasticNetBenchmark.track_train_score.json index 348e278c77..44687fdf59 100644 --- a/graphs/summary/linear_model.ElasticNetBenchmark.track_train_score.json +++ b/graphs/summary/linear_model.ElasticNetBenchmark.track_train_score.json @@ -1 +1 @@ -[[28511, 0.936935771034954], [29225, 0.9371663318442236], [29239, 0.9370235032523896], [29253, 0.9370860808343723], [29267, 0.9369902760000672], [29281, 0.9369486995506571], [29295, 0.9370697721927668], [29309, 0.9370649979933812], [29323, 0.9370805184149303], [29337, 0.9370172639130451], [29351, 0.9369797728566782], [29365, 0.9369483303169129], [29379, 0.93707273922306], [29393, 0.9369882850589253], [29407, 0.9369157412589306], [29421, 0.9370584633241127], [29435, 0.9369958938962495], [29449, 0.9370266742120363], [29463, 0.9370450798081853], [29477, 0.9369492039661422], [29547, 0.937043347283861], [29561, 0.9370279242403298], [29575, 0.9370043173094909], [29603, 0.9370203085695552], [29617, 0.9369978415514518], [29631, 0.9371287645574803], [29645, 0.9370127403101214], [29659, 0.9370365983647102], [29673, 0.9370548364870604], [29743, 0.9370533293187278], [29757, 0.9369838273704815], [29771, 0.9370562632969287], [29785, 0.9370877196046632], [29799, 0.9370658666359131], [29813, 0.9370079645646572], [29827, 0.9370668516651146], [29841, 0.9370777248398], [29855, 0.9370319610062215], [29869, 0.9371161558349711], [30009, 0.9370241955128709], [30023, 0.9371009107997376], [30037, 0.9370554965253072], [30051, 0.9369696052955241], [30065, 0.9370856360140379], [30079, 0.9370325843418353], [30093, 0.93705684600735], [30107, 0.9370490977915203], [30121, 0.9370093367537438], [30135, 0.9370724939019539], [30149, 0.9369839848004673], [30163, 0.9369857127001079], [30177, 0.9370614023639813], [30191, 0.9370135695539652], [30205, 0.9371151105785103], [30219, 0.9370331565430003], [30233, 0.9370543936962707], [30247, 0.9370187162335546], [30261, 0.9370522495364839], [30513, 0.9370597320610422], [30527, 0.9369933275518681], [30541, 0.9370218813459203], [30555, 0.9370428899827639], [30569, 0.9369914093806712], [30583, 0.937050457119154], [30597, 0.937143826269183], [30625, 0.9370355638279068], [30639, 0.9370730526212379], [30653, 0.9370181296241175], [30667, 0.937056301209843], [30681, 0.937024036654892], [30695, 0.936894070718689], [30709, 0.9370215275596778], [30723, 0.9370592907285011], [30737, 0.9371153434708362], [30751, 0.937047994182993], [30765, 0.9370389285018018], [30779, 0.937079608580743], [30793, 0.9370079915878957], [30807, 0.9369487333523621], [30821, 0.9370607660909613], [30835, 0.9371560337080205], [30849, 0.9370081406018037], [30863, 0.9369745559856651], [30877, 0.9370630974693027], [30891, 0.9370976128478526], [30905, 0.9368661580981505], [30919, 0.9370549861943965], [30933, 0.9370327350979768], [30947, 0.9369893691903548], [30961, 0.9370737625383595], [30975, 0.9370405087881098], [30989, 0.9370614241674238], [31003, 0.9370679858007898], [31017, 0.9369272494392331], [31031, 0.9371231484407471], [31045, 0.9370244487404096], [32095, 0.9370978751552292], [32109, 0.9370041484046836], [32123, 0.9370051772439119], [32137, 0.9369375446344484], [32151, 0.9371020183114585], [32165, 0.9370055126477523], [32179, 0.9369029886800347], [32193, 0.937037211869438], [32207, 0.9370364178574114], [32221, 0.9369995729503975], [32235, 0.9369996634781157], [32249, 0.9369981991776145], [32263, 0.9370608374809667], [32277, 0.9369897388437494], [32305, 0.9370933588045669], [32319, 0.9370493409111621], [32333, 0.9370461614806579], [32347, 0.9369734274456989], [32361, 0.9370755850453686], [32375, 0.9370075577122636], [32389, 0.9370357902479334], [32403, 0.9369100513922101], [32417, 0.9370682837650411], [32431, 0.937020588588023], [32445, 0.9370908883287036], [32585, 0.9370190022956165], [32599, 0.9369788279724208], [32613, 0.9370229705079977], [32627, 0.9370545637987638], [32641, 0.9370905365961208], [32655, 0.9370713003733867], [32851, 0.9370718277785639], [32865, 0.9370596866258178], [32879, 0.936944267841117], [32893, 0.9369746202660552], [32907, 0.9370115757307937], [32921, 0.9370008147709769], [32991, 0.9370632826644539], [33005, 0.9371161886539983], [33019, 0.9369241090527565], [33033, 0.9371178548966312], [33047, 0.9370915301289513], [33061, 0.9371134183760519], [33075, 0.937215293801633], [33089, 0.9370530958035903], [33103, 0.9370328338629014], [33117, 0.9371031222486235], [33131, 0.9369515653281077], [33145, 0.937196158170983], [33159, 0.9369924009280339], [33187, 0.9369293583851839], [33201, 0.9370647914847975], [33215, 0.9370295711043879], [33229, 0.9369856222820148], [33243, 0.9370252310710803], [33271, 0.93688585374982], [33299, 0.9369467158646638], [33313, 0.9369884209318767], [33327, 0.9370552452132763], [33341, 0.9370683296779793], [33355, 0.9370491403963865], [33369, 0.9370697921021364], [33383, 0.9370277881758065], [33397, 0.9370768691975904], [33411, 0.9371247085878582], [33425, 0.9370805920410223], [33439, 0.9369981680097714], [33453, 0.9369961196967896], [33467, 0.9369569391181305], [33523, 0.9369895119371746], [33537, 0.9370058204058713], [33551, 0.9369869582918874], [33649, 0.9369838930474592], [33705, 0.9371158595914374], [33719, 0.9370287438550752], [33733, 0.9369775092208187], [33747, 0.9370431771150489], [33761, 0.9370705029435537], [33775, 0.9369762685585881], [33803, 0.9369984743006556], [33817, 0.9369935871194539], [33831, 0.9369766570393626], [33845, 0.9368546996906173], [34041, 0.9370101339710839], [34055, 0.9369727133965703], [34069, 0.9370534971531631], [34083, 0.9370368336142844], [34125, 0.936926318034555], [34139, 0.9370522060609088], [34153, 0.9370495180239887], [34167, 0.9370456076085396]] \ No newline at end of file +[[28511, 0.936935771034954], [29225, 0.9371663318442236], [29239, 0.9370235032523896], [29253, 0.9370860808343723], [29267, 0.9369902760000672], [29281, 0.9369486995506571], [29295, 0.9370697721927668], [29309, 0.9370649979933812], [29323, 0.9370805184149303], [29337, 0.9370172639130451], [29351, 0.9369797728566782], [29365, 0.9369483303169129], [29379, 0.93707273922306], [29393, 0.9369882850589253], [29407, 0.9369157412589306], [29421, 0.9370584633241127], [29435, 0.9369958938962495], [29449, 0.9370266742120363], [29463, 0.9370450798081853], [29477, 0.9369492039661422], [29547, 0.937043347283861], [29561, 0.9370279242403298], [29575, 0.9370043173094909], [29603, 0.9370203085695552], [29617, 0.9369978415514518], [29631, 0.9371287645574803], [29645, 0.9370127403101214], [29659, 0.9370365983647102], [29673, 0.9370548364870604], [29743, 0.9370533293187278], [29757, 0.9369838273704815], [29771, 0.9370562632969287], [29785, 0.9370877196046632], [29799, 0.9370658666359131], [29813, 0.9370079645646572], [29827, 0.9370668516651146], [29841, 0.9370777248398], [29855, 0.9370319610062215], [29869, 0.9371161558349711], [30009, 0.9370241955128709], [30023, 0.9371009107997376], [30037, 0.9370554965253072], [30051, 0.9369696052955241], [30065, 0.9370856360140379], [30079, 0.9370325843418353], [30093, 0.93705684600735], [30107, 0.9370490977915203], [30121, 0.9370093367537438], [30135, 0.9370724939019539], [30149, 0.9369839848004673], [30163, 0.9369857127001079], [30177, 0.9370614023639813], [30191, 0.9370135695539652], [30205, 0.9371151105785103], [30219, 0.9370331565430003], [30233, 0.9370543936962707], [30247, 0.9370187162335546], [30261, 0.9370522495364839], [30513, 0.9370597320610422], [30527, 0.9369933275518681], [30541, 0.9370218813459203], [30555, 0.9370428899827639], [30569, 0.9369914093806712], [30583, 0.937050457119154], [30597, 0.937143826269183], [30625, 0.9370355638279068], [30639, 0.9370730526212379], [30653, 0.9370181296241175], [30667, 0.937056301209843], [30681, 0.937024036654892], [30695, 0.936894070718689], [30709, 0.9370215275596778], [30723, 0.9370592907285011], [30737, 0.9371153434708362], [30751, 0.937047994182993], [30765, 0.9370389285018018], [30779, 0.937079608580743], [30793, 0.9370079915878957], [30807, 0.9369487333523621], [30821, 0.9370607660909613], [30835, 0.9371560337080205], [30849, 0.9370081406018037], [30863, 0.9369745559856651], [30877, 0.9370630974693027], [30891, 0.9370976128478526], [30905, 0.9368661580981505], [30919, 0.9370549861943965], [30933, 0.9370327350979768], [30947, 0.9369893691903548], [30961, 0.9370737625383595], [30975, 0.9370405087881098], [30989, 0.9370614241674238], [31003, 0.9370679858007898], [31017, 0.9369272494392331], [31031, 0.9371231484407471], [31045, 0.9370244487404096], [32095, 0.9370978751552292], [32109, 0.9370041484046836], [32123, 0.9370051772439119], [32137, 0.9369375446344484], [32151, 0.9371020183114585], [32165, 0.9370055126477523], [32179, 0.9369029886800347], [32193, 0.937037211869438], [32207, 0.9370364178574114], [32221, 0.9369995729503975], [32235, 0.9369996634781157], [32249, 0.9369981991776145], [32263, 0.9370608374809667], [32277, 0.9369897388437494], [32305, 0.9370933588045669], [32319, 0.9370493409111621], [32333, 0.9370461614806579], [32347, 0.9369734274456989], [32361, 0.9370755850453686], [32375, 0.9370075577122636], [32389, 0.9370357902479334], [32403, 0.9369100513922101], [32417, 0.9370682837650411], [32431, 0.937020588588023], [32445, 0.9370908883287036], [32585, 0.9370190022956165], [32599, 0.9369788279724208], [32613, 0.9370229705079977], [32627, 0.9370545637987638], [32641, 0.9370905365961208], [32655, 0.9370713003733867], [32851, 0.9370718277785639], [32865, 0.9370596866258178], [32879, 0.936944267841117], [32893, 0.9369746202660552], [32907, 0.9370115757307937], [32921, 0.9370008147709769], [32991, 0.9370632826644539], [33005, 0.9371161886539983], [33019, 0.9369241090527565], [33033, 0.9371178548966312], [33047, 0.9370915301289513], [33061, 0.9371134183760519], [33075, 0.937215293801633], [33089, 0.9370530958035903], [33103, 0.9370328338629014], [33117, 0.9371031222486235], [33131, 0.9369515653281077], [33145, 0.937196158170983], [33159, 0.9369924009280339], [33187, 0.9369293583851839], [33201, 0.9370647914847975], [33215, 0.9370295711043879], [33229, 0.9369856222820148], [33243, 0.9370252310710803], [33271, 0.93688585374982], [33299, 0.9369467158646638], [33313, 0.9369884209318767], [33327, 0.9370552452132763], [33341, 0.9370683296779793], [33355, 0.9370491403963865], [33369, 0.9370697921021364], [33383, 0.9370277881758065], [33397, 0.9370768691975904], [33411, 0.9371247085878582], [33425, 0.9370805920410223], [33439, 0.9369981680097714], [33453, 0.9369961196967896], [33467, 0.9369569391181305], [33523, 0.9369895119371746], [33537, 0.9370058204058713], [33551, 0.9369869582918874], [33649, 0.9369838930474592], [33705, 0.9371158595914374], [33719, 0.9370287438550752], [33733, 0.9369775092208187], [33747, 0.9370431771150489], [33761, 0.9370705029435537], [33775, 0.9369762685585881], [33803, 0.9369984743006556], [33817, 0.9369935871194539], [33831, 0.9369766570393626], [33845, 0.9368546996906173], [34041, 0.9370101339710839], [34055, 0.9369727133965703], [34069, 0.9370534971531631], [34083, 0.9370368336142844], [34125, 0.936926318034555], [34139, 0.9370522060609088], [34153, 0.9370495180239887], [34167, 0.9370121402609861]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LassoBenchmark.peakmem_fit.json b/graphs/summary/linear_model.LassoBenchmark.peakmem_fit.json index a40a25f8de..5b1a4142f4 100644 --- a/graphs/summary/linear_model.LassoBenchmark.peakmem_fit.json +++ b/graphs/summary/linear_model.LassoBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 494424263.887413], [29225, 490159403.62937343], [29239, 490298771.4053316], [29253, 490316361.56211716], [29267, 490392175.8990902], [29281, 490663722.6210644], [29295, 490472964.3581856], [29309, 490565132.9499972], [29323, 490410890.3578819], [29337, 490787370.68207884], [29351, 489336696.7354927], [29365, 489193031.68370587], [29379, 489591385.4750054], [29393, 489577588.8592837], [29407, 489425629.6036731], [29421, 489343300.3178184], [29435, 490040397.44343215], [29449, 490077430.2210007], [29463, 490055496.29103726], [29477, 489966587.223688], [29547, 490436758.9689494], [29561, 490142257.1610072], [29575, 489499679.85559165], [29603, 491483849.57460034], [29617, 491470621.96160364], [29631, 492331803.1247039], [29645, 491693745.66640383], [29659, 491523352.84208596], [29673, 491408718.7410907], [29743, 491470213.5740746], [29757, 491700848.35896164], [29771, 491595602.9190243], [29785, 491636645.28599006], [29799, 491741656.1254834], [29813, 491908134.7777573], [29827, 492355098.8327297], [29841, 491808008.4188699], [29855, 491577581.9241798], [29869, 491935071.80461025], [30009, 492002273.912157], [30023, 491906808.23726344], [30037, 491622623.7346967], [30051, 491433020.5061883], [30065, 491321810.8651882], [30079, 491562420.44189113], [30093, 491498197.21073854], [30107, 491576976.8106405], [30121, 491723622.32591563], [30135, 491471914.72514254], [30149, 491913862.34192], [30163, 492083826.99991703], [30177, 492311077.05561244], [30191, 492371377.0440242], [30205, 492541070.87927014], [30219, 492373254.28065526], [30233, 492121452.5342226], [30247, 492286637.417662], [30261, 492015286.54585594], [30513, 492533614.8329283], [30527, 492400778.3441351], [30541, 492021026.15252656], [30555, 491979231.46855193], [30569, 492015847.3358553], [30583, 492366693.8351854], [30597, 491872845.9903943], [30625, 492157813.7837965], [30639, 492393218.74141514], [30653, 492006742.34562975], [30667, 492964782.9635829], [30681, 493540007.6460252], [30695, 492064380.39266306], [30709, 492156774.55888575], [30723, 492099144.43649715], [30737, 492066639.57644004], [30751, 492280837.7597071], [30765, 492738665.43774], [30779, 492144148.6501014], [30793, 492284409.6246491], [30807, 492507443.0935309], [30821, 492606342.54095], [30835, 492967751.6331148], [30849, 492309191.11052114], [30863, 492337975.9674865], [30877, 492512333.4601991], [30891, 492448059.02571285], [30905, 492378777.7008155], [30919, 492389960.4983867], [30933, 492555027.0392988], [30947, 492551234.86150265], [30961, 492565948.6945242], [30975, 492339663.87483203], [30989, 492427524.72197765], [31003, 492471485.2386535], [31017, 492482046.7374673], [31031, 492659350.25857234], [31045, 492491101.863081], [32095, 512575178.6191761], [32109, 512248124.8315687], [32123, 512448586.4146705], [32137, 512330761.397309], [32151, 512290139.1165883], [32165, 512447694.02118826], [32179, 512041409.8892504], [32193, 512535657.53388023], [32207, 514490636.5386758], [32221, 516910617.19640476], [32235, 517345624.4122993], [32249, 516651337.05238926], [32263, 516784749.6868919], [32277, 516852284.1744383], [32305, 518343250.69599384], [32319, 522021010.9747322], [32333, 522090439.36020106], [32347, 522019214.63740104], [32361, 522110422.3792427], [32375, 521758940.9415227], [32389, 521973262.5174221], [32403, 522113443.66150534], [32417, 521946428.86238766], [32431, 522162195.5990128], [32445, 522389036.49911267], [32585, 522561266.43334], [32599, 522632297.64312464], [32613, 522601774.52768517], [32627, 522951865.8146502], [32641, 522515912.17193276], [32655, 522552771.6403256], [32851, 523988785.82830185], [32865, 523989367.32602936], [32879, 524064010.6800385], [32893, 524204640.301747], [32907, 524050532.53255314], [32921, 523855392.1642424], [32991, 524224130.7232816], [33005, 523999641.4686044], [33019, 523382825.80761427], [33033, 523927024.12340933], [33047, 524207463.8786422], [33061, 524431958.8893995], [33075, 524379385.8442034], [33089, 548316092.432381], [33103, 572086527.46542], [33117, 572316626.7863865], [33131, 571855193.6399825], [33145, 572754282.5602958], [33159, 572675724.2282543], [33187, 524993885.625453], [33201, 524525056.86653864], [33215, 522603178.4264408], [33229, 517242302.36830413], [33243, 517185612.4260711], [33271, 509211655.96623605], [33299, 509541126.2463707], [33313, 509956116.9299999], [33327, 510241588.1527133], [33341, 510421794.12892014], [33355, 510715022.2716462], [33369, 511386018.1974766], [33383, 511875162.0720623], [33397, 512361168.4714707], [33411, 512581969.1871303], [33425, 512695603.84466773], [33439, 514241867.2105607], [33453, 506279038.969245], [33467, 506211237.1209666], [33523, 506592492.00122774], [33537, 506720740.95826334], [33551, 505635049.63263434], [33649, 504414395.9907102], [33705, 503592533.078821], [33719, 503933027.1108928], [33733, 503832817.1008688], [33747, 503587854.303584], [33761, 504025543.40270275], [33775, 503752791.58648723], [33803, 503803421.1744329], [33817, 503462530.33839375], [33831, 503555636.3550558], [33845, 503256812.05628896], [34041, 503204958.0089627], [34055, 503483814.85429114], [34069, 503404824.37629014], [34083, 503050297.4857491], [34125, 503302595.7271425], [34139, 503563947.6211833], [34153, 503088101.6775813], [34167, 503333648.6756391]] \ No newline at end of file +[[28511, 494424263.887413], [29225, 490159403.62937343], [29239, 490298771.4053316], [29253, 490316361.56211716], [29267, 490392175.8990902], [29281, 490663722.6210644], [29295, 490472964.3581856], [29309, 490565132.9499972], [29323, 490410890.3578819], [29337, 490787370.68207884], [29351, 489336696.7354927], [29365, 489193031.68370587], [29379, 489591385.4750054], [29393, 489577588.8592837], [29407, 489425629.6036731], [29421, 489343300.3178184], [29435, 490040397.44343215], [29449, 490077430.2210007], [29463, 490055496.29103726], [29477, 489966587.223688], [29547, 490436758.9689494], [29561, 490142257.1610072], [29575, 489499679.85559165], [29603, 491483849.57460034], [29617, 491470621.96160364], [29631, 492331803.1247039], [29645, 491693745.66640383], [29659, 491523352.84208596], [29673, 491408718.7410907], [29743, 491470213.5740746], [29757, 491700848.35896164], [29771, 491595602.9190243], [29785, 491636645.28599006], [29799, 491741656.1254834], [29813, 491908134.7777573], [29827, 492355098.8327297], [29841, 491808008.4188699], [29855, 491577581.9241798], [29869, 491935071.80461025], [30009, 492002273.912157], [30023, 491906808.23726344], [30037, 491622623.7346967], [30051, 491433020.5061883], [30065, 491321810.8651882], [30079, 491562420.44189113], [30093, 491498197.21073854], [30107, 491576976.8106405], [30121, 491723622.32591563], [30135, 491471914.72514254], [30149, 491913862.34192], [30163, 492083826.99991703], [30177, 492311077.05561244], [30191, 492371377.0440242], [30205, 492541070.87927014], [30219, 492373254.28065526], [30233, 492121452.5342226], [30247, 492286637.417662], [30261, 492015286.54585594], [30513, 492533614.8329283], [30527, 492400778.3441351], [30541, 492021026.15252656], [30555, 491979231.46855193], [30569, 492015847.3358553], [30583, 492366693.8351854], [30597, 491872845.9903943], [30625, 492157813.7837965], [30639, 492393218.74141514], [30653, 492006742.34562975], [30667, 492964782.9635829], [30681, 493540007.6460252], [30695, 492064380.39266306], [30709, 492156774.55888575], [30723, 492099144.43649715], [30737, 492066639.57644004], [30751, 492280837.7597071], [30765, 492738665.43774], [30779, 492144148.6501014], [30793, 492284409.6246491], [30807, 492507443.0935309], [30821, 492606342.54095], [30835, 492967751.6331148], [30849, 492309191.11052114], [30863, 492337975.9674865], [30877, 492512333.4601991], [30891, 492448059.02571285], [30905, 492378777.7008155], [30919, 492389960.4983867], [30933, 492555027.0392988], [30947, 492551234.86150265], [30961, 492565948.6945242], [30975, 492339663.87483203], [30989, 492427524.72197765], [31003, 492471485.2386535], [31017, 492482046.7374673], [31031, 492659350.25857234], [31045, 492491101.863081], [32095, 512575178.6191761], [32109, 512248124.8315687], [32123, 512448586.4146705], [32137, 512330761.397309], [32151, 512290139.1165883], [32165, 512447694.02118826], [32179, 512041409.8892504], [32193, 512535657.53388023], [32207, 514490636.5386758], [32221, 516910617.19640476], [32235, 517345624.4122993], [32249, 516651337.05238926], [32263, 516784749.6868919], [32277, 516852284.1744383], [32305, 518343250.69599384], [32319, 522021010.9747322], [32333, 522090439.36020106], [32347, 522019214.63740104], [32361, 522110422.3792427], [32375, 521758940.9415227], [32389, 521973262.5174221], [32403, 522113443.66150534], [32417, 521946428.86238766], [32431, 522162195.5990128], [32445, 522389036.49911267], [32585, 522561266.43334], [32599, 522632297.64312464], [32613, 522601774.52768517], [32627, 522951865.8146502], [32641, 522515912.17193276], [32655, 522552771.6403256], [32851, 523988785.82830185], [32865, 523989367.32602936], [32879, 524064010.6800385], [32893, 524204640.301747], [32907, 524050532.53255314], [32921, 523855392.1642424], [32991, 524224130.7232816], [33005, 523999641.4686044], [33019, 523382825.80761427], [33033, 523927024.12340933], [33047, 524207463.8786422], [33061, 524431958.8893995], [33075, 524379385.8442034], [33089, 548316092.432381], [33103, 572086527.46542], [33117, 572316626.7863865], [33131, 571855193.6399825], [33145, 572754282.5602958], [33159, 572675724.2282543], [33187, 524993885.625453], [33201, 524525056.86653864], [33215, 522603178.4264408], [33229, 517242302.36830413], [33243, 517185612.4260711], [33271, 509211655.96623605], [33299, 509541126.2463707], [33313, 509956116.9299999], [33327, 510241588.1527133], [33341, 510421794.12892014], [33355, 510715022.2716462], [33369, 511386018.1974766], [33383, 511875162.0720623], [33397, 512361168.4714707], [33411, 512581969.1871303], [33425, 512695603.84466773], [33439, 514241867.2105607], [33453, 506279038.969245], [33467, 506211237.1209666], [33523, 506592492.00122774], [33537, 506720740.95826334], [33551, 505635049.63263434], [33649, 504414395.9907102], [33705, 503592533.078821], [33719, 503933027.1108928], [33733, 503832817.1008688], [33747, 503587854.303584], [33761, 504025543.40270275], [33775, 503752791.58648723], [33803, 503803421.1744329], [33817, 503462530.33839375], [33831, 503555636.3550558], [33845, 503256812.05628896], [34041, 503204958.0089627], [34055, 503483814.85429114], [34069, 503404824.37629014], [34083, 503050297.4857491], [34125, 503302595.7271425], [34139, 503563947.6211833], [34153, 503088101.6775813], [34167, 503271909.2245375]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LassoBenchmark.peakmem_predict.json b/graphs/summary/linear_model.LassoBenchmark.peakmem_predict.json index 56d489c964..5d49e26218 100644 --- a/graphs/summary/linear_model.LassoBenchmark.peakmem_predict.json +++ b/graphs/summary/linear_model.LassoBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28511, 278430059.03500324], [29225, 274493785.13078773], [29239, 274300340.8399825], [29253, 273545308.627759], [29267, 274078559.2845665], [29281, 274355800.1977507], [29295, 274417337.4503122], [29309, 273827256.50719315], [29323, 274017603.08374095], [29337, 274473466.31210756], [29351, 273581528.1028343], [29365, 273436486.94747096], [29379, 273782342.18613523], [29393, 273703487.27820045], [29407, 273420760.4552166], [29421, 273614985.21209085], [29435, 274473876.29956967], [29449, 275046011.4804701], [29463, 274984316.62298375], [29477, 275197599.3627937], [29547, 275322093.69603026], [29561, 275178177.6139147], [29575, 274721738.76294744], [29603, 276300712.78638744], [29617, 276037154.4798701], [29631, 276234977.9388562], [29645, 276424944.87628525], [29659, 276184681.97585744], [29673, 276033791.788504], [29743, 276355883.5210314], [29757, 276342161.8101063], [29771, 276275359.53071606], [29785, 276102417.5244591], [29799, 276360994.2070327], [29813, 276421768.15591675], [29827, 276598305.1270646], [29841, 276459262.7967961], [29855, 275996332.68871635], [29869, 276269721.8323449], [30009, 276255734.01029825], [30023, 276438368.6489053], [30037, 276255116.85916203], [30051, 276424716.3601824], [30065, 276491212.49777454], [30079, 276553211.0520562], [30093, 276115078.1398324], [30107, 276103598.4849243], [30121, 276494197.3484041], [30135, 276203159.9439576], [30149, 276540994.03946066], [30163, 276916563.03173524], [30177, 277362863.96998227], [30191, 277083257.9219979], [30205, 277081295.45415187], [30219, 277071698.40289986], [30233, 276486100.9349837], [30247, 277026800.87239194], [30261, 276636534.94248646], [30513, 277067156.0589191], [30527, 276853885.6211248], [30541, 276788936.4647762], [30555, 276865109.1206323], [30569, 276812182.450253], [30583, 277011484.72883385], [30597, 276876695.8211696], [30625, 277089243.3604451], [30639, 277064695.7990362], [30653, 276839057.75049084], [30667, 276891026.1542366], [30681, 277021450.5089826], [30695, 277186285.7921495], [30709, 277029190.7899607], [30723, 276911486.0357579], [30737, 277022663.0320322], [30751, 277007826.87873346], [30765, 277584171.07391423], [30779, 276945348.2072664], [30793, 277019443.7063568], [30807, 276935578.0351913], [30821, 277268926.49780273], [30835, 277341378.0677583], [30849, 277201507.4320798], [30863, 277372312.1424675], [30877, 277382670.1386235], [30891, 277354763.30219436], [30905, 277324675.3009586], [30919, 276922790.90822834], [30933, 277062344.86933684], [30947, 277303740.25955606], [30961, 277159673.3536685], [30975, 277235737.8560948], [30989, 277361446.47612375], [31003, 277615758.2832695], [31017, 277335105.47588325], [31031, 276744656.5326886], [31045, 277151671.87127846], [32095, 293063259.35477597], [32109, 292975953.79643285], [32123, 293142519.56895196], [32137, 293181518.80545264], [32151, 293012352.1388221], [32165, 293035659.8278798], [32179, 292843604.9835968], [32193, 293234167.19153637], [32207, 294933484.48891914], [32221, 296916914.60441846], [32235, 296782506.2981052], [32249, 296744048.84291327], [32263, 296508108.49792725], [32277, 296341928.44855076], [32305, 297885845.24874735], [32319, 300794924.58136475], [32333, 300773845.0949727], [32347, 300711819.4721997], [32361, 300785849.19138926], [32375, 300972887.5647343], [32389, 300623356.5943241], [32403, 300817006.58595014], [32417, 300741645.4065015], [32431, 300770021.96393496], [32445, 301101506.068021], [32585, 301169196.1774252], [32599, 301272234.03095055], [32613, 301286583.5786328], [32627, 301420728.18244714], [32641, 301177360.5528964], [32655, 301205729.170035], [32851, 302470725.7781648], [32865, 302437893.62505245], [32879, 302531826.8597694], [32893, 302653178.26783496], [32907, 302718208.5574588], [32921, 302898970.80437744], [32991, 302827907.95708865], [33005, 302713675.60081077], [33019, 302270548.8928939], [33033, 302832806.352422], [33047, 302847669.1367419], [33061, 303125549.10006154], [33075, 302878070.4063652], [33089, 308058462.96075606], [33103, 313418016.72896856], [33117, 313593389.4936544], [33131, 313192012.34522426], [33145, 313776872.4276417], [33159, 313843841.45398074], [33187, 303238769.30874234], [33201, 303016320.0184883], [33215, 301363025.5201441], [33229, 296558908.94687015], [33243, 296676151.3769116], [33271, 289992741.9605611], [33299, 290080275.3329541], [33313, 290417733.9365144], [33327, 290368154.53251565], [33341, 290609108.94244623], [33355, 290977928.77161163], [33369, 291457865.45127565], [33383, 291825067.3714511], [33397, 292387457.35733575], [33411, 292234821.06887966], [33425, 292472873.90053684], [33439, 293845213.6129694], [33453, 287401316.7063033], [33467, 287521015.187896], [33523, 287447604.84695], [33537, 287717561.2170313], [33551, 286891085.2450792], [33649, 285436197.2552001], [33705, 285138539.567734], [33719, 285146695.4741372], [33733, 285107891.724243], [33747, 285286887.6674884], [33761, 285302581.5772614], [33775, 285494578.3454899], [33803, 285028399.1527541], [33817, 284567644.69312024], [33831, 284680350.0305186], [33845, 284640454.40559405], [34041, 284529651.6480789], [34055, 284953288.6426937], [34069, 284602813.15972644], [34083, 284915904.0180424], [34125, 284836544.52185315], [34139, 284945918.9614556], [34153, 284723727.5932255], [34167, 284725834.71458244]] \ No newline at end of file +[[28511, 278430059.03500324], [29225, 274493785.13078773], [29239, 274300340.8399825], [29253, 273545308.627759], [29267, 274078559.2845665], [29281, 274355800.1977507], [29295, 274417337.4503122], [29309, 273827256.50719315], [29323, 274017603.08374095], [29337, 274473466.31210756], [29351, 273581528.1028343], [29365, 273436486.94747096], [29379, 273782342.18613523], [29393, 273703487.27820045], [29407, 273420760.4552166], [29421, 273614985.21209085], [29435, 274473876.29956967], [29449, 275046011.4804701], [29463, 274984316.62298375], [29477, 275197599.3627937], [29547, 275322093.69603026], [29561, 275178177.6139147], [29575, 274721738.76294744], [29603, 276300712.78638744], [29617, 276037154.4798701], [29631, 276234977.9388562], [29645, 276424944.87628525], [29659, 276184681.97585744], [29673, 276033791.788504], [29743, 276355883.5210314], [29757, 276342161.8101063], [29771, 276275359.53071606], [29785, 276102417.5244591], [29799, 276360994.2070327], [29813, 276421768.15591675], [29827, 276598305.1270646], [29841, 276459262.7967961], [29855, 275996332.68871635], [29869, 276269721.8323449], [30009, 276255734.01029825], [30023, 276438368.6489053], [30037, 276255116.85916203], [30051, 276424716.3601824], [30065, 276491212.49777454], [30079, 276553211.0520562], [30093, 276115078.1398324], [30107, 276103598.4849243], [30121, 276494197.3484041], [30135, 276203159.9439576], [30149, 276540994.03946066], [30163, 276916563.03173524], [30177, 277362863.96998227], [30191, 277083257.9219979], [30205, 277081295.45415187], [30219, 277071698.40289986], [30233, 276486100.9349837], [30247, 277026800.87239194], [30261, 276636534.94248646], [30513, 277067156.0589191], [30527, 276853885.6211248], [30541, 276788936.4647762], [30555, 276865109.1206323], [30569, 276812182.450253], [30583, 277011484.72883385], [30597, 276876695.8211696], [30625, 277089243.3604451], [30639, 277064695.7990362], [30653, 276839057.75049084], [30667, 276891026.1542366], [30681, 277021450.5089826], [30695, 277186285.7921495], [30709, 277029190.7899607], [30723, 276911486.0357579], [30737, 277022663.0320322], [30751, 277007826.87873346], [30765, 277584171.07391423], [30779, 276945348.2072664], [30793, 277019443.7063568], [30807, 276935578.0351913], [30821, 277268926.49780273], [30835, 277341378.0677583], [30849, 277201507.4320798], [30863, 277372312.1424675], [30877, 277382670.1386235], [30891, 277354763.30219436], [30905, 277324675.3009586], [30919, 276922790.90822834], [30933, 277062344.86933684], [30947, 277303740.25955606], [30961, 277159673.3536685], [30975, 277235737.8560948], [30989, 277361446.47612375], [31003, 277615758.2832695], [31017, 277335105.47588325], [31031, 276744656.5326886], [31045, 277151671.87127846], [32095, 293063259.35477597], [32109, 292975953.79643285], [32123, 293142519.56895196], [32137, 293181518.80545264], [32151, 293012352.1388221], [32165, 293035659.8278798], [32179, 292843604.9835968], [32193, 293234167.19153637], [32207, 294933484.48891914], [32221, 296916914.60441846], [32235, 296782506.2981052], [32249, 296744048.84291327], [32263, 296508108.49792725], [32277, 296341928.44855076], [32305, 297885845.24874735], [32319, 300794924.58136475], [32333, 300773845.0949727], [32347, 300711819.4721997], [32361, 300785849.19138926], [32375, 300972887.5647343], [32389, 300623356.5943241], [32403, 300817006.58595014], [32417, 300741645.4065015], [32431, 300770021.96393496], [32445, 301101506.068021], [32585, 301169196.1774252], [32599, 301272234.03095055], [32613, 301286583.5786328], [32627, 301420728.18244714], [32641, 301177360.5528964], [32655, 301205729.170035], [32851, 302470725.7781648], [32865, 302437893.62505245], [32879, 302531826.8597694], [32893, 302653178.26783496], [32907, 302718208.5574588], [32921, 302898970.80437744], [32991, 302827907.95708865], [33005, 302713675.60081077], [33019, 302270548.8928939], [33033, 302832806.352422], [33047, 302847669.1367419], [33061, 303125549.10006154], [33075, 302878070.4063652], [33089, 308058462.96075606], [33103, 313418016.72896856], [33117, 313593389.4936544], [33131, 313192012.34522426], [33145, 313776872.4276417], [33159, 313843841.45398074], [33187, 303238769.30874234], [33201, 303016320.0184883], [33215, 301363025.5201441], [33229, 296558908.94687015], [33243, 296676151.3769116], [33271, 289992741.9605611], [33299, 290080275.3329541], [33313, 290417733.9365144], [33327, 290368154.53251565], [33341, 290609108.94244623], [33355, 290977928.77161163], [33369, 291457865.45127565], [33383, 291825067.3714511], [33397, 292387457.35733575], [33411, 292234821.06887966], [33425, 292472873.90053684], [33439, 293845213.6129694], [33453, 287401316.7063033], [33467, 287521015.187896], [33523, 287447604.84695], [33537, 287717561.2170313], [33551, 286891085.2450792], [33649, 285436197.2552001], [33705, 285138539.567734], [33719, 285146695.4741372], [33733, 285107891.724243], [33747, 285286887.6674884], [33761, 285302581.5772614], [33775, 285494578.3454899], [33803, 285028399.1527541], [33817, 284567644.69312024], [33831, 284680350.0305186], [33845, 284640454.40559405], [34041, 284529651.6480789], [34055, 284953288.6426937], [34069, 284602813.15972644], [34083, 284915904.0180424], [34125, 284836544.52185315], [34139, 284945918.9614556], [34153, 284723727.5932255], [34167, 284747341.18926364]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LassoBenchmark.time_fit.json b/graphs/summary/linear_model.LassoBenchmark.time_fit.json index 457db250bf..1a94c95850 100644 --- a/graphs/summary/linear_model.LassoBenchmark.time_fit.json +++ b/graphs/summary/linear_model.LassoBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 1.122644203039311], [29225, 1.746238261284628], [29239, 1.8705734584751803], [29253, 1.194624477353634], [29267, 1.1282125287118379], [29281, 1.2336368723917448], [29295, 1.2381030136646893], [29309, 1.1784557008780383], [29323, 1.1454639875323107], [29337, 1.1223674700548194], [29351, 1.183556594632121], [29365, 1.3431982977079406], [29379, 1.2340564148077604], [29393, 1.2031548197742028], [29407, 1.1263947949267386], [29421, 1.1648954991552434], [29435, 1.2234931358802317], [29449, 2.2030474503131128], [29463, 2.2949473645461875], [29477, 2.1107992058709035], [29547, 2.530527041516132], [29561, 1.9015123980660633], [29575, 1.7953428915872074], [29603, 1.7506052691615896], [29617, 1.740871189856846], [29631, 1.8005341416188267], [29645, 1.7602899089109996], [29659, 1.7630213164979938], [29673, 1.7945424621675317], [29743, 1.7364751284434807], [29757, 1.7945808815749635], [29771, 1.768900940845517], [29785, 1.9309789489127254], [29799, 1.8783976307353423], [29813, 1.977934912095724], [29827, 1.986450997370531], [29841, 1.7342148065337994], [29855, 1.8345929050581637], [29869, 1.929604457716316], [30009, 1.9436845524457587], [30023, 1.9076875346223188], [30037, 1.9000168956775099], [30051, 1.842156578526156], [30065, 1.9176973900783123], [30079, 1.993009719697722], [30093, 1.923828821085036], [30107, 1.7839412455660006], [30121, 1.8298227492232808], [30135, 1.9651480494814406], [30149, 1.9826765925530658], [30163, 1.918367937067005], [30177, 1.884358537708243], [30191, 1.9477896429257728], [30205, 1.9091976014286374], [30219, 1.8411780070634527], [30233, 2.0047129856687107], [30247, 1.963574209782092], [30261, 1.9381930766142335], [30513, 1.9159482704962596], [30527, 1.9138513855922716], [30541, 2.015876226560001], [30555, 1.852308701156079], [30569, 1.974334748312847], [30583, 1.7720489988222894], [30597, 1.7520170980703909], [30625, 1.994151823336317], [30639, 1.8361522289748708], [30653, 1.922204052582179], [30667, 1.8673837032509324], [30681, 1.8672088267082045], [30695, 2.1486379465737717], [30709, 1.7614092911676535], [30723, 1.8004295293512074], [30737, 1.875603273954285], [30751, 1.975409496368757], [30765, 1.8784461471207015], [30779, 1.8596681373813486], [30793, 1.8565400878611766], [30807, 2.0631361838808138], [30821, 1.9220052131375835], [30835, 1.998531164617125], [30849, 1.9414593961026854], [30863, 1.9976281268709988], [30877, 1.8096055629855354], [30891, 1.7725880655651516], [30905, 1.8429721069521374], [30919, 1.9086698065645933], [30933, 1.873238587062577], [30947, 1.81026146969063], [30961, 1.8254780399145762], [30975, 1.7966310490453778], [30989, 1.8180062567866873], [31003, 1.7439048811796134], [31017, 1.9298102736112923], [31031, 1.8609400318990017], [31045, 1.790195164174829], [32095, 1.8254992600558675], [32109, 1.8059753359271435], [32123, 1.7934005503604817], [32137, 1.7757818784668695], [32151, 1.8064940808117984], [32165, 1.8059214096063143], [32179, 1.847313181482955], [32193, 1.8224969099259594], [32207, 1.810225185096121], [32221, 1.809232681320644], [32235, 1.8371456068783076], [32249, 1.8271901500908374], [32263, 1.737897116867393], [32277, 1.7788557700220533], [32305, 1.6968325106539348], [32319, 1.7105891790299808], [32333, 2.0026161779820892], [32347, 1.8112835609625018], [32361, 1.756366229664608], [32375, 1.6116629670729272], [32389, 1.958357338472627], [32403, 1.7685632962344062], [32417, 1.9074846556115592], [32431, 1.9615137331794796], [32445, 1.7301428311313412], [32585, 1.7058306013585434], [32599, 1.7395394116675849], [32613, 1.7448455615950296], [32627, 1.741031927472135], [32641, 1.700081683980533], [32655, 1.7345013968218284], [32851, 1.8645248386564643], [32865, 1.831988211193549], [32879, 1.8443583942688466], [32893, 1.906391365522691], [32907, 1.8787527601879328], [32921, 1.7965219851915206], [32991, 1.7832352027973883], [33005, 1.866642302291509], [33019, 1.8136255720067842], [33033, 1.8307746116522772], [33047, 1.8732161561111778], [33061, 1.8555140109238808], [33075, 1.8209245545507695], [33089, 1.8482591662682066], [33103, 1.820084550976384], [33117, 1.8336607661153261], [33131, 1.804472370941109], [33145, 1.8914894463051297], [33159, 1.7943860814896389], [33187, 1.846318961037974], [33201, 1.8087029165836275], [33215, 1.8374799513460998], [33229, 1.8635530036453463], [33243, 1.9014480591198484], [33271, 1.9546852297157271], [33299, 1.935317353461234], [33313, 1.9141666085258875], [33327, 1.979997055489573], [33341, 1.9009257593614484], [33355, 2.0384441876897053], [33369, 1.9125403234749327], [33383, 1.851291803650754], [33397, 2.039653165529957], [33411, 1.9404564425865554], [33425, 1.996074770704861], [33439, 1.9841100609797522], [33453, 1.8525468204144915], [33467, 2.0538535091729186], [33523, 1.9389121025537852], [33537, 2.0023818901710815], [33551, 1.9806851895555717], [33649, 1.8367292184738482], [33705, 1.854075999336278], [33719, 1.9659479159591549], [33733, 2.008371782036743], [33747, 1.847197256203205], [33761, 1.785871802374101], [33775, 1.8536752628058741], [33803, 1.9850223670956404], [33817, 1.8735643078888402], [33831, 1.896699812182887], [33845, 1.950010331949544], [34041, 1.9563430966161304], [34055, 1.9351161500255305], [34069, 1.9392762443084768], [34083, 1.908449118677195], [34125, 1.9262926601551864], [34139, 1.9548026572401889], [34153, 1.9073990742613525], [34167, 1.9151704073534819]] \ No newline at end of file +[[28511, 1.122644203039311], [29225, 1.746238261284628], [29239, 1.8705734584751803], [29253, 1.194624477353634], [29267, 1.1282125287118379], [29281, 1.2336368723917448], [29295, 1.2381030136646893], [29309, 1.1784557008780383], [29323, 1.1454639875323107], [29337, 1.1223674700548194], [29351, 1.183556594632121], [29365, 1.3431982977079406], [29379, 1.2340564148077604], [29393, 1.2031548197742028], [29407, 1.1263947949267386], [29421, 1.1648954991552434], [29435, 1.2234931358802317], [29449, 2.2030474503131128], [29463, 2.2949473645461875], [29477, 2.1107992058709035], [29547, 2.530527041516132], [29561, 1.9015123980660633], [29575, 1.7953428915872074], [29603, 1.7506052691615896], [29617, 1.740871189856846], [29631, 1.8005341416188267], [29645, 1.7602899089109996], [29659, 1.7630213164979938], [29673, 1.7945424621675317], [29743, 1.7364751284434807], [29757, 1.7945808815749635], [29771, 1.768900940845517], [29785, 1.9309789489127254], [29799, 1.8783976307353423], [29813, 1.977934912095724], [29827, 1.986450997370531], [29841, 1.7342148065337994], [29855, 1.8345929050581637], [29869, 1.929604457716316], [30009, 1.9436845524457587], [30023, 1.9076875346223188], [30037, 1.9000168956775099], [30051, 1.842156578526156], [30065, 1.9176973900783123], [30079, 1.993009719697722], [30093, 1.923828821085036], [30107, 1.7839412455660006], [30121, 1.8298227492232808], [30135, 1.9651480494814406], [30149, 1.9826765925530658], [30163, 1.918367937067005], [30177, 1.884358537708243], [30191, 1.9477896429257728], [30205, 1.9091976014286374], [30219, 1.8411780070634527], [30233, 2.0047129856687107], [30247, 1.963574209782092], [30261, 1.9381930766142335], [30513, 1.9159482704962596], [30527, 1.9138513855922716], [30541, 2.015876226560001], [30555, 1.852308701156079], [30569, 1.974334748312847], [30583, 1.7720489988222894], [30597, 1.7520170980703909], [30625, 1.994151823336317], [30639, 1.8361522289748708], [30653, 1.922204052582179], [30667, 1.8673837032509324], [30681, 1.8672088267082045], [30695, 2.1486379465737717], [30709, 1.7614092911676535], [30723, 1.8004295293512074], [30737, 1.875603273954285], [30751, 1.975409496368757], [30765, 1.8784461471207015], [30779, 1.8596681373813486], [30793, 1.8565400878611766], [30807, 2.0631361838808138], [30821, 1.9220052131375835], [30835, 1.998531164617125], [30849, 1.9414593961026854], [30863, 1.9976281268709988], [30877, 1.8096055629855354], [30891, 1.7725880655651516], [30905, 1.8429721069521374], [30919, 1.9086698065645933], [30933, 1.873238587062577], [30947, 1.81026146969063], [30961, 1.8254780399145762], [30975, 1.7966310490453778], [30989, 1.8180062567866873], [31003, 1.7439048811796134], [31017, 1.9298102736112923], [31031, 1.8609400318990017], [31045, 1.790195164174829], [32095, 1.8254992600558675], [32109, 1.8059753359271435], [32123, 1.7934005503604817], [32137, 1.7757818784668695], [32151, 1.8064940808117984], [32165, 1.8059214096063143], [32179, 1.847313181482955], [32193, 1.8224969099259594], [32207, 1.810225185096121], [32221, 1.809232681320644], [32235, 1.8371456068783076], [32249, 1.8271901500908374], [32263, 1.737897116867393], [32277, 1.7788557700220533], [32305, 1.6968325106539348], [32319, 1.7105891790299808], [32333, 2.0026161779820892], [32347, 1.8112835609625018], [32361, 1.756366229664608], [32375, 1.6116629670729272], [32389, 1.958357338472627], [32403, 1.7685632962344062], [32417, 1.9074846556115592], [32431, 1.9615137331794796], [32445, 1.7301428311313412], [32585, 1.7058306013585434], [32599, 1.7395394116675849], [32613, 1.7448455615950296], [32627, 1.741031927472135], [32641, 1.700081683980533], [32655, 1.7345013968218284], [32851, 1.8645248386564643], [32865, 1.831988211193549], [32879, 1.8443583942688466], [32893, 1.906391365522691], [32907, 1.8787527601879328], [32921, 1.7965219851915206], [32991, 1.7832352027973883], [33005, 1.866642302291509], [33019, 1.8136255720067842], [33033, 1.8307746116522772], [33047, 1.8732161561111778], [33061, 1.8555140109238808], [33075, 1.8209245545507695], [33089, 1.8482591662682066], [33103, 1.820084550976384], [33117, 1.8336607661153261], [33131, 1.804472370941109], [33145, 1.8914894463051297], [33159, 1.7943860814896389], [33187, 1.846318961037974], [33201, 1.8087029165836275], [33215, 1.8374799513460998], [33229, 1.8635530036453463], [33243, 1.9014480591198484], [33271, 1.9546852297157271], [33299, 1.935317353461234], [33313, 1.9141666085258875], [33327, 1.979997055489573], [33341, 1.9009257593614484], [33355, 2.0384441876897053], [33369, 1.9125403234749327], [33383, 1.851291803650754], [33397, 2.039653165529957], [33411, 1.9404564425865554], [33425, 1.996074770704861], [33439, 1.9841100609797522], [33453, 1.8525468204144915], [33467, 2.0538535091729186], [33523, 1.9389121025537852], [33537, 2.0023818901710815], [33551, 1.9806851895555717], [33649, 1.8367292184738482], [33705, 1.854075999336278], [33719, 1.9659479159591549], [33733, 2.008371782036743], [33747, 1.847197256203205], [33761, 1.785871802374101], [33775, 1.8536752628058741], [33803, 1.9850223670956404], [33817, 1.8735643078888402], [33831, 1.896699812182887], [33845, 1.950010331949544], [34041, 1.9563430966161304], [34055, 1.9351161500255305], [34069, 1.9392762443084768], [34083, 1.908449118677195], [34125, 1.9262926601551864], [34139, 1.9548026572401889], [34153, 1.9073990742613525], [34167, 1.9102248910451602]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LassoBenchmark.time_predict.json b/graphs/summary/linear_model.LassoBenchmark.time_predict.json index 250f2c3948..01c3d5904d 100644 --- a/graphs/summary/linear_model.LassoBenchmark.time_predict.json +++ b/graphs/summary/linear_model.LassoBenchmark.time_predict.json @@ -1 +1 @@ -[[28511, 0.02716337342981687], [29225, 0.025726711630440442], [29239, 0.027823521453757973], [29253, 0.02816904287626214], [29267, 0.026619796557076525], [29281, 0.029972946173921794], [29295, 0.029077927265744024], [29309, 0.026818002878012403], [29323, 0.027280601384033275], [29337, 0.026557271556141394], [29351, 0.027307242209922283], [29365, 0.027609325447682027], [29379, 0.029234070688475222], [29393, 0.029247918811030487], [29407, 0.026904440898813456], [29421, 0.027364604284380693], [29435, 0.02806715740733599], [29449, 0.03186392487501241], [29463, 0.03147013621304355], [29477, 0.034438260302165645], [29547, 0.0336944296704687], [29561, 0.02829665674587078], [29575, 0.026780433716919815], [29603, 0.0262260854245565], [29617, 0.026403498144951104], [29631, 0.026540809661496887], [29645, 0.02592675140624355], [29659, 0.02639891639348086], [29673, 0.025327317384074597], [29743, 0.025376840837166667], [29757, 0.026619566317452388], [29771, 0.026716507698144643], [29785, 0.03163916523558882], [29799, 0.027461700461328363], [29813, 0.028316188069472226], [29827, 0.02965012811868447], [29841, 0.027810712711541785], [29855, 0.028726239572603646], [29869, 0.027979067100250575], [30009, 0.028977691144984167], [30023, 0.028201325592003265], [30037, 0.0282767643215352], [30051, 0.02845524892919438], [30065, 0.025835786117064656], [30079, 0.028719060420745523], [30093, 0.027159188626211347], [30107, 0.028489924753755256], [30121, 0.027722613213005273], [30135, 0.028717831462534194], [30149, 0.029438759827315336], [30163, 0.027103441510811], [30177, 0.025909465415570727], [30191, 0.027592795037078652], [30205, 0.0287173412901555], [30219, 0.028133808264046666], [30233, 0.029235084087703523], [30247, 0.02750744678152052], [30261, 0.028945202044070834], [30513, 0.028129875447015312], [30527, 0.028920840225409812], [30541, 0.029698246113333052], [30555, 0.028025296616093837], [30569, 0.027206396273884884], [30583, 0.02806066707186196], [30597, 0.027271399577381054], [30625, 0.03020309030120367], [30639, 0.02707399443220533], [30653, 0.029088748223780755], [30667, 0.028279093757865813], [30681, 0.02799199754339977], [30695, 0.030297797894054825], [30709, 0.025586808451797578], [30723, 0.027528445278745983], [30737, 0.02753266040108745], [30751, 0.029131310566488405], [30765, 0.026973988121919323], [30779, 0.025240556659016127], [30793, 0.02854636524351592], [30807, 0.02982452330008918], [30821, 0.028598444412245135], [30835, 0.025468462340359026], [30849, 0.028254987920237177], [30863, 0.02772146395036091], [30877, 0.029314488125894957], [30891, 0.027747460049451705], [30905, 0.025611881192865924], [30919, 0.02770839493758795], [30933, 0.027708958515113832], [30947, 0.026794764340969168], [30961, 0.029937694556000195], [30975, 0.026370524288333547], [30989, 0.028155703273749468], [31003, 0.025945784944683952], [31017, 0.02985352161510337], [31031, 0.028712827880968607], [31045, 0.028653100477698132], [32095, 0.019330348756802992], [32109, 0.019571818757869775], [32123, 0.01915984491593998], [32137, 0.01891909558222609], [32151, 0.01869127911125106], [32165, 0.019397949243240203], [32179, 0.01900373888466117], [32193, 0.01841022123457946], [32207, 0.019231049238962187], [32221, 0.019127361857175503], [32235, 0.019593492694496797], [32249, 0.019412794876675077], [32263, 0.01853515296534533], [32277, 0.01838679183555458], [32305, 0.019615616612762093], [32319, 0.01936293372344779], [32333, 0.019457321787002515], [32347, 0.01983257088239873], [32361, 0.019374041456933017], [32375, 0.017158573923967666], [32389, 0.0197636390064379], [32403, 0.01759017616866082], [32417, 0.019807818760828027], [32431, 0.018580529287399172], [32445, 0.02014248939059088], [32585, 0.019153856199165382], [32599, 0.019372850234705294], [32613, 0.018299253790466898], [32627, 0.018716997604282474], [32641, 0.0190495296843628], [32655, 0.018851021999004635], [32851, 0.01970297806922219], [32865, 0.01851219208136582], [32879, 0.01884643170322509], [32893, 0.01909461099243712], [32907, 0.01922488383871659], [32921, 0.017989933380296762], [32991, 0.018653781644489366], [33005, 0.01875864680531886], [33019, 0.020057592591143127], [33033, 0.018726658304891706], [33047, 0.018601873458355858], [33061, 0.01902787867927327], [33075, 0.018474470332618263], [33089, 0.01885860484919061], [33103, 0.018522595768603666], [33117, 0.018908394337951752], [33131, 0.01883613822680015], [33145, 0.019854571671851264], [33159, 0.018141906696973707], [33187, 0.019710748739281844], [33201, 0.019470834694804588], [33215, 0.018882418998093745], [33229, 0.019003636485769443], [33243, 0.018854911262234604], [33271, 0.018134619193012062], [33299, 0.020138147976786546], [33313, 0.018452512254314643], [33327, 0.0185691694794716], [33341, 0.01974789687977805], [33355, 0.02007044280632364], [33369, 0.019338796325139317], [33383, 0.018563870809310136], [33397, 0.019444137042495473], [33411, 0.01933121127229355], [33425, 0.019445787636892392], [33439, 0.019325613802283266], [33453, 0.0192861741043662], [33467, 0.0203389873007255], [33523, 0.017999184926700523], [33537, 0.019521127042154425], [33551, 0.0196596268173109], [33649, 0.01711390309326824], [33705, 0.018977708060939607], [33719, 0.019843152325847123], [33733, 0.019980566415814808], [33747, 0.019081938247226406], [33761, 0.020495980891526117], [33775, 0.0196388607910998], [33803, 0.020623648829721137], [33817, 0.01970363801943765], [33831, 0.019014560590234843], [33845, 0.019156343285705688], [34041, 0.019832896202680632], [34055, 0.019272158606304476], [34069, 0.019973559806710634], [34083, 0.019799270812136283], [34125, 0.018903988835478377], [34139, 0.01982117617020998], [34153, 0.019373512504017882], [34167, 0.019281109954221595]] \ No newline at end of file +[[28511, 0.02716337342981687], [29225, 0.025726711630440442], [29239, 0.027823521453757973], [29253, 0.02816904287626214], [29267, 0.026619796557076525], [29281, 0.029972946173921794], [29295, 0.029077927265744024], [29309, 0.026818002878012403], [29323, 0.027280601384033275], [29337, 0.026557271556141394], [29351, 0.027307242209922283], [29365, 0.027609325447682027], [29379, 0.029234070688475222], [29393, 0.029247918811030487], [29407, 0.026904440898813456], [29421, 0.027364604284380693], [29435, 0.02806715740733599], [29449, 0.03186392487501241], [29463, 0.03147013621304355], [29477, 0.034438260302165645], [29547, 0.0336944296704687], [29561, 0.02829665674587078], [29575, 0.026780433716919815], [29603, 0.0262260854245565], [29617, 0.026403498144951104], [29631, 0.026540809661496887], [29645, 0.02592675140624355], [29659, 0.02639891639348086], [29673, 0.025327317384074597], [29743, 0.025376840837166667], [29757, 0.026619566317452388], [29771, 0.026716507698144643], [29785, 0.03163916523558882], [29799, 0.027461700461328363], [29813, 0.028316188069472226], [29827, 0.02965012811868447], [29841, 0.027810712711541785], [29855, 0.028726239572603646], [29869, 0.027979067100250575], [30009, 0.028977691144984167], [30023, 0.028201325592003265], [30037, 0.0282767643215352], [30051, 0.02845524892919438], [30065, 0.025835786117064656], [30079, 0.028719060420745523], [30093, 0.027159188626211347], [30107, 0.028489924753755256], [30121, 0.027722613213005273], [30135, 0.028717831462534194], [30149, 0.029438759827315336], [30163, 0.027103441510811], [30177, 0.025909465415570727], [30191, 0.027592795037078652], [30205, 0.0287173412901555], [30219, 0.028133808264046666], [30233, 0.029235084087703523], [30247, 0.02750744678152052], [30261, 0.028945202044070834], [30513, 0.028129875447015312], [30527, 0.028920840225409812], [30541, 0.029698246113333052], [30555, 0.028025296616093837], [30569, 0.027206396273884884], [30583, 0.02806066707186196], [30597, 0.027271399577381054], [30625, 0.03020309030120367], [30639, 0.02707399443220533], [30653, 0.029088748223780755], [30667, 0.028279093757865813], [30681, 0.02799199754339977], [30695, 0.030297797894054825], [30709, 0.025586808451797578], [30723, 0.027528445278745983], [30737, 0.02753266040108745], [30751, 0.029131310566488405], [30765, 0.026973988121919323], [30779, 0.025240556659016127], [30793, 0.02854636524351592], [30807, 0.02982452330008918], [30821, 0.028598444412245135], [30835, 0.025468462340359026], [30849, 0.028254987920237177], [30863, 0.02772146395036091], [30877, 0.029314488125894957], [30891, 0.027747460049451705], [30905, 0.025611881192865924], [30919, 0.02770839493758795], [30933, 0.027708958515113832], [30947, 0.026794764340969168], [30961, 0.029937694556000195], [30975, 0.026370524288333547], [30989, 0.028155703273749468], [31003, 0.025945784944683952], [31017, 0.02985352161510337], [31031, 0.028712827880968607], [31045, 0.028653100477698132], [32095, 0.019330348756802992], [32109, 0.019571818757869775], [32123, 0.01915984491593998], [32137, 0.01891909558222609], [32151, 0.01869127911125106], [32165, 0.019397949243240203], [32179, 0.01900373888466117], [32193, 0.01841022123457946], [32207, 0.019231049238962187], [32221, 0.019127361857175503], [32235, 0.019593492694496797], [32249, 0.019412794876675077], [32263, 0.01853515296534533], [32277, 0.01838679183555458], [32305, 0.019615616612762093], [32319, 0.01936293372344779], [32333, 0.019457321787002515], [32347, 0.01983257088239873], [32361, 0.019374041456933017], [32375, 0.017158573923967666], [32389, 0.0197636390064379], [32403, 0.01759017616866082], [32417, 0.019807818760828027], [32431, 0.018580529287399172], [32445, 0.02014248939059088], [32585, 0.019153856199165382], [32599, 0.019372850234705294], [32613, 0.018299253790466898], [32627, 0.018716997604282474], [32641, 0.0190495296843628], [32655, 0.018851021999004635], [32851, 0.01970297806922219], [32865, 0.01851219208136582], [32879, 0.01884643170322509], [32893, 0.01909461099243712], [32907, 0.01922488383871659], [32921, 0.017989933380296762], [32991, 0.018653781644489366], [33005, 0.01875864680531886], [33019, 0.020057592591143127], [33033, 0.018726658304891706], [33047, 0.018601873458355858], [33061, 0.01902787867927327], [33075, 0.018474470332618263], [33089, 0.01885860484919061], [33103, 0.018522595768603666], [33117, 0.018908394337951752], [33131, 0.01883613822680015], [33145, 0.019854571671851264], [33159, 0.018141906696973707], [33187, 0.019710748739281844], [33201, 0.019470834694804588], [33215, 0.018882418998093745], [33229, 0.019003636485769443], [33243, 0.018854911262234604], [33271, 0.018134619193012062], [33299, 0.020138147976786546], [33313, 0.018452512254314643], [33327, 0.0185691694794716], [33341, 0.01974789687977805], [33355, 0.02007044280632364], [33369, 0.019338796325139317], [33383, 0.018563870809310136], [33397, 0.019444137042495473], [33411, 0.01933121127229355], [33425, 0.019445787636892392], [33439, 0.019325613802283266], [33453, 0.0192861741043662], [33467, 0.0203389873007255], [33523, 0.017999184926700523], [33537, 0.019521127042154425], [33551, 0.0196596268173109], [33649, 0.01711390309326824], [33705, 0.018977708060939607], [33719, 0.019843152325847123], [33733, 0.019980566415814808], [33747, 0.019081938247226406], [33761, 0.020495980891526117], [33775, 0.0196388607910998], [33803, 0.020623648829721137], [33817, 0.01970363801943765], [33831, 0.019014560590234843], [33845, 0.019156343285705688], [34041, 0.019832896202680632], [34055, 0.019272158606304476], [34069, 0.019973559806710634], [34083, 0.019799270812136283], [34125, 0.018903988835478377], [34139, 0.01982117617020998], [34153, 0.019373512504017882], [34167, 0.019302415059751048]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LassoBenchmark.track_test_score.json b/graphs/summary/linear_model.LassoBenchmark.track_test_score.json index fa8c0205e8..e5b8533ae4 100644 --- a/graphs/summary/linear_model.LassoBenchmark.track_test_score.json +++ b/graphs/summary/linear_model.LassoBenchmark.track_test_score.json @@ -1 +1 @@ -[[28511, 0.9343769234007396], [29225, 0.9346272853523011], [29239, 0.9341877383475066], [29253, 0.9346293553176869], [29267, 0.9342702638659101], [29281, 0.9347917296659087], [29295, 0.9343941982081857], [29309, 0.9344603162903388], [29323, 0.9344639459476538], [29337, 0.9343580789909733], [29351, 0.9342980405435869], [29365, 0.9343516644456026], [29379, 0.9340888459036011], [29393, 0.9340408608699704], [29407, 0.9342640874312013], [29421, 0.9343196872667784], [29435, 0.9342219125321148], [29449, 0.9340960995235564], [29463, 0.9342523949078652], [29477, 0.9339419200432382], [29547, 0.934121731385054], [29561, 0.9341868586924909], [29575, 0.9344573641040613], [29603, 0.934243574990592], [29617, 0.9343884746263236], [29631, 0.9344331741309456], [29645, 0.9341973820593594], [29659, 0.9343555991366417], [29673, 0.9344390361166539], [29743, 0.9343835019879554], [29757, 0.9340032426314325], [29771, 0.9344248230848086], [29785, 0.9342346046018941], [29799, 0.934115609808374], [29813, 0.9342115899357987], [29827, 0.9343045480473531], [29841, 0.934594327812247], [29855, 0.9344211800682825], [29869, 0.9343137103987718], [30009, 0.934517938026173], [30023, 0.934371265419425], [30037, 0.9344403782518538], [30051, 0.9342169562831081], [30065, 0.9344179597820962], [30079, 0.9342952412643726], [30093, 0.9343318430443253], [30107, 0.9341895204319518], [30121, 0.9343588868596405], [30135, 0.934326802389877], [30149, 0.9345434093862262], [30163, 0.9340709133684144], [30177, 0.9345009572995749], [30191, 0.9340714945736982], [30205, 0.9347166347878314], [30219, 0.9345233130139388], [30233, 0.9343613660169826], [30247, 0.9344616046000801], [30261, 0.9341915964650761], [30513, 0.9344511880651819], [30527, 0.9344096893843952], [30541, 0.9343668654096176], [30555, 0.9344078302826423], [30569, 0.934439910731916], [30583, 0.934131100232007], [30597, 0.9344836069393576], [30625, 0.9346207869212355], [30639, 0.9343929657033868], [30653, 0.9344304566846834], [30667, 0.9348193151094307], [30681, 0.9343203996629402], [30695, 0.9341898952512092], [30709, 0.9340029336073432], [30723, 0.9343759803912558], [30737, 0.9342627113088897], [30751, 0.934359969752304], [30765, 0.9343378780593768], [30779, 0.9347996959872402], [30793, 0.9343853809892045], [30807, 0.9343146156015827], [30821, 0.9341681795427925], [30835, 0.93499634803097], [30849, 0.9353011526068817], [30863, 0.9346185971535322], [30877, 0.9346696854207586], [30891, 0.9346751313140771], [30905, 0.9342536127254816], [30919, 0.9341108100091654], [30933, 0.9342613779925124], [30947, 0.934168159127805], [30961, 0.9341766081235862], [30975, 0.9345547452133915], [30989, 0.9343941542207829], [31003, 0.9342273048513441], [31017, 0.9336594814131307], [31031, 0.9346694416620145], [31045, 0.9345370505579929], [32095, 0.9343038271624237], [32109, 0.9343143925766815], [32123, 0.934385203408503], [32137, 0.9344670597262742], [32151, 0.9344300741603909], [32165, 0.9346159155408836], [32179, 0.9349508680096796], [32193, 0.9343484265012151], [32207, 0.9344348431216412], [32221, 0.9345419499796703], [32235, 0.934602322146556], [32249, 0.9347160662745051], [32263, 0.934429728871962], [32277, 0.9340605336904693], [32305, 0.9345276561292453], [32319, 0.9346499971060934], [32333, 0.934330605813784], [32347, 0.9342720705147993], [32361, 0.9344320814843179], [32375, 0.934096339310459], [32389, 0.9343621093575115], [32403, 0.9342207662836293], [32417, 0.9344989142701806], [32431, 0.9340683788833382], [32445, 0.934250854188174], [32585, 0.9342936900282598], [32599, 0.9344966074273967], [32613, 0.9341106819453322], [32627, 0.9339310672358851], [32641, 0.9342217943866937], [32655, 0.934309670477833], [32851, 0.9338148628090627], [32865, 0.9342123463733665], [32879, 0.9344788737982742], [32893, 0.934404960762953], [32907, 0.9346617436161163], [32921, 0.9343789404420815], [32991, 0.9343190002041459], [33005, 0.9343722264229002], [33019, 0.934245141563452], [33033, 0.9345739956148142], [33047, 0.9343328052376263], [33061, 0.934203005241566], [33075, 0.9348441901504179], [33089, 0.9340862254271682], [33103, 0.9342246455084213], [33117, 0.9345736734106516], [33131, 0.9343524635570855], [33145, 0.9349524424188385], [33159, 0.9346148466498275], [33187, 0.9342002531918672], [33201, 0.9343449649350698], [33215, 0.9343779362929279], [33229, 0.9342988649090345], [33243, 0.934478328018078], [33271, 0.9343913502560067], [33299, 0.9344107352995378], [33313, 0.9343571874922351], [33327, 0.9343750582740402], [33341, 0.934159421628234], [33355, 0.9343798608361821], [33369, 0.9343716983936446], [33383, 0.9343005152053577], [33397, 0.9343170490833377], [33411, 0.934430685850421], [33425, 0.9343160945771534], [33439, 0.9344563797469712], [33453, 0.9337547604251737], [33467, 0.9340926572456288], [33523, 0.9343342108573476], [33537, 0.934410388141251], [33551, 0.9344011809948505], [33649, 0.9339589258056487], [33705, 0.9343439702322868], [33719, 0.9342939018321701], [33733, 0.933800220335639], [33747, 0.9347530116896201], [33761, 0.9347297552043734], [33775, 0.9345052694321854], [33803, 0.9345730839053871], [33817, 0.9344267401080557], [33831, 0.9341645610870669], [33845, 0.9340542967374208], [34041, 0.9343511543874892], [34055, 0.9341123098630321], [34069, 0.934502748853931], [34083, 0.9344876188386865], [34125, 0.9344614358541072], [34139, 0.9343112292254767], [34153, 0.9346075462144788], [34167, 0.9342735338119837]] \ No newline at end of file +[[28511, 0.9343769234007396], [29225, 0.9346272853523011], [29239, 0.9341877383475066], [29253, 0.9346293553176869], [29267, 0.9342702638659101], [29281, 0.9347917296659087], [29295, 0.9343941982081857], [29309, 0.9344603162903388], [29323, 0.9344639459476538], [29337, 0.9343580789909733], [29351, 0.9342980405435869], [29365, 0.9343516644456026], [29379, 0.9340888459036011], [29393, 0.9340408608699704], [29407, 0.9342640874312013], [29421, 0.9343196872667784], [29435, 0.9342219125321148], [29449, 0.9340960995235564], [29463, 0.9342523949078652], [29477, 0.9339419200432382], [29547, 0.934121731385054], [29561, 0.9341868586924909], [29575, 0.9344573641040613], [29603, 0.934243574990592], [29617, 0.9343884746263236], [29631, 0.9344331741309456], [29645, 0.9341973820593594], [29659, 0.9343555991366417], [29673, 0.9344390361166539], [29743, 0.9343835019879554], [29757, 0.9340032426314325], [29771, 0.9344248230848086], [29785, 0.9342346046018941], [29799, 0.934115609808374], [29813, 0.9342115899357987], [29827, 0.9343045480473531], [29841, 0.934594327812247], [29855, 0.9344211800682825], [29869, 0.9343137103987718], [30009, 0.934517938026173], [30023, 0.934371265419425], [30037, 0.9344403782518538], [30051, 0.9342169562831081], [30065, 0.9344179597820962], [30079, 0.9342952412643726], [30093, 0.9343318430443253], [30107, 0.9341895204319518], [30121, 0.9343588868596405], [30135, 0.934326802389877], [30149, 0.9345434093862262], [30163, 0.9340709133684144], [30177, 0.9345009572995749], [30191, 0.9340714945736982], [30205, 0.9347166347878314], [30219, 0.9345233130139388], [30233, 0.9343613660169826], [30247, 0.9344616046000801], [30261, 0.9341915964650761], [30513, 0.9344511880651819], [30527, 0.9344096893843952], [30541, 0.9343668654096176], [30555, 0.9344078302826423], [30569, 0.934439910731916], [30583, 0.934131100232007], [30597, 0.9344836069393576], [30625, 0.9346207869212355], [30639, 0.9343929657033868], [30653, 0.9344304566846834], [30667, 0.9348193151094307], [30681, 0.9343203996629402], [30695, 0.9341898952512092], [30709, 0.9340029336073432], [30723, 0.9343759803912558], [30737, 0.9342627113088897], [30751, 0.934359969752304], [30765, 0.9343378780593768], [30779, 0.9347996959872402], [30793, 0.9343853809892045], [30807, 0.9343146156015827], [30821, 0.9341681795427925], [30835, 0.93499634803097], [30849, 0.9353011526068817], [30863, 0.9346185971535322], [30877, 0.9346696854207586], [30891, 0.9346751313140771], [30905, 0.9342536127254816], [30919, 0.9341108100091654], [30933, 0.9342613779925124], [30947, 0.934168159127805], [30961, 0.9341766081235862], [30975, 0.9345547452133915], [30989, 0.9343941542207829], [31003, 0.9342273048513441], [31017, 0.9336594814131307], [31031, 0.9346694416620145], [31045, 0.9345370505579929], [32095, 0.9343038271624237], [32109, 0.9343143925766815], [32123, 0.934385203408503], [32137, 0.9344670597262742], [32151, 0.9344300741603909], [32165, 0.9346159155408836], [32179, 0.9349508680096796], [32193, 0.9343484265012151], [32207, 0.9344348431216412], [32221, 0.9345419499796703], [32235, 0.934602322146556], [32249, 0.9347160662745051], [32263, 0.934429728871962], [32277, 0.9340605336904693], [32305, 0.9345276561292453], [32319, 0.9346499971060934], [32333, 0.934330605813784], [32347, 0.9342720705147993], [32361, 0.9344320814843179], [32375, 0.934096339310459], [32389, 0.9343621093575115], [32403, 0.9342207662836293], [32417, 0.9344989142701806], [32431, 0.9340683788833382], [32445, 0.934250854188174], [32585, 0.9342936900282598], [32599, 0.9344966074273967], [32613, 0.9341106819453322], [32627, 0.9339310672358851], [32641, 0.9342217943866937], [32655, 0.934309670477833], [32851, 0.9338148628090627], [32865, 0.9342123463733665], [32879, 0.9344788737982742], [32893, 0.934404960762953], [32907, 0.9346617436161163], [32921, 0.9343789404420815], [32991, 0.9343190002041459], [33005, 0.9343722264229002], [33019, 0.934245141563452], [33033, 0.9345739956148142], [33047, 0.9343328052376263], [33061, 0.934203005241566], [33075, 0.9348441901504179], [33089, 0.9340862254271682], [33103, 0.9342246455084213], [33117, 0.9345736734106516], [33131, 0.9343524635570855], [33145, 0.9349524424188385], [33159, 0.9346148466498275], [33187, 0.9342002531918672], [33201, 0.9343449649350698], [33215, 0.9343779362929279], [33229, 0.9342988649090345], [33243, 0.934478328018078], [33271, 0.9343913502560067], [33299, 0.9344107352995378], [33313, 0.9343571874922351], [33327, 0.9343750582740402], [33341, 0.934159421628234], [33355, 0.9343798608361821], [33369, 0.9343716983936446], [33383, 0.9343005152053577], [33397, 0.9343170490833377], [33411, 0.934430685850421], [33425, 0.9343160945771534], [33439, 0.9344563797469712], [33453, 0.9337547604251737], [33467, 0.9340926572456288], [33523, 0.9343342108573476], [33537, 0.934410388141251], [33551, 0.9344011809948505], [33649, 0.9339589258056487], [33705, 0.9343439702322868], [33719, 0.9342939018321701], [33733, 0.933800220335639], [33747, 0.9347530116896201], [33761, 0.9347297552043734], [33775, 0.9345052694321854], [33803, 0.9345730839053871], [33817, 0.9344267401080557], [33831, 0.9341645610870669], [33845, 0.9340542967374208], [34041, 0.9343511543874892], [34055, 0.9341123098630321], [34069, 0.934502748853931], [34083, 0.9344876188386865], [34125, 0.9344614358541072], [34139, 0.9343112292254767], [34153, 0.9346075462144788], [34167, 0.9343343103985976]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LassoBenchmark.track_train_score.json b/graphs/summary/linear_model.LassoBenchmark.track_train_score.json index e51b8ab8c8..333f870fb1 100644 --- a/graphs/summary/linear_model.LassoBenchmark.track_train_score.json +++ b/graphs/summary/linear_model.LassoBenchmark.track_train_score.json @@ -1 +1 @@ -[[28511, 0.9361485652072762], [29225, 0.9363882559099636], [29239, 0.9362342941502024], [29253, 0.9362866031917982], [29267, 0.9361997614455078], [29281, 0.9361512110354739], [29295, 0.936273121910383], [29309, 0.9362775092972113], [29323, 0.9362938520384694], [29337, 0.9362254623741953], [29351, 0.9361809229231618], [29365, 0.9361597887085454], [29379, 0.9362817796217078], [29393, 0.9361850992857481], [29407, 0.9361305694929953], [29421, 0.9362639608414732], [29435, 0.9361904913806499], [29449, 0.9362314608771216], [29463, 0.9362441743178257], [29477, 0.9361551464681007], [29547, 0.9362416580010883], [29561, 0.9362410448410303], [29575, 0.9361966839961404], [29603, 0.9362062943609151], [29617, 0.9362074924648798], [29631, 0.9363378904700217], [29645, 0.9362203855232705], [29659, 0.9362472147801011], [29673, 0.936264317990268], [29743, 0.9362673648058368], [29757, 0.93618695593679], [29771, 0.9362593248458225], [29785, 0.9362955387633854], [29799, 0.9362648262375733], [29813, 0.9362149292300477], [29827, 0.9362504640709873], [29841, 0.9362806227017086], [29855, 0.9362455840748458], [29869, 0.9363281388205185], [30009, 0.9362238025368718], [30023, 0.9363132244636839], [30037, 0.9362594795226892], [30051, 0.9361678056162127], [30065, 0.9362773901315062], [30079, 0.9362380661461106], [30093, 0.936251532938167], [30107, 0.9362459622757128], [30121, 0.9362241971156003], [30135, 0.9362947905817476], [30149, 0.9361896129556151], [30163, 0.9361815219023676], [30177, 0.9362591132461675], [30191, 0.9362100837484789], [30205, 0.9363309025625465], [30219, 0.936243973999432], [30233, 0.936256364915869], [30247, 0.9362224498954044], [30261, 0.9362535899397835], [30513, 0.9362610251446741], [30527, 0.9361909168095071], [30541, 0.936224947916028], [30555, 0.9362503647916971], [30569, 0.9361973209409917], [30583, 0.9362317215863537], [30597, 0.9363499943770738], [30625, 0.9362514011281794], [30639, 0.9362799796458092], [30653, 0.9362162617915617], [30667, 0.9362648499558517], [30681, 0.9362268509760284], [30695, 0.936082170621395], [30709, 0.9362247520687941], [30723, 0.9362656992826082], [30737, 0.9363260069883228], [30751, 0.9362540641520615], [30765, 0.9362336636157602], [30779, 0.9362865946273528], [30793, 0.9362031648036052], [30807, 0.9361539914193117], [30821, 0.9362727621174376], [30835, 0.9363580854644815], [30849, 0.9362116537908673], [30863, 0.9362032848388367], [30877, 0.9362689753654803], [30891, 0.936310189722142], [30905, 0.9360874888072153], [30919, 0.9362638147603118], [30933, 0.9362149106251652], [30947, 0.9361966527870764], [30961, 0.9362901829770514], [30975, 0.9362464560988539], [30989, 0.9362655136410024], [31003, 0.9362762082165752], [31017, 0.9361179520787757], [31031, 0.9362991351086682], [31045, 0.9362404355241372], [32095, 0.9363120398236029], [32109, 0.9361993776417009], [32123, 0.9362148415413698], [32137, 0.9361386785039416], [32151, 0.936325725652023], [32165, 0.9361967238711474], [32179, 0.9360948420598513], [32193, 0.9362342874430479], [32207, 0.9362486213579808], [32221, 0.9362061740963391], [32235, 0.9362000725597895], [32249, 0.9362156293376489], [32263, 0.9362715336692963], [32277, 0.9361932367970122], [32305, 0.9363026425322611], [32319, 0.9362620497132538], [32333, 0.9362565955205041], [32347, 0.9361684273235974], [32361, 0.9362830685641957], [32375, 0.9362444932931241], [32389, 0.9362497093816583], [32403, 0.936114328798118], [32417, 0.9362881611725187], [32431, 0.9362254030118811], [32445, 0.9362951810223614], [32585, 0.9362134360295752], [32599, 0.9361763199530427], [32613, 0.9362266799516209], [32627, 0.9362532149044864], [32641, 0.9362910742655116], [32655, 0.9362618977862681], [32851, 0.9362928723408542], [32865, 0.93625551992988], [32879, 0.9361538424097486], [32893, 0.9361791905353661], [32907, 0.9362186612085589], [32921, 0.9362194211747343], [32991, 0.9362684720019843], [33005, 0.9363404798088302], [33019, 0.936134280914118], [33033, 0.9363326763450639], [33047, 0.9362960247932397], [33061, 0.9363295817493948], [33075, 0.9364107810297394], [33089, 0.9362647271455753], [33103, 0.9362338466329634], [33117, 0.9363092587627675], [33131, 0.9361769531351032], [33145, 0.9364136658163891], [33159, 0.9362056665206028], [33187, 0.936120798394372], [33201, 0.9362773922926566], [33215, 0.9362307396578713], [33229, 0.9361790351071961], [33243, 0.9362218679275265], [33271, 0.936077560169559], [33299, 0.9361593789963614], [33313, 0.9361890950523554], [33327, 0.936270561706585], [33341, 0.9362791765187735], [33355, 0.936253673929583], [33369, 0.9362778932835149], [33383, 0.936231151476299], [33397, 0.9362770484696871], [33411, 0.9363512503632481], [33425, 0.9362939535402917], [33439, 0.9362134169756106], [33453, 0.9361974670001236], [33467, 0.9361654365650718], [33523, 0.9361858585795745], [33537, 0.9362152020656976], [33551, 0.9361893838763379], [33649, 0.9361740259857765], [33705, 0.9363052477082624], [33719, 0.9362341378256727], [33733, 0.936181307249245], [33747, 0.9362586176213405], [33761, 0.9362715134001303], [33775, 0.936192843182105], [33803, 0.9362000008599187], [33817, 0.9362074629934238], [33831, 0.9361765896853055], [33845, 0.9360513421725011], [34041, 0.9362158217587373], [34055, 0.9361803037938107], [34069, 0.9362557010157997], [34083, 0.9362469780441965], [34125, 0.9361263858350828], [34139, 0.9362604376518138], [34153, 0.9362554376332769], [34167, 0.9362457099583468]] \ No newline at end of file +[[28511, 0.9361485652072762], [29225, 0.9363882559099636], [29239, 0.9362342941502024], [29253, 0.9362866031917982], [29267, 0.9361997614455078], [29281, 0.9361512110354739], [29295, 0.936273121910383], [29309, 0.9362775092972113], [29323, 0.9362938520384694], [29337, 0.9362254623741953], [29351, 0.9361809229231618], [29365, 0.9361597887085454], [29379, 0.9362817796217078], [29393, 0.9361850992857481], [29407, 0.9361305694929953], [29421, 0.9362639608414732], [29435, 0.9361904913806499], [29449, 0.9362314608771216], [29463, 0.9362441743178257], [29477, 0.9361551464681007], [29547, 0.9362416580010883], [29561, 0.9362410448410303], [29575, 0.9361966839961404], [29603, 0.9362062943609151], [29617, 0.9362074924648798], [29631, 0.9363378904700217], [29645, 0.9362203855232705], [29659, 0.9362472147801011], [29673, 0.936264317990268], [29743, 0.9362673648058368], [29757, 0.93618695593679], [29771, 0.9362593248458225], [29785, 0.9362955387633854], [29799, 0.9362648262375733], [29813, 0.9362149292300477], [29827, 0.9362504640709873], [29841, 0.9362806227017086], [29855, 0.9362455840748458], [29869, 0.9363281388205185], [30009, 0.9362238025368718], [30023, 0.9363132244636839], [30037, 0.9362594795226892], [30051, 0.9361678056162127], [30065, 0.9362773901315062], [30079, 0.9362380661461106], [30093, 0.936251532938167], [30107, 0.9362459622757128], [30121, 0.9362241971156003], [30135, 0.9362947905817476], [30149, 0.9361896129556151], [30163, 0.9361815219023676], [30177, 0.9362591132461675], [30191, 0.9362100837484789], [30205, 0.9363309025625465], [30219, 0.936243973999432], [30233, 0.936256364915869], [30247, 0.9362224498954044], [30261, 0.9362535899397835], [30513, 0.9362610251446741], [30527, 0.9361909168095071], [30541, 0.936224947916028], [30555, 0.9362503647916971], [30569, 0.9361973209409917], [30583, 0.9362317215863537], [30597, 0.9363499943770738], [30625, 0.9362514011281794], [30639, 0.9362799796458092], [30653, 0.9362162617915617], [30667, 0.9362648499558517], [30681, 0.9362268509760284], [30695, 0.936082170621395], [30709, 0.9362247520687941], [30723, 0.9362656992826082], [30737, 0.9363260069883228], [30751, 0.9362540641520615], [30765, 0.9362336636157602], [30779, 0.9362865946273528], [30793, 0.9362031648036052], [30807, 0.9361539914193117], [30821, 0.9362727621174376], [30835, 0.9363580854644815], [30849, 0.9362116537908673], [30863, 0.9362032848388367], [30877, 0.9362689753654803], [30891, 0.936310189722142], [30905, 0.9360874888072153], [30919, 0.9362638147603118], [30933, 0.9362149106251652], [30947, 0.9361966527870764], [30961, 0.9362901829770514], [30975, 0.9362464560988539], [30989, 0.9362655136410024], [31003, 0.9362762082165752], [31017, 0.9361179520787757], [31031, 0.9362991351086682], [31045, 0.9362404355241372], [32095, 0.9363120398236029], [32109, 0.9361993776417009], [32123, 0.9362148415413698], [32137, 0.9361386785039416], [32151, 0.936325725652023], [32165, 0.9361967238711474], [32179, 0.9360948420598513], [32193, 0.9362342874430479], [32207, 0.9362486213579808], [32221, 0.9362061740963391], [32235, 0.9362000725597895], [32249, 0.9362156293376489], [32263, 0.9362715336692963], [32277, 0.9361932367970122], [32305, 0.9363026425322611], [32319, 0.9362620497132538], [32333, 0.9362565955205041], [32347, 0.9361684273235974], [32361, 0.9362830685641957], [32375, 0.9362444932931241], [32389, 0.9362497093816583], [32403, 0.936114328798118], [32417, 0.9362881611725187], [32431, 0.9362254030118811], [32445, 0.9362951810223614], [32585, 0.9362134360295752], [32599, 0.9361763199530427], [32613, 0.9362266799516209], [32627, 0.9362532149044864], [32641, 0.9362910742655116], [32655, 0.9362618977862681], [32851, 0.9362928723408542], [32865, 0.93625551992988], [32879, 0.9361538424097486], [32893, 0.9361791905353661], [32907, 0.9362186612085589], [32921, 0.9362194211747343], [32991, 0.9362684720019843], [33005, 0.9363404798088302], [33019, 0.936134280914118], [33033, 0.9363326763450639], [33047, 0.9362960247932397], [33061, 0.9363295817493948], [33075, 0.9364107810297394], [33089, 0.9362647271455753], [33103, 0.9362338466329634], [33117, 0.9363092587627675], [33131, 0.9361769531351032], [33145, 0.9364136658163891], [33159, 0.9362056665206028], [33187, 0.936120798394372], [33201, 0.9362773922926566], [33215, 0.9362307396578713], [33229, 0.9361790351071961], [33243, 0.9362218679275265], [33271, 0.936077560169559], [33299, 0.9361593789963614], [33313, 0.9361890950523554], [33327, 0.936270561706585], [33341, 0.9362791765187735], [33355, 0.936253673929583], [33369, 0.9362778932835149], [33383, 0.936231151476299], [33397, 0.9362770484696871], [33411, 0.9363512503632481], [33425, 0.9362939535402917], [33439, 0.9362134169756106], [33453, 0.9361974670001236], [33467, 0.9361654365650718], [33523, 0.9361858585795745], [33537, 0.9362152020656976], [33551, 0.9361893838763379], [33649, 0.9361740259857765], [33705, 0.9363052477082624], [33719, 0.9362341378256727], [33733, 0.936181307249245], [33747, 0.9362586176213405], [33761, 0.9362715134001303], [33775, 0.936192843182105], [33803, 0.9362000008599187], [33817, 0.9362074629934238], [33831, 0.9361765896853055], [33845, 0.9360513421725011], [34041, 0.9362158217587373], [34055, 0.9361803037938107], [34069, 0.9362557010157997], [34083, 0.9362469780441965], [34125, 0.9361263858350828], [34139, 0.9362604376518138], [34153, 0.9362554376332769], [34167, 0.9362174836631965]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LinearRegressionBenchmark.peakmem_fit.json b/graphs/summary/linear_model.LinearRegressionBenchmark.peakmem_fit.json index 93d6614d72..bb2c170694 100644 --- a/graphs/summary/linear_model.LinearRegressionBenchmark.peakmem_fit.json +++ b/graphs/summary/linear_model.LinearRegressionBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28497, 600821042.2885579], [29215, 598342700.2313994], [29225, 598639845.2622494], [29227, 598041619.5805314], [29228, 597911321.5561999], [29229, 598208184.0888131], [29235, 598463351.8739007], [29240, 598772346.1309161], [29245, 598635535.994827], [29246, 598772805.5221041], [29258, 598908360.2189103], [29262, 598903383.0036159], [29279, 598876730.0947974], [29286, 598820770.9937717], [29293, 598911983.1704209], [29294, 599053416.0772133], [29295, 598477577.5386652], [29296, 599004982.0274205], [29313, 598658101.449243], [29318, 599051266.2186248], [29319, 598917671.8476461], [29322, 598395964.2435888], [29325, 599060796.1863034], [29327, 599033061.62989], [29328, 598830394.3249031], [29340, 598890498.9799712], [29344, 597596186.7234182], [29349, 598014865.8698287], [29364, 598210331.3260796], [29371, 598320421.7376674], [29376, 598133597.0398483], [29381, 598199226.9423681], [29383, 598408777.0625923], [29387, 598271190.9895018], [29401, 597862657.1566253], [29404, 598291843.0259877], [29409, 598217657.7245238], [29414, 597279175.7647966], [29415, 598219050.1739008], [29420, 598170897.9394084], [29421, 598578270.9664983], [29425, 598677478.2005926], [29429, 598946373.6391686], [29435, 598357720.7763325], [29443, 598247321.6641418], [29446, 598367076.9892141], [29453, 597999298.256635], [29454, 598072422.1790806], [29455, 598264801.1867384], [29457, 598158161.1962103], [29458, 598604955.9284269], [29469, 598180008.3387327], [29541, 598561243.7965167], [29548, 598403677.3354458], [29550, 598413726.1921809], [29551, 598627010.9462738], [29572, 597949505.8791095], [29591, 599278808.1257912], [29598, 599286612.5418583], [29609, 599160717.3316178], [29611, 599318978.5323967], [29621, 599603385.9830639], [29638, 599280647.7469051], [29644, 599631783.6941624], [29648, 599765170.271795], [29652, 599350741.5844244], [29656, 599461190.6443505], [29657, 599199638.4563613], [29662, 598833097.6444628], [29665, 599360331.2836449], [29667, 599380916.5986221], [29735, 599221402.7600747], [29742, 599372514.7608461], [29750, 598147881.7218142], [29753, 599542420.9780024], [29757, 599382009.6985584], [29761, 599267556.3055773], [29765, 599599957.309992], [29766, 598433149.4887516], [29768, 599171906.7146125], [29776, 599319840.6428578], [29783, 599517773.26679], [29788, 599455971.1982843], [29789, 599608324.5669082], [29790, 599301368.8153878], [29795, 599550303.4350991], [29798, 599495738.2860258], [29805, 599751462.7560778], [29806, 599303230.1330016], [29807, 599541881.1366221], [29808, 599486125.2855922], [29813, 599713994.7759476], [29815, 599550496.139996], [29828, 598568891.5254487], [29839, 599369211.218491], [29844, 599275254.8479292], [29858, 599306896.8461424], [29865, 599683307.7744726], [29999, 599418521.2036715], [30002, 599574129.2267522], [30010, 599613311.9212924], [30013, 599369927.9392549], [30023, 599591827.9852414], [30028, 599560127.0944991], [30035, 599415960.1908079], [30046, 599364676.1658345], [30053, 599539203.623647], [30066, 599382248.0126657], [30068, 599291534.9094459], [30070, 599632470.0514591], [30074, 599804419.8965114], [30076, 599245700.6713669], [30077, 599593561.381534], [30078, 599601406.5536973], [30085, 599506315.442047], [30086, 599366098.1967783], [30096, 599381774.9112055], [30104, 599484953.3708856], [30106, 599362882.3592036], [30112, 600014037.2745328], [30116, 599558634.0841507], [30118, 599301151.647059], [30123, 599557958.2337587], [30128, 599405580.9233954], [30135, 598234999.2934761], [30145, 599736064.8741432], [30155, 600005727.3487345], [30156, 599989881.5877267], [30157, 600076504.5523045], [30165, 599992121.0301242], [30174, 600089670.9421705], [30179, 599721617.5240332], [30185, 600360591.4549006], [30189, 600311868.7823223], [30190, 599941303.1692216], [30198, 600303191.8313168], [30202, 600176536.7072167], [30203, 600091385.1192766], [30208, 600345512.0183467], [30212, 600260670.0766952], [30213, 599848036.3872641], [30215, 600052061.2155137], [30218, 600130290.7274187], [30225, 600012205.9276657], [30227, 600029739.2671272], [30233, 600262498.6671101], [30235, 599939393.0610497], [30238, 599839143.0811714], [30244, 600191236.2855077], [30248, 599896607.5219136], [30254, 599780323.3345448], [30259, 599821098.1727041], [30260, 599908058.9410872], [30501, 600005798.4275237], [30502, 598901055.1279994], [30506, 599966434.9942744], [30507, 600069000.0348682], [30510, 600202010.0609555], [30515, 599584814.3651636], [30519, 599986498.6751544], [30520, 599939215.3723574], [30524, 600221759.9779409], [30525, 600093935.4494538], [30529, 599922653.8225034], [30533, 599618476.8361167], [30538, 599858926.2713476], [30542, 599776169.256528], [30543, 599606765.2931591], [30544, 600116154.8414552], [30545, 599632647.6072159], [30550, 599464458.6260982], [30552, 599588080.288044], [30556, 599538310.8368291], [30561, 599636313.0474465], [30564, 599613597.7515196], [30565, 599664383.4132885], [30577, 599587487.0995231], [30581, 600111328.4340537], [30586, 599883595.050609], [30593, 599757244.8742485], [30615, 599840725.8465421], [30621, 599795583.9147606], [30622, 599898512.2009324], [30629, 599766156.5001706], [30635, 600065871.8271419], [30639, 599397130.2806404], [30640, 600050653.7695057], [30643, 599751817.5732944], [30646, 599900222.9250274], [30647, 599909981.7617933], [30650, 600023046.5848043], [30657, 599941929.4397489], [30665, 599601192.6138783], [30670, 600068048.987186], [30675, 600018853.9651101], [30679, 599841642.4047625], [30694, 599785881.2865738], [30704, 599925224.9492087], [30708, 599818395.5579149], [30718, 599985857.9804593], [30723, 600058687.6042798], [30729, 599777409.484272], [30730, 599891415.9579046], [30734, 599932225.906463], [30739, 599991828.4036012], [30744, 600089666.8603249], [30748, 599859394.8571346], [30750, 599986190.5266074], [30754, 600224060.9571222], [30761, 600535529.5697898], [30762, 600427811.0231901], [30777, 599938721.3868895], [30782, 599835271.7787329], [30785, 599990101.4428288], [30787, 599910283.293528], [30794, 599919305.7677307], [30804, 599781183.6769775], [30812, 599815661.3381336], [30817, 600065758.3417242], [30821, 600348247.4719093], [30838, 600000216.046594], [30849, 599883480.5378636], [30861, 599935240.1823429], [30868, 600049259.1676933], [30872, 600329606.267574], [30890, 600043754.4445428], [30904, 605473088.9253616], [30907, 605149160.9578077], [30908, 605576665.6220866], [30917, 605019171.9372882], [30928, 605597072.2123253], [30931, 605289711.7015275], [30938, 605228556.4635968], [30945, 605848036.5015099], [30949, 605268992.0615007], [30955, 605576357.3260149], [30957, 605566850.2575092], [30967, 605290559.016021], [30974, 605419671.1916596], [30978, 605196313.2408271], [30987, 605612841.8905879], [30988, 604686046.3075745], [30994, 605583391.5793495], [30997, 605469454.1512407], [31009, 605581227.4187175], [31019, 605391140.2858148], [31031, 605281360.9774077], [31039, 605759766.4814341], [31040, 605586406.2343377], [31041, 605562212.2048637], [32090, 623578301.9399707], [32101, 622805789.2475891], [32104, 623342973.5113045], [32112, 623503587.9206402], [32115, 623350197.577584], [32116, 623399256.2913693], [32120, 623011514.4224129], [32130, 623369646.5520535], [32131, 623495408.9472634], [32132, 623393115.3056252], [32138, 622939876.874052], [32148, 623441277.6126119], [32152, 622767956.0031596], [32156, 623503639.4224932], [32157, 623642658.3235518], [32163, 623002330.0624256], [32174, 622808856.8586577], [32181, 623548624.2224131], [32186, 623271429.4574128], [32187, 623232550.802816], [32193, 622922512.8941369], [32197, 623408532.884702], [32198, 626915193.4664079], [32204, 626942777.3971647], [32213, 627066488.0214331], [32218, 627920637.2161944], [32220, 627966509.7254881], [32224, 627733053.7016594], [32241, 627823643.7842139], [32249, 627587029.932455], [32252, 627938986.4617367], [32256, 627797054.3661823], [32259, 627843117.6144344], [32261, 626794912.7438918], [32265, 626921406.5686866], [32270, 626370052.1564616], [32274, 626610029.2084205], [32292, 626519178.0889794], [32294, 626763894.5119857], [33213, 540469009.749149], [33259, 540337591.9862518], [33296, 540695637.1269518], [33302, 540705556.6333258], [33309, 540689439.5248023], [33310, 540605038.4483569], [33311, 541066391.9522104], [33315, 540708133.1460643], [33323, 541470593.5366243], [33332, 540382366.5635098], [33333, 541658033.3797505], [33337, 541449927.6020583], [33338, 541113237.3418411], [33341, 541751382.3517379], [33346, 541533007.1906844], [33351, 541420830.9810314], [33358, 542542881.3884673], [33359, 542356194.5484092], [33361, 541726069.349355], [33370, 542424450.6093454], [33373, 542151053.0637631], [33380, 542837075.782748], [33386, 542767344.1399498], [33393, 542888437.735895], [33400, 542603028.4331439], [33414, 542736427.4935683], [33424, 543081665.5104462], [33428, 544258066.3375261], [33437, 543986746.7130158], [33444, 531721353.1031698], [33453, 531630300.76044494], [33516, 531869656.61750627], [33517, 531826536.68374044], [33518, 531935278.97876847], [33520, 532021028.3754166], [33524, 532075462.58777034], [33533, 531942112.6185778], [33536, 531937274.3819663], [33537, 531243093.42675376], [33543, 531433014.55033904], [33546, 531020625.7249755], [33648, 536373627.8793466], [33704, 535573937.0688451], [33707, 536093976.7647819], [33708, 536138366.84081024], [33712, 535898292.7297923], [33715, 535678550.16378415], [33722, 535702814.9124124], [33733, 535823981.7117584], [33734, 535639861.89207137], [33756, 535883449.8533453], [33766, 535491409.1043408], [33802, 535774945.16061723], [33808, 535507923.94185966], [33813, 535351572.06257564], [33818, 535741024.6876263], [33820, 535438024.54284674], [33826, 535347016.7298233], [33833, 535545637.17471445], [34031, 535352474.60036594], [34034, 535227441.1573187], [34046, 535826302.231896], [34049, 535638563.83592206], [34052, 535375978.28032637], [34058, 535843718.93145967], [34065, 535610313.27678347], [34068, 535080577.3334108], [34075, 535238630.76311505], [34079, 535334423.55545175], [34113, 535754185.2706837], [34115, 535707612.8613622], [34120, 535553657.5068805], [34126, 535651861.7581459], [34139, 535350400.1667167], [34140, 535136366.227232], [34141, 536012041.783657], [34155, 535562444.3535603], [34158, 535218668.1985821], [34160, 535682443.56232345], [34162, 535848749.56423086]] \ No newline at end of file +[[28497, 600821042.2885579], [29215, 598342700.2313994], [29225, 598639845.2622494], [29227, 598041619.5805314], [29228, 597911321.5561999], [29229, 598208184.0888131], [29235, 598463351.8739007], [29240, 598772346.1309161], [29245, 598635535.994827], [29246, 598772805.5221041], [29258, 598908360.2189103], [29262, 598903383.0036159], [29279, 598876730.0947974], [29286, 598820770.9937717], [29293, 598911983.1704209], [29294, 599053416.0772133], [29295, 598477577.5386652], [29296, 599004982.0274205], [29313, 598658101.449243], [29318, 599051266.2186248], [29319, 598917671.8476461], [29322, 598395964.2435888], [29325, 599060796.1863034], [29327, 599033061.62989], [29328, 598830394.3249031], [29340, 598890498.9799712], [29344, 597596186.7234182], [29349, 598014865.8698287], [29364, 598210331.3260796], [29371, 598320421.7376674], [29376, 598133597.0398483], [29381, 598199226.9423681], [29383, 598408777.0625923], [29387, 598271190.9895018], [29401, 597862657.1566253], [29404, 598291843.0259877], [29409, 598217657.7245238], [29414, 597279175.7647966], [29415, 598219050.1739008], [29420, 598170897.9394084], [29421, 598578270.9664983], [29425, 598677478.2005926], [29429, 598946373.6391686], [29435, 598357720.7763325], [29443, 598247321.6641418], [29446, 598367076.9892141], [29453, 597999298.256635], [29454, 598072422.1790806], [29455, 598264801.1867384], [29457, 598158161.1962103], [29458, 598604955.9284269], [29469, 598180008.3387327], [29541, 598561243.7965167], [29548, 598403677.3354458], [29550, 598413726.1921809], [29551, 598627010.9462738], [29572, 597949505.8791095], [29591, 599278808.1257912], [29598, 599286612.5418583], [29609, 599160717.3316178], [29611, 599318978.5323967], [29621, 599603385.9830639], [29638, 599280647.7469051], [29644, 599631783.6941624], [29648, 599765170.271795], [29652, 599350741.5844244], [29656, 599461190.6443505], [29657, 599199638.4563613], [29662, 598833097.6444628], [29665, 599360331.2836449], [29667, 599380916.5986221], [29735, 599221402.7600747], [29742, 599372514.7608461], [29750, 598147881.7218142], [29753, 599542420.9780024], [29757, 599382009.6985584], [29761, 599267556.3055773], [29765, 599599957.309992], [29766, 598433149.4887516], [29768, 599171906.7146125], [29776, 599319840.6428578], [29783, 599517773.26679], [29788, 599455971.1982843], [29789, 599608324.5669082], [29790, 599301368.8153878], [29795, 599550303.4350991], [29798, 599495738.2860258], [29805, 599751462.7560778], [29806, 599303230.1330016], [29807, 599541881.1366221], [29808, 599486125.2855922], [29813, 599713994.7759476], [29815, 599550496.139996], [29828, 598568891.5254487], [29839, 599369211.218491], [29844, 599275254.8479292], [29858, 599306896.8461424], [29865, 599683307.7744726], [29999, 599418521.2036715], [30002, 599574129.2267522], [30010, 599613311.9212924], [30013, 599369927.9392549], [30023, 599591827.9852414], [30028, 599560127.0944991], [30035, 599415960.1908079], [30046, 599364676.1658345], [30053, 599539203.623647], [30066, 599382248.0126657], [30068, 599291534.9094459], [30070, 599632470.0514591], [30074, 599804419.8965114], [30076, 599245700.6713669], [30077, 599593561.381534], [30078, 599601406.5536973], [30085, 599506315.442047], [30086, 599366098.1967783], [30096, 599381774.9112055], [30104, 599484953.3708856], [30106, 599362882.3592036], [30112, 600014037.2745328], [30116, 599558634.0841507], [30118, 599301151.647059], [30123, 599557958.2337587], [30128, 599405580.9233954], [30135, 598234999.2934761], [30145, 599736064.8741432], [30155, 600005727.3487345], [30156, 599989881.5877267], [30157, 600076504.5523045], [30165, 599992121.0301242], [30174, 600089670.9421705], [30179, 599721617.5240332], [30185, 600360591.4549006], [30189, 600311868.7823223], [30190, 599941303.1692216], [30198, 600303191.8313168], [30202, 600176536.7072167], [30203, 600091385.1192766], [30208, 600345512.0183467], [30212, 600260670.0766952], [30213, 599848036.3872641], [30215, 600052061.2155137], [30218, 600130290.7274187], [30225, 600012205.9276657], [30227, 600029739.2671272], [30233, 600262498.6671101], [30235, 599939393.0610497], [30238, 599839143.0811714], [30244, 600191236.2855077], [30248, 599896607.5219136], [30254, 599780323.3345448], [30259, 599821098.1727041], [30260, 599908058.9410872], [30501, 600005798.4275237], [30502, 598901055.1279994], [30506, 599966434.9942744], [30507, 600069000.0348682], [30510, 600202010.0609555], [30515, 599584814.3651636], [30519, 599986498.6751544], [30520, 599939215.3723574], [30524, 600221759.9779409], [30525, 600093935.4494538], [30529, 599922653.8225034], [30533, 599618476.8361167], [30538, 599858926.2713476], [30542, 599776169.256528], [30543, 599606765.2931591], [30544, 600116154.8414552], [30545, 599632647.6072159], [30550, 599464458.6260982], [30552, 599588080.288044], [30556, 599538310.8368291], [30561, 599636313.0474465], [30564, 599613597.7515196], [30565, 599664383.4132885], [30577, 599587487.0995231], [30581, 600111328.4340537], [30586, 599883595.050609], [30593, 599757244.8742485], [30615, 599840725.8465421], [30621, 599795583.9147606], [30622, 599898512.2009324], [30629, 599766156.5001706], [30635, 600065871.8271419], [30639, 599397130.2806404], [30640, 600050653.7695057], [30643, 599751817.5732944], [30646, 599900222.9250274], [30647, 599909981.7617933], [30650, 600023046.5848043], [30657, 599941929.4397489], [30665, 599601192.6138783], [30670, 600068048.987186], [30675, 600018853.9651101], [30679, 599841642.4047625], [30694, 599785881.2865738], [30704, 599925224.9492087], [30708, 599818395.5579149], [30718, 599985857.9804593], [30723, 600058687.6042798], [30729, 599777409.484272], [30730, 599891415.9579046], [30734, 599932225.906463], [30739, 599991828.4036012], [30744, 600089666.8603249], [30748, 599859394.8571346], [30750, 599986190.5266074], [30754, 600224060.9571222], [30761, 600535529.5697898], [30762, 600427811.0231901], [30777, 599938721.3868895], [30782, 599835271.7787329], [30785, 599990101.4428288], [30787, 599910283.293528], [30794, 599919305.7677307], [30804, 599781183.6769775], [30812, 599815661.3381336], [30817, 600065758.3417242], [30821, 600348247.4719093], [30838, 600000216.046594], [30849, 599883480.5378636], [30861, 599935240.1823429], [30868, 600049259.1676933], [30872, 600329606.267574], [30890, 600043754.4445428], [30904, 605473088.9253616], [30907, 605149160.9578077], [30908, 605576665.6220866], [30917, 605019171.9372882], [30928, 605597072.2123253], [30931, 605289711.7015275], [30938, 605228556.4635968], [30945, 605848036.5015099], [30949, 605268992.0615007], [30955, 605576357.3260149], [30957, 605566850.2575092], [30967, 605290559.016021], [30974, 605419671.1916596], [30978, 605196313.2408271], [30987, 605612841.8905879], [30988, 604686046.3075745], [30994, 605583391.5793495], [30997, 605469454.1512407], [31009, 605581227.4187175], [31019, 605391140.2858148], [31031, 605281360.9774077], [31039, 605759766.4814341], [31040, 605586406.2343377], [31041, 605562212.2048637], [32090, 623578301.9399707], [32101, 622805789.2475891], [32104, 623342973.5113045], [32112, 623503587.9206402], [32115, 623350197.577584], [32116, 623399256.2913693], [32120, 623011514.4224129], [32130, 623369646.5520535], [32131, 623495408.9472634], [32132, 623393115.3056252], [32138, 622939876.874052], [32148, 623441277.6126119], [32152, 622767956.0031596], [32156, 623503639.4224932], [32157, 623642658.3235518], [32163, 623002330.0624256], [32174, 622808856.8586577], [32181, 623548624.2224131], [32186, 623271429.4574128], [32187, 623232550.802816], [32193, 622922512.8941369], [32197, 623408532.884702], [32198, 626915193.4664079], [32204, 626942777.3971647], [32213, 627066488.0214331], [32218, 627920637.2161944], [32220, 627966509.7254881], [32224, 627733053.7016594], [32241, 627823643.7842139], [32249, 627587029.932455], [32252, 627938986.4617367], [32256, 627797054.3661823], [32259, 627843117.6144344], [32261, 626794912.7438918], [32265, 626921406.5686866], [32270, 626370052.1564616], [32274, 626610029.2084205], [32292, 626519178.0889794], [32294, 626763894.5119857], [33213, 540469009.749149], [33259, 540337591.9862518], [33296, 540695637.1269518], [33302, 540705556.6333258], [33309, 540689439.5248023], [33310, 540605038.4483569], [33311, 541066391.9522104], [33315, 540708133.1460643], [33323, 541470593.5366243], [33332, 540382366.5635098], [33333, 541658033.3797505], [33337, 541449927.6020583], [33338, 541113237.3418411], [33341, 541751382.3517379], [33346, 541533007.1906844], [33351, 541420830.9810314], [33358, 542542881.3884673], [33359, 542356194.5484092], [33361, 541726069.349355], [33370, 542424450.6093454], [33373, 542151053.0637631], [33380, 542837075.782748], [33386, 542767344.1399498], [33393, 542888437.735895], [33400, 542603028.4331439], [33414, 542736427.4935683], [33424, 543081665.5104462], [33428, 544258066.3375261], [33437, 543986746.7130158], [33444, 531721353.1031698], [33453, 531630300.76044494], [33516, 531869656.61750627], [33517, 531826536.68374044], [33518, 531935278.97876847], [33520, 532021028.3754166], [33524, 532075462.58777034], [33533, 531942112.6185778], [33536, 531937274.3819663], [33537, 531243093.42675376], [33543, 531433014.55033904], [33546, 531020625.7249755], [33648, 536373627.8793466], [33704, 535573937.0688451], [33707, 536093976.7647819], [33708, 536138366.84081024], [33712, 535898292.7297923], [33715, 535678550.16378415], [33722, 535702814.9124124], [33733, 535823981.7117584], [33734, 535639861.89207137], [33756, 535883449.8533453], [33766, 535491409.1043408], [33802, 535774945.16061723], [33808, 535507923.94185966], [33813, 535351572.06257564], [33818, 535741024.6876263], [33820, 535438024.54284674], [33826, 535347016.7298233], [33833, 535545637.17471445], [34031, 535352474.60036594], [34034, 535227441.1573187], [34046, 535826302.231896], [34049, 535638563.83592206], [34052, 535375978.28032637], [34058, 535843718.93145967], [34065, 535610313.27678347], [34068, 535080577.3334108], [34075, 535238630.76311505], [34079, 535334423.55545175], [34113, 535754185.2706837], [34115, 535707612.8613622], [34120, 535553657.5068805], [34126, 535651861.7581459], [34139, 535350400.1667167], [34140, 535136366.227232], [34141, 536012041.783657], [34155, 535562444.3535603], [34158, 535218668.1985821], [34160, 535682443.56232345], [34162, 535848749.56423086], [34164, 535194090.6381144]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LinearRegressionBenchmark.peakmem_predict.json b/graphs/summary/linear_model.LinearRegressionBenchmark.peakmem_predict.json index 1fce329894..390546457e 100644 --- a/graphs/summary/linear_model.LinearRegressionBenchmark.peakmem_predict.json +++ b/graphs/summary/linear_model.LinearRegressionBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28497, 328787304.15116644], [29215, 327098178.94116604], [29225, 327329922.6163702], [29227, 327046996.5007472], [29228, 326847206.3868055], [29229, 326893020.89449], [29235, 327222016.35800034], [29240, 326450910.0935225], [29245, 326604705.01311046], [29246, 326682602.24418], [29258, 326617676.911352], [29262, 326734442.6433487], [29279, 326375540.6821199], [29286, 326657492.0191631], [29293, 326849085.8460318], [29294, 326448612.4689423], [29295, 326545302.0844503], [29296, 326457368.35326725], [29313, 326232647.1265717], [29318, 326695839.7862439], [29319, 326193316.9210879], [29322, 326236886.3420396], [29325, 326453608.45967263], [29327, 326395262.58020836], [29328, 326370010.62729466], [29340, 326333425.41044575], [29344, 325399045.00725514], [29349, 325404565.8871618], [29364, 325703633.47941947], [29371, 325887238.4262586], [29376, 325945165.9759367], [29381, 325948985.9601877], [29383, 326165279.7040554], [29387, 325719900.8416686], [29401, 325774610.9669895], [29404, 326362413.3703352], [29409, 325903302.0586441], [29414, 324885880.0951708], [29415, 325964730.16726184], [29420, 326085671.16495967], [29421, 326033261.0857228], [29425, 326167588.3775029], [29429, 326429993.2091037], [29435, 327159500.59344786], [29443, 326883573.5825806], [29446, 327198294.4851488], [29453, 326701370.6422426], [29454, 326840219.21051145], [29455, 326956788.60034037], [29457, 327034624.5914649], [29458, 327175718.46519804], [29469, 327082969.2461932], [29541, 327458779.7771476], [29548, 327134869.6950677], [29550, 327304965.2362931], [29551, 327588327.27268314], [29572, 326699320.0187576], [29591, 327967417.0149706], [29598, 327928955.5397637], [29609, 327912881.49540246], [29611, 328001644.25215966], [29621, 328292640.4783791], [29638, 327971913.5456901], [29644, 328199812.2122929], [29648, 328293945.376903], [29652, 327981958.79171646], [29656, 328290008.4607086], [29657, 327753300.5247031], [29662, 327832371.7926204], [29665, 328150374.4089112], [29667, 328198878.1151581], [29735, 327899098.4890833], [29742, 328015762.9022071], [29750, 327249491.73842686], [29753, 328155039.5765997], [29757, 328032437.0277452], [29761, 327885698.8162072], [29765, 328109316.9685904], [29766, 327449889.2512521], [29768, 327947546.02105516], [29776, 327912748.23967993], [29783, 328249695.849273], [29788, 327913603.10656035], [29789, 328348724.4353948], [29790, 328020468.77925885], [29795, 328169754.1959483], [29798, 328305335.9589891], [29805, 328405232.2874759], [29806, 328162655.6086873], [29807, 328199282.51774096], [29808, 328106736.07104456], [29813, 328304365.1382399], [29815, 328299216.7891178], [29828, 327553872.94226545], [29839, 328259300.3352093], [29844, 328229725.0717734], [29858, 328405955.0646043], [29865, 328262432.6514655], [29999, 328270850.2471481], [30002, 328247200.8495155], [30010, 328290196.65431374], [30013, 328204531.11812085], [30023, 328233629.844952], [30028, 328166266.78171885], [30035, 328167927.18712276], [30046, 328182231.7445017], [30053, 328150551.40918505], [30066, 328129688.18638396], [30068, 328170068.96374166], [30070, 328517783.8741365], [30074, 328478031.27165157], [30076, 328073637.9957334], [30077, 328468882.73626834], [30078, 328310433.5448388], [30085, 328212355.40244734], [30086, 328152445.5413199], [30096, 328018683.9792558], [30104, 328205429.6210177], [30106, 328252696.4427815], [30112, 328507664.8724834], [30116, 328205930.47512335], [30118, 328157513.54872894], [30123, 328135352.1469566], [30128, 328297431.3070782], [30135, 327494031.45254517], [30145, 328365900.0694801], [30155, 328525310.91120875], [30156, 328688513.7693295], [30157, 328523109.9128973], [30165, 328884832.42587006], [30174, 328877440.41147137], [30179, 328426959.81185037], [30185, 329010567.05074507], [30189, 328899001.1559543], [30190, 328694270.51619285], [30198, 328745646.7656918], [30202, 328667858.3287884], [30203, 328639096.8746306], [30208, 328648997.5257331], [30212, 328743485.05903864], [30213, 328554364.7087572], [30215, 328841820.7746717], [30218, 328677474.22900075], [30225, 328423140.93647814], [30227, 328727236.20779604], [30233, 328829963.8480206], [30235, 328867778.5268345], [30238, 328692993.05982363], [30244, 328983772.7903938], [30248, 328727785.41531724], [30254, 328518969.8829056], [30259, 328725302.28672934], [30260, 328741861.65178365], [30501, 328841004.0597946], [30502, 328021688.7318227], [30506, 328849515.9985624], [30507, 328744847.8269432], [30510, 328882961.36096585], [30515, 328603479.07451516], [30519, 328720869.778892], [30520, 328692391.73102546], [30524, 328825256.8003783], [30525, 328921619.3630317], [30529, 328945373.461277], [30533, 328671935.91789234], [30538, 328754022.82369524], [30542, 328527265.5941141], [30543, 328786823.31805646], [30544, 328635687.64826715], [30545, 328450215.2357533], [30550, 328588060.3541268], [30552, 328424241.44041246], [30556, 328397424.5531947], [30561, 328508944.04540974], [30564, 328672270.4187379], [30565, 328696233.30527765], [30577, 328556941.6049655], [30581, 328898143.4942162], [30586, 328453219.2585967], [30593, 328537218.4858719], [30615, 328691609.430268], [30621, 328991211.09126693], [30622, 328702904.1841921], [30629, 328621681.1464611], [30635, 328823819.6951763], [30639, 328673746.0876404], [30640, 328628056.49108607], [30643, 328717553.1676649], [30646, 328597958.73921466], [30647, 328611182.4069704], [30650, 328489134.79403067], [30657, 328623016.9784473], [30665, 328439289.9751606], [30670, 328519263.50540274], [30675, 328874946.2204963], [30679, 328704717.9348671], [30694, 328792860.59797734], [30704, 328754525.2405597], [30708, 328692685.7090267], [30718, 328683598.35203755], [30723, 328895331.7395912], [30729, 328995351.68054396], [30730, 328550708.7796585], [30734, 328809524.09403425], [30739, 329048647.0882876], [30744, 328723047.7621282], [30748, 328728549.81818074], [30750, 328907271.290694], [30754, 329073254.8582755], [30761, 329377559.7249926], [30762, 329105562.36208856], [30777, 328614255.4900473], [30782, 328534690.53569704], [30785, 328754819.3671306], [30787, 328845683.4085678], [30794, 328934072.5222621], [30804, 328813380.3722211], [30812, 328857548.2627267], [30817, 328970229.1881714], [30821, 329122960.05527496], [30838, 328849532.2732762], [30849, 328824675.81603056], [30861, 328994528.36042756], [30868, 329264075.4524304], [30872, 328957814.858025], [30890, 329011926.26474464], [30904, 328919108.2921632], [30907, 328724085.55784696], [30908, 329053633.68483096], [30917, 328769442.5124328], [30928, 328823042.6052123], [30931, 328887956.02993745], [30938, 328811452.85106677], [30945, 329044526.54498047], [30949, 328791817.916653], [30955, 328758959.79520214], [30957, 329075727.30600566], [30967, 328934319.56390953], [30974, 329188681.7953448], [30978, 328935726.96074164], [30987, 329114676.5300128], [30988, 328324113.69162446], [30994, 329100305.70087725], [30997, 329114888.49151635], [31009, 328979359.7783648], [31019, 328825497.4440292], [31031, 328637139.64067477], [31039, 328890994.3641687], [31040, 329095320.1683875], [31041, 329103078.18401694], [32090, 282508905.3215191], [32101, 281874883.31137854], [32104, 282156812.9251341], [32112, 282267950.2085942], [32115, 282153448.20757645], [32116, 282330200.09437424], [32120, 281986548.33450055], [32130, 282201493.7379761], [32131, 282256823.99968606], [32132, 282058693.8273008], [32138, 281931383.6927723], [32148, 282185726.9892732], [32152, 281768615.82764584], [32156, 282485035.83825403], [32157, 282249058.2060118], [32163, 282075994.7098131], [32174, 281814802.099707], [32181, 282562037.3490854], [32186, 282237716.8692199], [32187, 282132511.8736335], [32193, 281986417.29340285], [32197, 282176173.3190885], [32198, 285427288.13544005], [32204, 285488227.35806763], [32213, 285679521.8599908], [32218, 286458168.81062764], [32220, 286421643.6795538], [32224, 286646430.7022509], [32241, 286358376.7235294], [32249, 286152992.98122436], [32252, 286663928.4692702], [32256, 286339711.70815575], [32259, 286713823.16546595], [32261, 285368024.2788765], [32265, 285677549.2584892], [32270, 285002237.95759237], [32274, 285110462.9802685], [32292, 285135982.51319265], [32294, 285277777.6573827], [33213, 280541374.5249494], [33259, 280698965.17144483], [33296, 280902759.7124616], [33302, 280905612.3342111], [33309, 280890815.82862294], [33310, 280865218.14866835], [33311, 281284128.48374075], [33315, 280992718.82947165], [33323, 281712417.19960654], [33332, 280927174.8452645], [33333, 281576608.03847414], [33337, 281285715.0385508], [33338, 281408554.72985303], [33341, 281620353.25660735], [33346, 281681121.25802124], [33351, 281701538.2753232], [33358, 282546322.2793144], [33359, 282168458.877562], [33361, 282011984.8316301], [33370, 282077614.37066483], [33373, 282295790.70501745], [33380, 282653230.03767717], [33386, 282754599.63525265], [33393, 282691261.6133723], [33400, 282644651.2775077], [33414, 283202666.5875814], [33424, 282737854.41518193], [33428, 283992437.5986235], [33437, 283866974.4658324], [33444, 278407087.54343736], [33453, 278403096.3384448], [33516, 278560663.53415287], [33517, 278640668.5023542], [33518, 278527015.75355506], [33520, 278791991.1476185], [33524, 278628255.6506974], [33533, 278770043.6646792], [33536, 278683488.79668576], [33537, 278001213.0618474], [33543, 278067031.53677094], [33546, 277816835.90597314], [33648, 276787071.95261556], [33704, 276722435.8905145], [33707, 276999810.57574993], [33708, 276869057.1314375], [33712, 276882090.00939703], [33715, 276226383.33026296], [33722, 276784204.28182757], [33733, 276564890.22101706], [33734, 276413336.02567554], [33756, 276670767.97910655], [33766, 276615134.3988844], [33802, 276831845.89062035], [33808, 276607417.40640914], [33813, 276147163.4997658], [33818, 276646113.95594895], [33820, 276686570.9458646], [33826, 276598607.82627034], [33833, 276565805.5309991], [34031, 276140469.6264832], [34034, 275892994.7069027], [34046, 276805325.9112684], [34049, 276163242.9265463], [34052, 276615376.06602275], [34058, 277016567.79358566], [34065, 276401405.5823646], [34068, 276139492.72753906], [34075, 276269153.3998064], [34079, 276312170.13567686], [34113, 276764163.21613157], [34115, 276481638.3951455], [34120, 276382630.339994], [34126, 276796415.4677499], [34139, 276561086.99779767], [34140, 275803237.78255266], [34141, 276742586.58516496], [34155, 276462017.9752322], [34158, 276164537.2557049], [34160, 276556725.1227743], [34162, 276522733.4512824]] \ No newline at end of file +[[28497, 328787304.15116644], [29215, 327098178.94116604], [29225, 327329922.6163702], [29227, 327046996.5007472], [29228, 326847206.3868055], [29229, 326893020.89449], [29235, 327222016.35800034], [29240, 326450910.0935225], [29245, 326604705.01311046], [29246, 326682602.24418], [29258, 326617676.911352], [29262, 326734442.6433487], [29279, 326375540.6821199], [29286, 326657492.0191631], [29293, 326849085.8460318], [29294, 326448612.4689423], [29295, 326545302.0844503], [29296, 326457368.35326725], [29313, 326232647.1265717], [29318, 326695839.7862439], [29319, 326193316.9210879], [29322, 326236886.3420396], [29325, 326453608.45967263], [29327, 326395262.58020836], [29328, 326370010.62729466], [29340, 326333425.41044575], [29344, 325399045.00725514], [29349, 325404565.8871618], [29364, 325703633.47941947], [29371, 325887238.4262586], [29376, 325945165.9759367], [29381, 325948985.9601877], [29383, 326165279.7040554], [29387, 325719900.8416686], [29401, 325774610.9669895], [29404, 326362413.3703352], [29409, 325903302.0586441], [29414, 324885880.0951708], [29415, 325964730.16726184], [29420, 326085671.16495967], [29421, 326033261.0857228], [29425, 326167588.3775029], [29429, 326429993.2091037], [29435, 327159500.59344786], [29443, 326883573.5825806], [29446, 327198294.4851488], [29453, 326701370.6422426], [29454, 326840219.21051145], [29455, 326956788.60034037], [29457, 327034624.5914649], [29458, 327175718.46519804], [29469, 327082969.2461932], [29541, 327458779.7771476], [29548, 327134869.6950677], [29550, 327304965.2362931], [29551, 327588327.27268314], [29572, 326699320.0187576], [29591, 327967417.0149706], [29598, 327928955.5397637], [29609, 327912881.49540246], [29611, 328001644.25215966], [29621, 328292640.4783791], [29638, 327971913.5456901], [29644, 328199812.2122929], [29648, 328293945.376903], [29652, 327981958.79171646], [29656, 328290008.4607086], [29657, 327753300.5247031], [29662, 327832371.7926204], [29665, 328150374.4089112], [29667, 328198878.1151581], [29735, 327899098.4890833], [29742, 328015762.9022071], [29750, 327249491.73842686], [29753, 328155039.5765997], [29757, 328032437.0277452], [29761, 327885698.8162072], [29765, 328109316.9685904], [29766, 327449889.2512521], [29768, 327947546.02105516], [29776, 327912748.23967993], [29783, 328249695.849273], [29788, 327913603.10656035], [29789, 328348724.4353948], [29790, 328020468.77925885], [29795, 328169754.1959483], [29798, 328305335.9589891], [29805, 328405232.2874759], [29806, 328162655.6086873], [29807, 328199282.51774096], [29808, 328106736.07104456], [29813, 328304365.1382399], [29815, 328299216.7891178], [29828, 327553872.94226545], [29839, 328259300.3352093], [29844, 328229725.0717734], [29858, 328405955.0646043], [29865, 328262432.6514655], [29999, 328270850.2471481], [30002, 328247200.8495155], [30010, 328290196.65431374], [30013, 328204531.11812085], [30023, 328233629.844952], [30028, 328166266.78171885], [30035, 328167927.18712276], [30046, 328182231.7445017], [30053, 328150551.40918505], [30066, 328129688.18638396], [30068, 328170068.96374166], [30070, 328517783.8741365], [30074, 328478031.27165157], [30076, 328073637.9957334], [30077, 328468882.73626834], [30078, 328310433.5448388], [30085, 328212355.40244734], [30086, 328152445.5413199], [30096, 328018683.9792558], [30104, 328205429.6210177], [30106, 328252696.4427815], [30112, 328507664.8724834], [30116, 328205930.47512335], [30118, 328157513.54872894], [30123, 328135352.1469566], [30128, 328297431.3070782], [30135, 327494031.45254517], [30145, 328365900.0694801], [30155, 328525310.91120875], [30156, 328688513.7693295], [30157, 328523109.9128973], [30165, 328884832.42587006], [30174, 328877440.41147137], [30179, 328426959.81185037], [30185, 329010567.05074507], [30189, 328899001.1559543], [30190, 328694270.51619285], [30198, 328745646.7656918], [30202, 328667858.3287884], [30203, 328639096.8746306], [30208, 328648997.5257331], [30212, 328743485.05903864], [30213, 328554364.7087572], [30215, 328841820.7746717], [30218, 328677474.22900075], [30225, 328423140.93647814], [30227, 328727236.20779604], [30233, 328829963.8480206], [30235, 328867778.5268345], [30238, 328692993.05982363], [30244, 328983772.7903938], [30248, 328727785.41531724], [30254, 328518969.8829056], [30259, 328725302.28672934], [30260, 328741861.65178365], [30501, 328841004.0597946], [30502, 328021688.7318227], [30506, 328849515.9985624], [30507, 328744847.8269432], [30510, 328882961.36096585], [30515, 328603479.07451516], [30519, 328720869.778892], [30520, 328692391.73102546], [30524, 328825256.8003783], [30525, 328921619.3630317], [30529, 328945373.461277], [30533, 328671935.91789234], [30538, 328754022.82369524], [30542, 328527265.5941141], [30543, 328786823.31805646], [30544, 328635687.64826715], [30545, 328450215.2357533], [30550, 328588060.3541268], [30552, 328424241.44041246], [30556, 328397424.5531947], [30561, 328508944.04540974], [30564, 328672270.4187379], [30565, 328696233.30527765], [30577, 328556941.6049655], [30581, 328898143.4942162], [30586, 328453219.2585967], [30593, 328537218.4858719], [30615, 328691609.430268], [30621, 328991211.09126693], [30622, 328702904.1841921], [30629, 328621681.1464611], [30635, 328823819.6951763], [30639, 328673746.0876404], [30640, 328628056.49108607], [30643, 328717553.1676649], [30646, 328597958.73921466], [30647, 328611182.4069704], [30650, 328489134.79403067], [30657, 328623016.9784473], [30665, 328439289.9751606], [30670, 328519263.50540274], [30675, 328874946.2204963], [30679, 328704717.9348671], [30694, 328792860.59797734], [30704, 328754525.2405597], [30708, 328692685.7090267], [30718, 328683598.35203755], [30723, 328895331.7395912], [30729, 328995351.68054396], [30730, 328550708.7796585], [30734, 328809524.09403425], [30739, 329048647.0882876], [30744, 328723047.7621282], [30748, 328728549.81818074], [30750, 328907271.290694], [30754, 329073254.8582755], [30761, 329377559.7249926], [30762, 329105562.36208856], [30777, 328614255.4900473], [30782, 328534690.53569704], [30785, 328754819.3671306], [30787, 328845683.4085678], [30794, 328934072.5222621], [30804, 328813380.3722211], [30812, 328857548.2627267], [30817, 328970229.1881714], [30821, 329122960.05527496], [30838, 328849532.2732762], [30849, 328824675.81603056], [30861, 328994528.36042756], [30868, 329264075.4524304], [30872, 328957814.858025], [30890, 329011926.26474464], [30904, 328919108.2921632], [30907, 328724085.55784696], [30908, 329053633.68483096], [30917, 328769442.5124328], [30928, 328823042.6052123], [30931, 328887956.02993745], [30938, 328811452.85106677], [30945, 329044526.54498047], [30949, 328791817.916653], [30955, 328758959.79520214], [30957, 329075727.30600566], [30967, 328934319.56390953], [30974, 329188681.7953448], [30978, 328935726.96074164], [30987, 329114676.5300128], [30988, 328324113.69162446], [30994, 329100305.70087725], [30997, 329114888.49151635], [31009, 328979359.7783648], [31019, 328825497.4440292], [31031, 328637139.64067477], [31039, 328890994.3641687], [31040, 329095320.1683875], [31041, 329103078.18401694], [32090, 282508905.3215191], [32101, 281874883.31137854], [32104, 282156812.9251341], [32112, 282267950.2085942], [32115, 282153448.20757645], [32116, 282330200.09437424], [32120, 281986548.33450055], [32130, 282201493.7379761], [32131, 282256823.99968606], [32132, 282058693.8273008], [32138, 281931383.6927723], [32148, 282185726.9892732], [32152, 281768615.82764584], [32156, 282485035.83825403], [32157, 282249058.2060118], [32163, 282075994.7098131], [32174, 281814802.099707], [32181, 282562037.3490854], [32186, 282237716.8692199], [32187, 282132511.8736335], [32193, 281986417.29340285], [32197, 282176173.3190885], [32198, 285427288.13544005], [32204, 285488227.35806763], [32213, 285679521.8599908], [32218, 286458168.81062764], [32220, 286421643.6795538], [32224, 286646430.7022509], [32241, 286358376.7235294], [32249, 286152992.98122436], [32252, 286663928.4692702], [32256, 286339711.70815575], [32259, 286713823.16546595], [32261, 285368024.2788765], [32265, 285677549.2584892], [32270, 285002237.95759237], [32274, 285110462.9802685], [32292, 285135982.51319265], [32294, 285277777.6573827], [33213, 280541374.5249494], [33259, 280698965.17144483], [33296, 280902759.7124616], [33302, 280905612.3342111], [33309, 280890815.82862294], [33310, 280865218.14866835], [33311, 281284128.48374075], [33315, 280992718.82947165], [33323, 281712417.19960654], [33332, 280927174.8452645], [33333, 281576608.03847414], [33337, 281285715.0385508], [33338, 281408554.72985303], [33341, 281620353.25660735], [33346, 281681121.25802124], [33351, 281701538.2753232], [33358, 282546322.2793144], [33359, 282168458.877562], [33361, 282011984.8316301], [33370, 282077614.37066483], [33373, 282295790.70501745], [33380, 282653230.03767717], [33386, 282754599.63525265], [33393, 282691261.6133723], [33400, 282644651.2775077], [33414, 283202666.5875814], [33424, 282737854.41518193], [33428, 283992437.5986235], [33437, 283866974.4658324], [33444, 278407087.54343736], [33453, 278403096.3384448], [33516, 278560663.53415287], [33517, 278640668.5023542], [33518, 278527015.75355506], [33520, 278791991.1476185], [33524, 278628255.6506974], [33533, 278770043.6646792], [33536, 278683488.79668576], [33537, 278001213.0618474], [33543, 278067031.53677094], [33546, 277816835.90597314], [33648, 276787071.95261556], [33704, 276722435.8905145], [33707, 276999810.57574993], [33708, 276869057.1314375], [33712, 276882090.00939703], [33715, 276226383.33026296], [33722, 276784204.28182757], [33733, 276564890.22101706], [33734, 276413336.02567554], [33756, 276670767.97910655], [33766, 276615134.3988844], [33802, 276831845.89062035], [33808, 276607417.40640914], [33813, 276147163.4997658], [33818, 276646113.95594895], [33820, 276686570.9458646], [33826, 276598607.82627034], [33833, 276565805.5309991], [34031, 276140469.6264832], [34034, 275892994.7069027], [34046, 276805325.9112684], [34049, 276163242.9265463], [34052, 276615376.06602275], [34058, 277016567.79358566], [34065, 276401405.5823646], [34068, 276139492.72753906], [34075, 276269153.3998064], [34079, 276312170.13567686], [34113, 276764163.21613157], [34115, 276481638.3951455], [34120, 276382630.339994], [34126, 276796415.4677499], [34139, 276561086.99779767], [34140, 275803237.78255266], [34141, 276742586.58516496], [34155, 276462017.9752322], [34158, 276164537.2557049], [34160, 276556725.1227743], [34162, 276522733.4512824], [34164, 276169464.55709225]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LinearRegressionBenchmark.time_fit.json b/graphs/summary/linear_model.LinearRegressionBenchmark.time_fit.json index 149f1e8be6..9d8e52ea57 100644 --- a/graphs/summary/linear_model.LinearRegressionBenchmark.time_fit.json +++ b/graphs/summary/linear_model.LinearRegressionBenchmark.time_fit.json @@ -1 +1 @@ -[[28497, 0.7670027288690253], [29215, 2.0317083339626723], [29225, 1.6850654845930086], [29227, 1.97697960001286], [29228, 1.715248594642864], [29229, 1.7120541564237333], [29235, 1.8504395037502228], [29240, 0.8218993013643217], [29245, 0.8190582880665124], [29246, 0.8224029929136254], [29258, 0.8786062893452422], [29262, 0.9028427239132413], [29279, 0.8749773912583496], [29286, 0.9387551663501877], [29293, 0.7902926936057779], [29294, 0.780154399376658], [29295, 0.7869526463403976], [29296, 0.8284110086978042], [29313, 0.816711069708861], [29318, 0.774382629916316], [29319, 0.7833932530488391], [29322, 0.8558009623610286], [29325, 0.8042179175036939], [29327, 0.8392451110957407], [29328, 0.7820941270778786], [29340, 0.8960127427909144], [29344, 0.8431622943142125], [29349, 0.8463822330023938], [29364, 0.7736278539510453], [29371, 0.8411020366843867], [29376, 0.9575889273291037], [29381, 0.8518132235737423], [29383, 0.8582468334277454], [29387, 0.9181724163184151], [29401, 0.7753454148271773], [29404, 0.8175660909670573], [29409, 0.8101719486163341], [29414, 0.8550401589113225], [29415, 0.9202796737042721], [29420, 0.889847208143304], [29421, 0.7740904488445151], [29425, 0.8041404312845222], [29429, 0.9877762952230468], [29435, 1.9119315967397525], [29443, 1.7886672157975365], [29446, 1.8484077763492714], [29453, 1.841716271525753], [29454, 1.906878738736181], [29455, 1.8363193016499937], [29457, 1.9414371567875857], [29458, 1.810532196501947], [29469, 1.8817677395456518], [29541, 1.8796376135127826], [29548, 1.9787821599981603], [29550, 1.8605137723596399], [29551, 1.611069963607682], [29572, 1.5819201605805147], [29591, 1.6847958022876015], [29598, 1.666101480374696], [29609, 1.6236688690761973], [29611, 1.5608215196935185], [29621, 1.5804937061350406], [29638, 1.5609958176268826], [29644, 1.6417883902586965], [29648, 1.6168547209151412], [29652, 1.6077497165980477], [29656, 1.5810586062721097], [29657, 1.582030988540719], [29662, 1.5708329840903792], [29665, 1.564554445112649], [29667, 1.6372436741346414], [29735, 1.5782951146722155], [29742, 1.6049059368857204], [29750, 1.6212090424599255], [29753, 1.5957181149253794], [29757, 1.6111010537703954], [29761, 1.5849186503504875], [29765, 1.576631841505199], [29766, 1.5711389891824297], [29768, 1.6353881147831535], [29776, 1.9539473649090853], [29783, 1.7991822322526052], [29788, 1.7923857778719592], [29789, 1.673612124434807], [29790, 1.6796608535651856], [29795, 1.7023161590335139], [29798, 1.8153181133831042], [29805, 1.9686297924059941], [29806, 1.8580578512832293], [29807, 1.64248458278274], [29808, 1.8411158192323498], [29813, 1.8399225027400707], [29815, 1.674435797826298], [29828, 1.6523194917171329], [29839, 1.6565651504414685], [29844, 1.7487987590508978], [29858, 1.709924785855935], [29865, 1.788413763552007], [29999, 1.6986010250472288], [30002, 1.8209373389179542], [30010, 1.8354468557566042], [30013, 1.6986420222826], [30023, 1.7293979953129655], [30028, 1.8027410679122315], [30035, 1.70352536922512], [30046, 1.9280582764485585], [30053, 2.006967691161731], [30066, 1.8863382415520904], [30068, 1.8664117175895858], [30070, 1.8814091058416567], [30074, 1.7947704510152922], [30076, 1.9225084942737012], [30077, 1.8710079852466752], [30078, 1.7189875816378921], [30085, 1.6309854026591986], [30086, 1.7665172100669104], [30096, 1.8476830029286344], [30104, 1.7578707986676665], [30106, 1.967557461529028], [30112, 1.7379689933002658], [30116, 1.7390608717795117], [30118, 1.7842315526498007], [30123, 1.6541521887501631], [30128, 1.6873456225365924], [30135, 1.919238237236852], [30145, 1.9715856499306639], [30155, 1.6424371264485056], [30156, 1.7738675675660809], [30157, 1.974238116200863], [30165, 1.8853439034643704], [30174, 1.8207560627052874], [30179, 1.7640606061325628], [30185, 1.7699445366256035], [30189, 1.9619258287354062], [30190, 1.6557283172956172], [30198, 1.7378327913851377], [30202, 1.9716442013856983], [30203, 1.7824784886694027], [30208, 1.7495422079223648], [30212, 1.9229889627782089], [30213, 1.8123979403550015], [30215, 1.9764606039749608], [30218, 1.7257978369491815], [30225, 1.9565147809567964], [30227, 1.7604636610667252], [30233, 1.711067515942334], [30235, 1.8684173703517466], [30238, 1.7737337737404626], [30244, 1.8507158418718956], [30248, 1.7325743101012696], [30254, 1.7895508565231484], [30259, 1.8819147096394486], [30260, 1.6882341773722929], [30501, 1.958325601326453], [30502, 1.7600324755474466], [30506, 1.7044983720067721], [30507, 1.929832035925905], [30510, 1.8588156527038622], [30515, 1.816629513520083], [30519, 1.7141225483506146], [30520, 1.8717970686629852], [30524, 1.7253344256780896], [30525, 1.706128572815942], [30529, 1.7660347447230074], [30533, 1.9362749158959167], [30538, 1.8011778475684344], [30542, 1.921546532774889], [30543, 2.009410266871124], [30544, 1.6942304565043411], [30545, 1.776209119868407], [30550, 1.9457862118860474], [30552, 1.7837720303567757], [30556, 1.7832038698299988], [30561, 1.7149253810075669], [30564, 1.8181654994120575], [30565, 1.7535555292462846], [30577, 2.078390384507815], [30581, 1.7720196763625755], [30586, 1.9373477448688055], [30593, 1.6892073048162284], [30615, 1.8336481635654285], [30621, 1.758089525813159], [30622, 1.8912737546620586], [30629, 1.6953963061869681], [30635, 1.6773103571622354], [30639, 1.9379489403562211], [30640, 1.7475871605688658], [30643, 1.8590959891234542], [30646, 1.8416640425930473], [30647, 1.8560378328512317], [30650, 1.715161461103693], [30657, 1.7064090675364767], [30665, 1.9339979023107847], [30670, 1.6502769282971315], [30675, 1.786138593689935], [30679, 1.6507010648485634], [30694, 1.9589630183458966], [30704, 1.7236538594465707], [30708, 1.7053337991402828], [30718, 1.6513622731363145], [30723, 1.738041997786503], [30729, 1.8777535624748907], [30730, 1.8303086414684588], [30734, 1.8838485192619405], [30739, 1.7017948781793497], [30744, 1.8118813834940766], [30748, 1.9170810142923307], [30750, 1.7018312167972236], [30754, 1.8443029239103588], [30761, 1.7117431096449212], [30762, 1.654865456569545], [30777, 1.6631308746525204], [30782, 1.7493516260795796], [30785, 2.010824388034362], [30787, 1.9188464118853261], [30794, 1.7908699002609336], [30804, 1.8342671363330227], [30812, 1.7262608646175257], [30817, 1.80503414217748], [30821, 1.6425183913202905], [30838, 1.6769248323208223], [30849, 1.9026122983952294], [30861, 1.7174412292605554], [30868, 1.9638208094104592], [30872, 1.6362871790132543], [30890, 1.7022640926995847], [30904, 2.4772135894372003], [30907, 2.1965624154593004], [30908, 2.614973166248388], [30917, 2.1807497906246365], [30928, 2.2586103843481657], [30931, 2.1915531883917807], [30938, 2.4878553899323843], [30945, 2.262808535495075], [30949, 2.441514037303918], [30955, 2.3268445099031667], [30957, 2.3323758674750175], [30967, 2.3522071764900288], [30974, 2.130114556584749], [30978, 2.148745444829366], [30987, 2.08573725038087], [30988, 2.168505545714986], [30994, 2.2468766379836587], [30997, 2.104700681767819], [31009, 2.682459758221501], [31019, 2.412058505316337], [31031, 2.0855231361211275], [31039, 2.2544278800424453], [31040, 2.083158843481867], [31041, 2.169116439531745], [32090, 2.289367213725081], [32101, 2.2842090476640657], [32104, 2.3442250293102846], [32112, 2.232433037356549], [32115, 2.24715244075413], [32116, 2.2647547768392875], [32120, 2.3150105657178655], [32130, 2.303994516758621], [32131, 2.279331130721187], [32132, 2.2402571890164893], [32138, 2.2262418949649345], [32148, 2.265392439602322], [32152, 2.370411276039898], [32156, 2.2679711799660853], [32157, 2.3805940869823137], [32163, 2.2422138281786443], [32174, 2.271377606761759], [32181, 2.3208364262468013], [32186, 2.255995691242301], [32187, 2.289506098702815], [32193, 2.2638006216826074], [32197, 2.2872424208334263], [32198, 2.0605254572137066], [32204, 2.096921298490956], [32213, 2.047379094472232], [32218, 2.0664376482985323], [32220, 2.171923055934207], [32224, 2.0877354774081716], [32241, 2.0722153213732755], [32249, 2.3187213390218435], [32252, 2.071719637506678], [32256, 1.9961713693993237], [32259, 2.0150516542969457], [32261, 2.2040339192494725], [32265, 2.1861624241750506], [32270, 1.9610811961688015], [32274, 1.9625220251930109], [32292, 2.132643560068157], [32294, 2.095025784950825], [33213, 1.9383379580107412], [33259, 1.9471944464821944], [33296, 2.102763671666327], [33302, 1.9121178348597838], [33309, 1.7228494956699887], [33310, 1.8158892816654437], [33311, 1.9131851318923692], [33315, 1.974846974351093], [33323, 1.8992561778616304], [33332, 1.969506468246454], [33333, 1.8863250007452896], [33337, 1.9240335861019815], [33338, 1.902827822849607], [33341, 1.991648384422383], [33346, 2.044331890910552], [33351, 1.8539353079289012], [33358, 1.8710312732636927], [33359, 1.7327623167498192], [33361, 1.9720746060403558], [33370, 1.9725498366543373], [33373, 1.8906911042552064], [33380, 1.959217462072267], [33386, 1.957212182210371], [33393, 1.9085580318049873], [33400, 2.002496286449468], [33414, 1.9449264873701753], [33424, 2.0268936358770357], [33428, 1.9717582773576547], [33437, 1.9848606054529416], [33444, 1.9520469410338472], [33453, 1.9391444808490919], [33516, 1.9652826456177537], [33517, 1.8755699113585151], [33518, 1.9049375426868451], [33520, 1.9806003054579466], [33524, 1.933589353882882], [33533, 1.9282918638720168], [33536, 1.935233478481392], [33537, 1.9296115710927775], [33543, 1.882989616880713], [33546, 1.86081902722387], [33648, 1.9919736978414337], [33704, 1.8687403491232801], [33707, 2.029065121220803], [33708, 1.8711876509344776], [33712, 2.006368328849859], [33715, 1.9253827596323885], [33722, 1.9250506242009329], [33733, 1.8114070148079404], [33734, 1.9721951387899692], [33756, 1.811036801749629], [33766, 1.9164668416869666], [33802, 1.901796532841748], [33808, 1.8422969976797072], [33813, 1.8425514096772624], [33818, 1.8609174508252926], [33820, 1.8561235660970115], [33826, 1.8687682507535799], [33833, 1.8924977146440582], [34031, 1.8807342484268939], [34034, 1.870139850866268], [34046, 1.8621396801066905], [34049, 1.9767115840294058], [34052, 2.078347136421663], [34058, 1.971677980157737], [34065, 1.933538669654708], [34068, 2.001242267093898], [34075, 1.9874601749813312], [34079, 2.017278952828842], [34113, 1.87763186854628], [34115, 1.866886807459026], [34120, 1.838618370703505], [34126, 1.8691835826314116], [34139, 1.8732469159763048], [34140, 1.8724361473078803], [34141, 1.8527778322033677], [34155, 1.857048649597801], [34158, 1.8805453436519664], [34160, 1.8728795254832178], [34162, 1.8891350711625756]] \ No newline at end of file +[[28497, 0.7670027288690253], [29215, 2.0317083339626723], [29225, 1.6850654845930086], [29227, 1.97697960001286], [29228, 1.715248594642864], [29229, 1.7120541564237333], [29235, 1.8504395037502228], [29240, 0.8218993013643217], [29245, 0.8190582880665124], [29246, 0.8224029929136254], [29258, 0.8786062893452422], [29262, 0.9028427239132413], [29279, 0.8749773912583496], [29286, 0.9387551663501877], [29293, 0.7902926936057779], [29294, 0.780154399376658], [29295, 0.7869526463403976], [29296, 0.8284110086978042], [29313, 0.816711069708861], [29318, 0.774382629916316], [29319, 0.7833932530488391], [29322, 0.8558009623610286], [29325, 0.8042179175036939], [29327, 0.8392451110957407], [29328, 0.7820941270778786], [29340, 0.8960127427909144], [29344, 0.8431622943142125], [29349, 0.8463822330023938], [29364, 0.7736278539510453], [29371, 0.8411020366843867], [29376, 0.9575889273291037], [29381, 0.8518132235737423], [29383, 0.8582468334277454], [29387, 0.9181724163184151], [29401, 0.7753454148271773], [29404, 0.8175660909670573], [29409, 0.8101719486163341], [29414, 0.8550401589113225], [29415, 0.9202796737042721], [29420, 0.889847208143304], [29421, 0.7740904488445151], [29425, 0.8041404312845222], [29429, 0.9877762952230468], [29435, 1.9119315967397525], [29443, 1.7886672157975365], [29446, 1.8484077763492714], [29453, 1.841716271525753], [29454, 1.906878738736181], [29455, 1.8363193016499937], [29457, 1.9414371567875857], [29458, 1.810532196501947], [29469, 1.8817677395456518], [29541, 1.8796376135127826], [29548, 1.9787821599981603], [29550, 1.8605137723596399], [29551, 1.611069963607682], [29572, 1.5819201605805147], [29591, 1.6847958022876015], [29598, 1.666101480374696], [29609, 1.6236688690761973], [29611, 1.5608215196935185], [29621, 1.5804937061350406], [29638, 1.5609958176268826], [29644, 1.6417883902586965], [29648, 1.6168547209151412], [29652, 1.6077497165980477], [29656, 1.5810586062721097], [29657, 1.582030988540719], [29662, 1.5708329840903792], [29665, 1.564554445112649], [29667, 1.6372436741346414], [29735, 1.5782951146722155], [29742, 1.6049059368857204], [29750, 1.6212090424599255], [29753, 1.5957181149253794], [29757, 1.6111010537703954], [29761, 1.5849186503504875], [29765, 1.576631841505199], [29766, 1.5711389891824297], [29768, 1.6353881147831535], [29776, 1.9539473649090853], [29783, 1.7991822322526052], [29788, 1.7923857778719592], [29789, 1.673612124434807], [29790, 1.6796608535651856], [29795, 1.7023161590335139], [29798, 1.8153181133831042], [29805, 1.9686297924059941], [29806, 1.8580578512832293], [29807, 1.64248458278274], [29808, 1.8411158192323498], [29813, 1.8399225027400707], [29815, 1.674435797826298], [29828, 1.6523194917171329], [29839, 1.6565651504414685], [29844, 1.7487987590508978], [29858, 1.709924785855935], [29865, 1.788413763552007], [29999, 1.6986010250472288], [30002, 1.8209373389179542], [30010, 1.8354468557566042], [30013, 1.6986420222826], [30023, 1.7293979953129655], [30028, 1.8027410679122315], [30035, 1.70352536922512], [30046, 1.9280582764485585], [30053, 2.006967691161731], [30066, 1.8863382415520904], [30068, 1.8664117175895858], [30070, 1.8814091058416567], [30074, 1.7947704510152922], [30076, 1.9225084942737012], [30077, 1.8710079852466752], [30078, 1.7189875816378921], [30085, 1.6309854026591986], [30086, 1.7665172100669104], [30096, 1.8476830029286344], [30104, 1.7578707986676665], [30106, 1.967557461529028], [30112, 1.7379689933002658], [30116, 1.7390608717795117], [30118, 1.7842315526498007], [30123, 1.6541521887501631], [30128, 1.6873456225365924], [30135, 1.919238237236852], [30145, 1.9715856499306639], [30155, 1.6424371264485056], [30156, 1.7738675675660809], [30157, 1.974238116200863], [30165, 1.8853439034643704], [30174, 1.8207560627052874], [30179, 1.7640606061325628], [30185, 1.7699445366256035], [30189, 1.9619258287354062], [30190, 1.6557283172956172], [30198, 1.7378327913851377], [30202, 1.9716442013856983], [30203, 1.7824784886694027], [30208, 1.7495422079223648], [30212, 1.9229889627782089], [30213, 1.8123979403550015], [30215, 1.9764606039749608], [30218, 1.7257978369491815], [30225, 1.9565147809567964], [30227, 1.7604636610667252], [30233, 1.711067515942334], [30235, 1.8684173703517466], [30238, 1.7737337737404626], [30244, 1.8507158418718956], [30248, 1.7325743101012696], [30254, 1.7895508565231484], [30259, 1.8819147096394486], [30260, 1.6882341773722929], [30501, 1.958325601326453], [30502, 1.7600324755474466], [30506, 1.7044983720067721], [30507, 1.929832035925905], [30510, 1.8588156527038622], [30515, 1.816629513520083], [30519, 1.7141225483506146], [30520, 1.8717970686629852], [30524, 1.7253344256780896], [30525, 1.706128572815942], [30529, 1.7660347447230074], [30533, 1.9362749158959167], [30538, 1.8011778475684344], [30542, 1.921546532774889], [30543, 2.009410266871124], [30544, 1.6942304565043411], [30545, 1.776209119868407], [30550, 1.9457862118860474], [30552, 1.7837720303567757], [30556, 1.7832038698299988], [30561, 1.7149253810075669], [30564, 1.8181654994120575], [30565, 1.7535555292462846], [30577, 2.078390384507815], [30581, 1.7720196763625755], [30586, 1.9373477448688055], [30593, 1.6892073048162284], [30615, 1.8336481635654285], [30621, 1.758089525813159], [30622, 1.8912737546620586], [30629, 1.6953963061869681], [30635, 1.6773103571622354], [30639, 1.9379489403562211], [30640, 1.7475871605688658], [30643, 1.8590959891234542], [30646, 1.8416640425930473], [30647, 1.8560378328512317], [30650, 1.715161461103693], [30657, 1.7064090675364767], [30665, 1.9339979023107847], [30670, 1.6502769282971315], [30675, 1.786138593689935], [30679, 1.6507010648485634], [30694, 1.9589630183458966], [30704, 1.7236538594465707], [30708, 1.7053337991402828], [30718, 1.6513622731363145], [30723, 1.738041997786503], [30729, 1.8777535624748907], [30730, 1.8303086414684588], [30734, 1.8838485192619405], [30739, 1.7017948781793497], [30744, 1.8118813834940766], [30748, 1.9170810142923307], [30750, 1.7018312167972236], [30754, 1.8443029239103588], [30761, 1.7117431096449212], [30762, 1.654865456569545], [30777, 1.6631308746525204], [30782, 1.7493516260795796], [30785, 2.010824388034362], [30787, 1.9188464118853261], [30794, 1.7908699002609336], [30804, 1.8342671363330227], [30812, 1.7262608646175257], [30817, 1.80503414217748], [30821, 1.6425183913202905], [30838, 1.6769248323208223], [30849, 1.9026122983952294], [30861, 1.7174412292605554], [30868, 1.9638208094104592], [30872, 1.6362871790132543], [30890, 1.7022640926995847], [30904, 2.4772135894372003], [30907, 2.1965624154593004], [30908, 2.614973166248388], [30917, 2.1807497906246365], [30928, 2.2586103843481657], [30931, 2.1915531883917807], [30938, 2.4878553899323843], [30945, 2.262808535495075], [30949, 2.441514037303918], [30955, 2.3268445099031667], [30957, 2.3323758674750175], [30967, 2.3522071764900288], [30974, 2.130114556584749], [30978, 2.148745444829366], [30987, 2.08573725038087], [30988, 2.168505545714986], [30994, 2.2468766379836587], [30997, 2.104700681767819], [31009, 2.682459758221501], [31019, 2.412058505316337], [31031, 2.0855231361211275], [31039, 2.2544278800424453], [31040, 2.083158843481867], [31041, 2.169116439531745], [32090, 2.289367213725081], [32101, 2.2842090476640657], [32104, 2.3442250293102846], [32112, 2.232433037356549], [32115, 2.24715244075413], [32116, 2.2647547768392875], [32120, 2.3150105657178655], [32130, 2.303994516758621], [32131, 2.279331130721187], [32132, 2.2402571890164893], [32138, 2.2262418949649345], [32148, 2.265392439602322], [32152, 2.370411276039898], [32156, 2.2679711799660853], [32157, 2.3805940869823137], [32163, 2.2422138281786443], [32174, 2.271377606761759], [32181, 2.3208364262468013], [32186, 2.255995691242301], [32187, 2.289506098702815], [32193, 2.2638006216826074], [32197, 2.2872424208334263], [32198, 2.0605254572137066], [32204, 2.096921298490956], [32213, 2.047379094472232], [32218, 2.0664376482985323], [32220, 2.171923055934207], [32224, 2.0877354774081716], [32241, 2.0722153213732755], [32249, 2.3187213390218435], [32252, 2.071719637506678], [32256, 1.9961713693993237], [32259, 2.0150516542969457], [32261, 2.2040339192494725], [32265, 2.1861624241750506], [32270, 1.9610811961688015], [32274, 1.9625220251930109], [32292, 2.132643560068157], [32294, 2.095025784950825], [33213, 1.9383379580107412], [33259, 1.9471944464821944], [33296, 2.102763671666327], [33302, 1.9121178348597838], [33309, 1.7228494956699887], [33310, 1.8158892816654437], [33311, 1.9131851318923692], [33315, 1.974846974351093], [33323, 1.8992561778616304], [33332, 1.969506468246454], [33333, 1.8863250007452896], [33337, 1.9240335861019815], [33338, 1.902827822849607], [33341, 1.991648384422383], [33346, 2.044331890910552], [33351, 1.8539353079289012], [33358, 1.8710312732636927], [33359, 1.7327623167498192], [33361, 1.9720746060403558], [33370, 1.9725498366543373], [33373, 1.8906911042552064], [33380, 1.959217462072267], [33386, 1.957212182210371], [33393, 1.9085580318049873], [33400, 2.002496286449468], [33414, 1.9449264873701753], [33424, 2.0268936358770357], [33428, 1.9717582773576547], [33437, 1.9848606054529416], [33444, 1.9520469410338472], [33453, 1.9391444808490919], [33516, 1.9652826456177537], [33517, 1.8755699113585151], [33518, 1.9049375426868451], [33520, 1.9806003054579466], [33524, 1.933589353882882], [33533, 1.9282918638720168], [33536, 1.935233478481392], [33537, 1.9296115710927775], [33543, 1.882989616880713], [33546, 1.86081902722387], [33648, 1.9919736978414337], [33704, 1.8687403491232801], [33707, 2.029065121220803], [33708, 1.8711876509344776], [33712, 2.006368328849859], [33715, 1.9253827596323885], [33722, 1.9250506242009329], [33733, 1.8114070148079404], [33734, 1.9721951387899692], [33756, 1.811036801749629], [33766, 1.9164668416869666], [33802, 1.901796532841748], [33808, 1.8422969976797072], [33813, 1.8425514096772624], [33818, 1.8609174508252926], [33820, 1.8561235660970115], [33826, 1.8687682507535799], [33833, 1.8924977146440582], [34031, 1.8807342484268939], [34034, 1.870139850866268], [34046, 1.8621396801066905], [34049, 1.9767115840294058], [34052, 2.078347136421663], [34058, 1.971677980157737], [34065, 1.933538669654708], [34068, 2.001242267093898], [34075, 1.9874601749813312], [34079, 2.017278952828842], [34113, 1.87763186854628], [34115, 1.866886807459026], [34120, 1.838618370703505], [34126, 1.8691835826314116], [34139, 1.8732469159763048], [34140, 1.8724361473078803], [34141, 1.8527778322033677], [34155, 1.857048649597801], [34158, 1.8805453436519664], [34160, 1.8728795254832178], [34162, 1.8891350711625756], [34164, 1.8791068218778368]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LinearRegressionBenchmark.time_predict.json b/graphs/summary/linear_model.LinearRegressionBenchmark.time_predict.json index 28b49fe959..c9acbea922 100644 --- a/graphs/summary/linear_model.LinearRegressionBenchmark.time_predict.json +++ b/graphs/summary/linear_model.LinearRegressionBenchmark.time_predict.json @@ -1 +1 @@ -[[28497, 0.054903094039247036], [29215, 0.09047455108186246], [29225, 0.08751469615063344], [29227, 0.08918766605313662], [29228, 0.08833958084932605], [29229, 0.08819503856241483], [29235, 0.08719389598066425], [29240, 0.06635004147837376], [29245, 0.05463390374945392], [29246, 0.05356047116743053], [29258, 0.053214197601916695], [29262, 0.0543368570649475], [29279, 0.0595210451786751], [29286, 0.06127668335128591], [29293, 0.05375965443633766], [29294, 0.054002998472526695], [29295, 0.053683252657023395], [29296, 0.054065435236503034], [29313, 0.053666599508913976], [29318, 0.05452537337063146], [29319, 0.0543456960948009], [29322, 0.05487326341760504], [29325, 0.054523073213713316], [29327, 0.05656199591440331], [29328, 0.05366573149419437], [29340, 0.05857008457925727], [29344, 0.061197166747998986], [29349, 0.0535293540472246], [29364, 0.05479980358210308], [29371, 0.0538471361619987], [29376, 0.06086449387728128], [29381, 0.05392456655881818], [29383, 0.05407109295641383], [29387, 0.061471533915078126], [29401, 0.05443520734688522], [29404, 0.06450141701117636], [29409, 0.05341519250916818], [29414, 0.054873918330760704], [29415, 0.059280378692316164], [29420, 0.055605213323057866], [29421, 0.05428091153865277], [29425, 0.05401923591210642], [29429, 0.05594162290887323], [29435, 0.0946961098753781], [29443, 0.08551534115523901], [29446, 0.0880315903654639], [29453, 0.08594392181124345], [29454, 0.08655110028156159], [29455, 0.08753081013268492], [29457, 0.0890355037398804], [29458, 0.09196030390502442], [29469, 0.08886734373095316], [29541, 0.08995784607495526], [29548, 0.08970944259287754], [29550, 0.08883492280472212], [29551, 0.07410987674455453], [29572, 0.07878563539607371], [29591, 0.07794697480294269], [29598, 0.079761457238947], [29609, 0.07838976741888565], [29611, 0.07735554783297585], [29621, 0.07994099667033036], [29638, 0.0801597905267139], [29644, 0.07474005299560324], [29648, 0.07546431248349791], [29652, 0.07499441069081862], [29656, 0.07820836251307085], [29657, 0.07859089024187062], [29662, 0.0738824071876207], [29665, 0.078947032632273], [29667, 0.0742199164242152], [29735, 0.07780702754493252], [29742, 0.07488491615404813], [29750, 0.0792107225094401], [29753, 0.07993598346168011], [29757, 0.07918110829797596], [29761, 0.07765848982689172], [29765, 0.07847770420312054], [29766, 0.07754553343183229], [29768, 0.0798747608845263], [29776, 0.09408150194010759], [29783, 0.08221010010040461], [29788, 0.10024669324511289], [29789, 0.0790663434725697], [29790, 0.07845117778665099], [29795, 0.08246654602186093], [29798, 0.07851051519371571], [29805, 0.08559172829132844], [29806, 0.08778184029673829], [29807, 0.07753953951061492], [29808, 0.0848436191403751], [29813, 0.08627318676788107], [29815, 0.07865791792847181], [29828, 0.07583505735689032], [29839, 0.07741774263413251], [29844, 0.08537241271606913], [29858, 0.0779438216453587], [29865, 0.09212733002094387], [29999, 0.08475756239722708], [30002, 0.09112220317976744], [30010, 0.07870454885302072], [30013, 0.07876627702254206], [30023, 0.09192219258677414], [30028, 0.0876893299098634], [30035, 0.07825964969326898], [30046, 0.09138723202176516], [30053, 0.09283536422850497], [30066, 0.08025022781328324], [30068, 0.08842531905314019], [30070, 0.09550563580067298], [30074, 0.09081675210201473], [30076, 0.07920107924185774], [30077, 0.09041668989187074], [30078, 0.09065971253065569], [30085, 0.08453566193074383], [30086, 0.08877316515655585], [30096, 0.08215703295850867], [30104, 0.08957123791898515], [30106, 0.08550644891286115], [30112, 0.08584017694279682], [30116, 0.08677475067332892], [30118, 0.08637524503020365], [30123, 0.0883655331134633], [30128, 0.07841065471698609], [30135, 0.08434849833998323], [30145, 0.09036579477698065], [30155, 0.08685930258863149], [30156, 0.08838779998155376], [30157, 0.0868225881316682], [30165, 0.08461015351792758], [30174, 0.09048895450464713], [30179, 0.09149378954886411], [30185, 0.0796579099161991], [30189, 0.08767594162785804], [30190, 0.07892189047622122], [30198, 0.09233402290100136], [30202, 0.08169808345132816], [30203, 0.0920118640824603], [30208, 0.09124542828664585], [30212, 0.09264086393938042], [30213, 0.09395285580130738], [30215, 0.08985719938778125], [30218, 0.08067887208164454], [30225, 0.08527102569495915], [30227, 0.08527034974066884], [30233, 0.07846096249836701], [30235, 0.08594024805084018], [30238, 0.08526954723961049], [30244, 0.08690788972074392], [30248, 0.08132331795206865], [30254, 0.08388812844194021], [30259, 0.08819788708306249], [30260, 0.08643007971363811], [30501, 0.09071421303313248], [30502, 0.08608944303497643], [30506, 0.07865211237903508], [30507, 0.09140561383221014], [30510, 0.08071363248262538], [30515, 0.0925595054385495], [30519, 0.09108828260290427], [30520, 0.07821873869447127], [30524, 0.07959059809009209], [30525, 0.08047743522386504], [30529, 0.08594487845783877], [30533, 0.09354796634778857], [30538, 0.08787308377335884], [30542, 0.07986217638174577], [30543, 0.08626831522293996], [30544, 0.08063563575679018], [30545, 0.08751091227904224], [30550, 0.09177063072999037], [30552, 0.08547185202358187], [30556, 0.08875155424617176], [30561, 0.0897680308316318], [30564, 0.09378692268779323], [30565, 0.07878304179835802], [30577, 0.09147028113315828], [30581, 0.08699583614456445], [30586, 0.09107200238539097], [30593, 0.07945085187899481], [30615, 0.0895152714990597], [30621, 0.0921772778521892], [30622, 0.08675590239536846], [30629, 0.09162906915719606], [30635, 0.082300478547682], [30639, 0.08561146971400413], [30640, 0.08254703380449835], [30643, 0.09120889293881], [30646, 0.08271093526834607], [30647, 0.08775998210841586], [30650, 0.08889354322797606], [30657, 0.08450784472942907], [30665, 0.08934195057551636], [30670, 0.07834804981471459], [30675, 0.08914398971563975], [30679, 0.07899887960138453], [30694, 0.08897426484825917], [30704, 0.07817568276343684], [30708, 0.07880504835261358], [30718, 0.07984209866935141], [30723, 0.08076084141077373], [30729, 0.08231329571062546], [30730, 0.08980984230608574], [30734, 0.08640294325929151], [30739, 0.0783151855686935], [30744, 0.09671857700103803], [30748, 0.0841259371717624], [30750, 0.0803854505871398], [30754, 0.08751039258098703], [30761, 0.0876061213017175], [30762, 0.07928264479170313], [30777, 0.0858156587965769], [30782, 0.08053500474369336], [30785, 0.08680005167270961], [30787, 0.0838640913192557], [30794, 0.08899530076867765], [30804, 0.0908000077033463], [30812, 0.08064643082002461], [30817, 0.08419784715879593], [30821, 0.08017505342264312], [30838, 0.08697529383289511], [30849, 0.08775170795897139], [30861, 0.07753124206405838], [30868, 0.09176085114618783], [30872, 0.08130541603624186], [30890, 0.08024246288827476], [30904, 0.07928944510368591], [30907, 0.09038428318179755], [30908, 0.09089664148654959], [30917, 0.08021692114564358], [30928, 0.09366698996223617], [30931, 0.0874261325545228], [30938, 0.08809273667190097], [30945, 0.08881105684626475], [30949, 0.09097764534346839], [30955, 0.08063636793514323], [30957, 0.09199179448465912], [30967, 0.08861819658614457], [30974, 0.0783414104572132], [30978, 0.07997640044182501], [30987, 0.08728205861135455], [30988, 0.08320173929390083], [30994, 0.08405626870710026], [30997, 0.07917285403306187], [31009, 0.09128816434449494], [31019, 0.09393715466899717], [31031, 0.0863892118814406], [31039, 0.0866449651163845], [31040, 0.08070509782596998], [31041, 0.08135068116616014], [32090, 0.04220372082297226], [32101, 0.04073574473725479], [32104, 0.041889633856466574], [32112, 0.03954664240060427], [32115, 0.04074860334583154], [32116, 0.03953767523553472], [32120, 0.04088780931897665], [32130, 0.04111388148577068], [32131, 0.03997083944097134], [32132, 0.03876552619344579], [32138, 0.039820142310479825], [32148, 0.04266802065535705], [32152, 0.040790038510441363], [32156, 0.04061375589750646], [32157, 0.040353198894099225], [32163, 0.03982908667589864], [32174, 0.04154401945618198], [32181, 0.03997927134236058], [32186, 0.038292766222897276], [32187, 0.039693558925449825], [32193, 0.040057366726861596], [32197, 0.04256914967632055], [32198, 0.04030163978896253], [32204, 0.04113008450075359], [32213, 0.04050743450799862], [32218, 0.039582318497344116], [32220, 0.041806712693321084], [32224, 0.04179220881114154], [32241, 0.0402131411512891], [32249, 0.04236227235797825], [32252, 0.037611492088236095], [32256, 0.036792324921044374], [32259, 0.03939331457852718], [32261, 0.040201001425236436], [32265, 0.0404636955153391], [32270, 0.03889838989454272], [32274, 0.039792071396264], [32292, 0.040580176757628754], [32294, 0.039708499019034955], [33213, 0.037081046033859984], [33259, 0.04131047866799088], [33296, 0.03637739903923172], [33302, 0.04100703585154689], [33309, 0.037307422700313286], [33310, 0.0388197070458866], [33311, 0.041179418571789944], [33315, 0.04263356708827073], [33323, 0.03772200279758448], [33332, 0.0404645378531961], [33333, 0.04069816432497403], [33337, 0.04142284553392745], [33338, 0.03939479998757584], [33341, 0.04359577720962291], [33346, 0.04103790842646266], [33351, 0.04340422406441884], [33358, 0.041517442583390275], [33359, 0.03742755971381495], [33361, 0.04001509951776079], [33370, 0.037425352037839546], [33373, 0.036024213674160865], [33380, 0.03594653128324906], [33386, 0.037180658184750935], [33393, 0.03799816669982042], [33400, 0.0406762357525213], [33414, 0.039547858897864115], [33424, 0.040081766219388144], [33428, 0.041852212169479604], [33437, 0.03884623171296531], [33444, 0.03865820678202229], [33453, 0.042849884214415046], [33516, 0.03994147305047556], [33517, 0.04031676654320536], [33518, 0.03765037100035139], [33520, 0.03995421705524846], [33524, 0.042964068422617636], [33533, 0.039749711726232664], [33536, 0.04451423834887171], [33537, 0.04114736971816402], [33543, 0.03893953833168961], [33546, 0.04113292252968398], [33648, 0.0441179749454324], [33704, 0.03851743663597064], [33707, 0.041157295903096816], [33708, 0.03724064658799166], [33712, 0.03825338186381671], [33715, 0.04066421781927622], [33722, 0.04364234386512251], [33733, 0.03988510500746747], [33734, 0.041015833832498357], [33756, 0.041959236577762946], [33766, 0.039698853336766954], [33802, 0.042941106362399305], [33808, 0.04138322113054373], [33813, 0.04164967523448394], [33818, 0.040487428349372856], [33820, 0.03923705048909195], [33826, 0.04287542977765179], [33833, 0.04318424855239311], [34031, 0.0432774662448544], [34034, 0.04382338814434802], [34046, 0.04198315762376204], [34049, 0.039645990322374126], [34052, 0.04176563982787283], [34058, 0.04056748425293905], [34065, 0.04091156042683434], [34068, 0.04075051976280761], [34075, 0.042513241376331466], [34079, 0.03972716454990094], [34113, 0.04138588128373375], [34115, 0.04181654059145901], [34120, 0.041512831527276486], [34126, 0.04315725822312574], [34139, 0.04063934855174407], [34140, 0.04303448679985575], [34141, 0.041573954595035385], [34155, 0.04021911732463453], [34158, 0.04125980807053857], [34160, 0.04272862600884475], [34162, 0.04069155794168967]] \ No newline at end of file +[[28497, 0.054903094039247036], [29215, 0.09047455108186246], [29225, 0.08751469615063344], [29227, 0.08918766605313662], [29228, 0.08833958084932605], [29229, 0.08819503856241483], [29235, 0.08719389598066425], [29240, 0.06635004147837376], [29245, 0.05463390374945392], [29246, 0.05356047116743053], [29258, 0.053214197601916695], [29262, 0.0543368570649475], [29279, 0.0595210451786751], [29286, 0.06127668335128591], [29293, 0.05375965443633766], [29294, 0.054002998472526695], [29295, 0.053683252657023395], [29296, 0.054065435236503034], [29313, 0.053666599508913976], [29318, 0.05452537337063146], [29319, 0.0543456960948009], [29322, 0.05487326341760504], [29325, 0.054523073213713316], [29327, 0.05656199591440331], [29328, 0.05366573149419437], [29340, 0.05857008457925727], [29344, 0.061197166747998986], [29349, 0.0535293540472246], [29364, 0.05479980358210308], [29371, 0.0538471361619987], [29376, 0.06086449387728128], [29381, 0.05392456655881818], [29383, 0.05407109295641383], [29387, 0.061471533915078126], [29401, 0.05443520734688522], [29404, 0.06450141701117636], [29409, 0.05341519250916818], [29414, 0.054873918330760704], [29415, 0.059280378692316164], [29420, 0.055605213323057866], [29421, 0.05428091153865277], [29425, 0.05401923591210642], [29429, 0.05594162290887323], [29435, 0.0946961098753781], [29443, 0.08551534115523901], [29446, 0.0880315903654639], [29453, 0.08594392181124345], [29454, 0.08655110028156159], [29455, 0.08753081013268492], [29457, 0.0890355037398804], [29458, 0.09196030390502442], [29469, 0.08886734373095316], [29541, 0.08995784607495526], [29548, 0.08970944259287754], [29550, 0.08883492280472212], [29551, 0.07410987674455453], [29572, 0.07878563539607371], [29591, 0.07794697480294269], [29598, 0.079761457238947], [29609, 0.07838976741888565], [29611, 0.07735554783297585], [29621, 0.07994099667033036], [29638, 0.0801597905267139], [29644, 0.07474005299560324], [29648, 0.07546431248349791], [29652, 0.07499441069081862], [29656, 0.07820836251307085], [29657, 0.07859089024187062], [29662, 0.0738824071876207], [29665, 0.078947032632273], [29667, 0.0742199164242152], [29735, 0.07780702754493252], [29742, 0.07488491615404813], [29750, 0.0792107225094401], [29753, 0.07993598346168011], [29757, 0.07918110829797596], [29761, 0.07765848982689172], [29765, 0.07847770420312054], [29766, 0.07754553343183229], [29768, 0.0798747608845263], [29776, 0.09408150194010759], [29783, 0.08221010010040461], [29788, 0.10024669324511289], [29789, 0.0790663434725697], [29790, 0.07845117778665099], [29795, 0.08246654602186093], [29798, 0.07851051519371571], [29805, 0.08559172829132844], [29806, 0.08778184029673829], [29807, 0.07753953951061492], [29808, 0.0848436191403751], [29813, 0.08627318676788107], [29815, 0.07865791792847181], [29828, 0.07583505735689032], [29839, 0.07741774263413251], [29844, 0.08537241271606913], [29858, 0.0779438216453587], [29865, 0.09212733002094387], [29999, 0.08475756239722708], [30002, 0.09112220317976744], [30010, 0.07870454885302072], [30013, 0.07876627702254206], [30023, 0.09192219258677414], [30028, 0.0876893299098634], [30035, 0.07825964969326898], [30046, 0.09138723202176516], [30053, 0.09283536422850497], [30066, 0.08025022781328324], [30068, 0.08842531905314019], [30070, 0.09550563580067298], [30074, 0.09081675210201473], [30076, 0.07920107924185774], [30077, 0.09041668989187074], [30078, 0.09065971253065569], [30085, 0.08453566193074383], [30086, 0.08877316515655585], [30096, 0.08215703295850867], [30104, 0.08957123791898515], [30106, 0.08550644891286115], [30112, 0.08584017694279682], [30116, 0.08677475067332892], [30118, 0.08637524503020365], [30123, 0.0883655331134633], [30128, 0.07841065471698609], [30135, 0.08434849833998323], [30145, 0.09036579477698065], [30155, 0.08685930258863149], [30156, 0.08838779998155376], [30157, 0.0868225881316682], [30165, 0.08461015351792758], [30174, 0.09048895450464713], [30179, 0.09149378954886411], [30185, 0.0796579099161991], [30189, 0.08767594162785804], [30190, 0.07892189047622122], [30198, 0.09233402290100136], [30202, 0.08169808345132816], [30203, 0.0920118640824603], [30208, 0.09124542828664585], [30212, 0.09264086393938042], [30213, 0.09395285580130738], [30215, 0.08985719938778125], [30218, 0.08067887208164454], [30225, 0.08527102569495915], [30227, 0.08527034974066884], [30233, 0.07846096249836701], [30235, 0.08594024805084018], [30238, 0.08526954723961049], [30244, 0.08690788972074392], [30248, 0.08132331795206865], [30254, 0.08388812844194021], [30259, 0.08819788708306249], [30260, 0.08643007971363811], [30501, 0.09071421303313248], [30502, 0.08608944303497643], [30506, 0.07865211237903508], [30507, 0.09140561383221014], [30510, 0.08071363248262538], [30515, 0.0925595054385495], [30519, 0.09108828260290427], [30520, 0.07821873869447127], [30524, 0.07959059809009209], [30525, 0.08047743522386504], [30529, 0.08594487845783877], [30533, 0.09354796634778857], [30538, 0.08787308377335884], [30542, 0.07986217638174577], [30543, 0.08626831522293996], [30544, 0.08063563575679018], [30545, 0.08751091227904224], [30550, 0.09177063072999037], [30552, 0.08547185202358187], [30556, 0.08875155424617176], [30561, 0.0897680308316318], [30564, 0.09378692268779323], [30565, 0.07878304179835802], [30577, 0.09147028113315828], [30581, 0.08699583614456445], [30586, 0.09107200238539097], [30593, 0.07945085187899481], [30615, 0.0895152714990597], [30621, 0.0921772778521892], [30622, 0.08675590239536846], [30629, 0.09162906915719606], [30635, 0.082300478547682], [30639, 0.08561146971400413], [30640, 0.08254703380449835], [30643, 0.09120889293881], [30646, 0.08271093526834607], [30647, 0.08775998210841586], [30650, 0.08889354322797606], [30657, 0.08450784472942907], [30665, 0.08934195057551636], [30670, 0.07834804981471459], [30675, 0.08914398971563975], [30679, 0.07899887960138453], [30694, 0.08897426484825917], [30704, 0.07817568276343684], [30708, 0.07880504835261358], [30718, 0.07984209866935141], [30723, 0.08076084141077373], [30729, 0.08231329571062546], [30730, 0.08980984230608574], [30734, 0.08640294325929151], [30739, 0.0783151855686935], [30744, 0.09671857700103803], [30748, 0.0841259371717624], [30750, 0.0803854505871398], [30754, 0.08751039258098703], [30761, 0.0876061213017175], [30762, 0.07928264479170313], [30777, 0.0858156587965769], [30782, 0.08053500474369336], [30785, 0.08680005167270961], [30787, 0.0838640913192557], [30794, 0.08899530076867765], [30804, 0.0908000077033463], [30812, 0.08064643082002461], [30817, 0.08419784715879593], [30821, 0.08017505342264312], [30838, 0.08697529383289511], [30849, 0.08775170795897139], [30861, 0.07753124206405838], [30868, 0.09176085114618783], [30872, 0.08130541603624186], [30890, 0.08024246288827476], [30904, 0.07928944510368591], [30907, 0.09038428318179755], [30908, 0.09089664148654959], [30917, 0.08021692114564358], [30928, 0.09366698996223617], [30931, 0.0874261325545228], [30938, 0.08809273667190097], [30945, 0.08881105684626475], [30949, 0.09097764534346839], [30955, 0.08063636793514323], [30957, 0.09199179448465912], [30967, 0.08861819658614457], [30974, 0.0783414104572132], [30978, 0.07997640044182501], [30987, 0.08728205861135455], [30988, 0.08320173929390083], [30994, 0.08405626870710026], [30997, 0.07917285403306187], [31009, 0.09128816434449494], [31019, 0.09393715466899717], [31031, 0.0863892118814406], [31039, 0.0866449651163845], [31040, 0.08070509782596998], [31041, 0.08135068116616014], [32090, 0.04220372082297226], [32101, 0.04073574473725479], [32104, 0.041889633856466574], [32112, 0.03954664240060427], [32115, 0.04074860334583154], [32116, 0.03953767523553472], [32120, 0.04088780931897665], [32130, 0.04111388148577068], [32131, 0.03997083944097134], [32132, 0.03876552619344579], [32138, 0.039820142310479825], [32148, 0.04266802065535705], [32152, 0.040790038510441363], [32156, 0.04061375589750646], [32157, 0.040353198894099225], [32163, 0.03982908667589864], [32174, 0.04154401945618198], [32181, 0.03997927134236058], [32186, 0.038292766222897276], [32187, 0.039693558925449825], [32193, 0.040057366726861596], [32197, 0.04256914967632055], [32198, 0.04030163978896253], [32204, 0.04113008450075359], [32213, 0.04050743450799862], [32218, 0.039582318497344116], [32220, 0.041806712693321084], [32224, 0.04179220881114154], [32241, 0.0402131411512891], [32249, 0.04236227235797825], [32252, 0.037611492088236095], [32256, 0.036792324921044374], [32259, 0.03939331457852718], [32261, 0.040201001425236436], [32265, 0.0404636955153391], [32270, 0.03889838989454272], [32274, 0.039792071396264], [32292, 0.040580176757628754], [32294, 0.039708499019034955], [33213, 0.037081046033859984], [33259, 0.04131047866799088], [33296, 0.03637739903923172], [33302, 0.04100703585154689], [33309, 0.037307422700313286], [33310, 0.0388197070458866], [33311, 0.041179418571789944], [33315, 0.04263356708827073], [33323, 0.03772200279758448], [33332, 0.0404645378531961], [33333, 0.04069816432497403], [33337, 0.04142284553392745], [33338, 0.03939479998757584], [33341, 0.04359577720962291], [33346, 0.04103790842646266], [33351, 0.04340422406441884], [33358, 0.041517442583390275], [33359, 0.03742755971381495], [33361, 0.04001509951776079], [33370, 0.037425352037839546], [33373, 0.036024213674160865], [33380, 0.03594653128324906], [33386, 0.037180658184750935], [33393, 0.03799816669982042], [33400, 0.0406762357525213], [33414, 0.039547858897864115], [33424, 0.040081766219388144], [33428, 0.041852212169479604], [33437, 0.03884623171296531], [33444, 0.03865820678202229], [33453, 0.042849884214415046], [33516, 0.03994147305047556], [33517, 0.04031676654320536], [33518, 0.03765037100035139], [33520, 0.03995421705524846], [33524, 0.042964068422617636], [33533, 0.039749711726232664], [33536, 0.04451423834887171], [33537, 0.04114736971816402], [33543, 0.03893953833168961], [33546, 0.04113292252968398], [33648, 0.0441179749454324], [33704, 0.03851743663597064], [33707, 0.041157295903096816], [33708, 0.03724064658799166], [33712, 0.03825338186381671], [33715, 0.04066421781927622], [33722, 0.04364234386512251], [33733, 0.03988510500746747], [33734, 0.041015833832498357], [33756, 0.041959236577762946], [33766, 0.039698853336766954], [33802, 0.042941106362399305], [33808, 0.04138322113054373], [33813, 0.04164967523448394], [33818, 0.040487428349372856], [33820, 0.03923705048909195], [33826, 0.04287542977765179], [33833, 0.04318424855239311], [34031, 0.0432774662448544], [34034, 0.04382338814434802], [34046, 0.04198315762376204], [34049, 0.039645990322374126], [34052, 0.04176563982787283], [34058, 0.04056748425293905], [34065, 0.04091156042683434], [34068, 0.04075051976280761], [34075, 0.042513241376331466], [34079, 0.03972716454990094], [34113, 0.04138588128373375], [34115, 0.04181654059145901], [34120, 0.041512831527276486], [34126, 0.04315725822312574], [34139, 0.04063934855174407], [34140, 0.04303448679985575], [34141, 0.041573954595035385], [34155, 0.04021911732463453], [34158, 0.04125980807053857], [34160, 0.04272862600884475], [34162, 0.04069155794168967], [34164, 0.04048496563558533]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LinearRegressionBenchmark.track_test_score.json b/graphs/summary/linear_model.LinearRegressionBenchmark.track_test_score.json index ee5fd02426..935b2cda50 100644 --- a/graphs/summary/linear_model.LinearRegressionBenchmark.track_test_score.json +++ b/graphs/summary/linear_model.LinearRegressionBenchmark.track_test_score.json @@ -1 +1 @@ -[[28497, 0.3051355901880866], [29215, 0.3051444166955154], [29225, 0.30095552034179734], [29227, 0.2993674928748154], [29228, 0.31102630137112003], [29229, 0.310054266263877], [29235, 0.3054260721628789], [29240, 0.30475037832615065], [29245, 0.30825967421612727], [29246, 0.30780839510402724], [29258, 0.3070823400206157], [29262, 0.30530553803114185], [29279, 0.31155757178541976], [29286, 0.3105927601316091], [29293, 0.3174896047112276], [29294, 0.31719074935438496], [29295, 0.3062463707626025], [29296, 0.29332698670575874], [29313, 0.3172831702613257], [29318, 0.325708016941584], [29319, 0.3157659287164844], [29322, 0.31370513789094734], [29325, 0.3109709866278612], [29327, 0.3229769137284453], [29328, 0.2985030423407546], [29340, 0.3136942298800128], [29344, 0.32151040113542806], [29349, 0.30149134397616606], [29364, 0.3053270300426712], [29371, 0.30498530415786024], [29376, 0.30600271678697394], [29381, 0.30106469859639373], [29383, 0.3051452351999759], [29387, 0.30977966816807245], [29401, 0.31187978837006575], [29404, 0.30604804554292864], [29409, 0.30860574414236513], [29414, 0.31488692823237857], [29415, 0.3047070244346215], [29420, 0.3238659709134957], [29421, 0.30380744752815936], [29425, 0.31005292623706515], [29429, 0.2919036073148203], [29435, 0.3013633545496021], [29443, 0.30224179258057426], [29446, 0.3124605401315249], [29453, 0.30974485730975604], [29454, 0.31946569460165913], [29455, 0.31503887934201796], [29457, 0.31961503424454696], [29458, 0.307952492165894], [29469, 0.31625252893068895], [29541, 0.29999344660501076], [29548, 0.3023642280096055], [29550, 0.29989997156745013], [29551, 0.3110980116566392], [29572, 0.3088939765117958], [29591, 0.3072443929554082], [29598, 0.3143335628535943], [29609, 0.3088053298684264], [29611, 0.32801178354224236], [29621, 0.30153211146235026], [29638, 0.3330567906535801], [29644, 0.3030212737757196], [29648, 0.31141210242218714], [29652, 0.3040859948295301], [29656, 0.3049508987366573], [29657, 0.30909144287053497], [29662, 0.32169310096342646], [29665, 0.325108995361994], [29667, 0.30692813788094264], [29735, 0.31432222044412167], [29742, 0.30347121954139544], [29750, 0.3087926723642837], [29753, 0.29322747682489797], [29757, 0.30287759195727637], [29761, 0.31473286051637844], [29765, 0.3140304129666544], [29766, 0.3044757739935926], [29768, 0.30483097928340924], [29776, 0.30811443376493], [29783, 0.29786732268702937], [29788, 0.31649491004977304], [29789, 0.31117564367744804], [29790, 0.29970609557570027], [29795, 0.30803248736603805], [29798, 0.30851301697358013], [29805, 0.3171044425991437], [29806, 0.3159903198048293], [29807, 0.3133566018038661], [29808, 0.30945198452005596], [29813, 0.3013429885853042], [29815, 0.31147829641308045], [29828, 0.32018423942476076], [29839, 0.309629598093665], [29844, 0.30827831618296386], [29858, 0.30698495312425605], [29865, 0.3143074933694528], [29999, 0.30974719664374284], [30002, 0.3038151227830538], [30010, 0.30555323110856175], [30013, 0.3076673518640553], [30023, 0.31330163903624286], [30028, 0.30922883463185696], [30035, 0.3148176495011402], [30046, 0.30560889528238194], [30053, 0.31255765533680663], [30066, 0.295555763659889], [30068, 0.3132296764978417], [30070, 0.3063811771352634], [30074, 0.30467834109229514], [30076, 0.3120336264990119], [30077, 0.2962859130748658], [30078, 0.3082006187851212], [30085, 0.31205182187820507], [30086, 0.310837061099105], [30096, 0.3128968994754925], [30104, 0.304947885989986], [30106, 0.29962948176011533], [30112, 0.30240994305247276], [30116, 0.3004193267189336], [30118, 0.3070351948573802], [30123, 0.2915936788039259], [30128, 0.3099684243615256], [30135, 0.30093343704394165], [30145, 0.32704660419375836], [30155, 0.30685862170562966], [30156, 0.3063479656400891], [30157, 0.3174303050030959], [30165, 0.3101332829661087], [30174, 0.31913964956838], [30179, 0.31615002754625743], [30185, 0.30371513457173976], [30189, 0.3058489304414809], [30190, 0.2985904467791236], [30198, 0.3145977717500085], [30202, 0.30524380470609475], [30203, 0.31327798116211236], [30208, 0.30823909263589033], [30212, 0.30786178900033073], [30213, 0.31676110634338894], [30215, 0.308663791976498], [30218, 0.314235453417157], [30225, 0.30617754174697936], [30227, 0.3211682777375455], [30233, 0.3078555880724531], [30235, 0.31271506354782214], [30238, 0.3070076084129068], [30244, 0.31479710871023214], [30248, 0.30957382366684333], [30254, 0.30643635019993487], [30259, 0.31093823986123587], [30260, 0.3127561231835987], [30501, 0.3273567342410305], [30502, 0.3196434937829604], [30506, 0.3193882978158203], [30507, 0.31642598585793336], [30510, 0.308363772142338], [30515, 0.3006593310245183], [30519, 0.30168390525768635], [30520, 0.3143796793982464], [30524, 0.30856016187338314], [30525, 0.29737148491949356], [30529, 0.3017857172133572], [30533, 0.3168468282493152], [30538, 0.30115922747752244], [30542, 0.30725760795749024], [30543, 0.3040457349072022], [30544, 0.3204923186352474], [30545, 0.31046172565779034], [30550, 0.30103184989179593], [30552, 0.29759230536844994], [30556, 0.31468337369732724], [30561, 0.30822581144821304], [30564, 0.3129854176067525], [30565, 0.30358362116234106], [30577, 0.30173322983049816], [30581, 0.3076497056680437], [30586, 0.3071251115846661], [30593, 0.2994918773811261], [30615, 0.3149488141297496], [30621, 0.3145649324815838], [30622, 0.3201175980179841], [30629, 0.30931275045352363], [30635, 0.3044521197570201], [30639, 0.2950130235655144], [30640, 0.3047013475029213], [30643, 0.31032068427910225], [30646, 0.29780682653332824], [30647, 0.3041669798412786], [30650, 0.3114652970462574], [30657, 0.30569946484587207], [30665, 0.30986850826685963], [30670, 0.3001077093216415], [30675, 0.32321926348273494], [30679, 0.3147373546403953], [30694, 0.31253890596683215], [30704, 0.3187348992249539], [30708, 0.3095708053539685], [30718, 0.31248760502255757], [30723, 0.2998349921088314], [30729, 0.31465991720903136], [30730, 0.3072868187453572], [30734, 0.30845409988948425], [30739, 0.3022442243001142], [30744, 0.3151800865970288], [30748, 0.3096151577383061], [30750, 0.31530582771271454], [30754, 0.30256797634216587], [30761, 0.3008359854085618], [30762, 0.30919457484532614], [30777, 0.30766275462853376], [30782, 0.3039857130983988], [30785, 0.3138092942860077], [30787, 0.3037960987735038], [30794, 0.30576120707793153], [30804, 0.30666093400232985], [30812, 0.31166959911989606], [30817, 0.2907284793486503], [30821, 0.3077563851836773], [30838, 0.32376361555417876], [30849, 0.29818976015240883], [30861, 0.3146355080345594], [30868, 0.31160872836688663], [30872, 0.31469787469260746], [30890, 0.2984554526177901], [30904, 0.29963650616196136], [30907, 0.28544196839952807], [30908, 0.3128894919523878], [30917, 0.3065142375299122], [30928, 0.3038756449580923], [30931, 0.3107060402949911], [30938, 0.32205272251469835], [30945, 0.31124378962658317], [30949, 0.29974945269309183], [30955, 0.2916770648756224], [30957, 0.3101853492176601], [30967, 0.3100704213235983], [30974, 0.3161717551661771], [30978, 0.29753974348978407], [30987, 0.3096384527735155], [30988, 0.310033378415511], [30994, 0.3031369889545075], [30997, 0.3137365494111708], [31009, 0.2923545321179314], [31019, 0.3081130795557638], [31031, 0.30652272785752877], [31039, 0.3155222453446974], [31040, 0.3023003534677022], [31041, 0.31203455885197356], [32090, 0.2999804836748685], [32101, 0.31178889751588806], [32104, 0.3133829372718549], [32112, 0.31214226690182506], [32115, 0.30930533757092815], [32116, 0.3167011633741555], [32120, 0.311788898578478], [32130, 0.30396236741112176], [32131, 0.3198988562123781], [32132, 0.3119911167772262], [32138, 0.3013609276418304], [32148, 0.2986508556558232], [32152, 0.3030932249620025], [32156, 0.3018411310558053], [32157, 0.3102755027404438], [32163, 0.3068002435821841], [32174, 0.3132309357889178], [32181, 0.3135621568219189], [32186, 0.30285791601719686], [32187, 0.29750903775711285], [32193, 0.30895171903464186], [32197, 0.3110997405235142], [32198, 0.30567918648736], [32204, 0.30940589654663947], [32213, 0.2940283391925977], [32218, 0.3206778041136635], [32220, 0.3049105822325592], [32224, 0.3087464915901611], [32241, 0.30827750851510954], [32249, 0.3155844624907498], [32252, 0.3021638022502738], [32256, 0.30904075853369906], [32259, 0.3018875056005814], [32261, 0.3158798037622359], [32265, 0.300646434008773], [32270, 0.3086541285732064], [32274, 0.30499161783550544], [32292, 0.31337126597448006], [32294, 0.3019623460410213], [33213, 0.30584507286222384], [33259, 0.31582916924224597], [33296, 0.3124594206093537], [33302, 0.30365794355516473], [33309, 0.30757261575016454], [33310, 0.3031934665440438], [33311, 0.3092853541013022], [33315, 0.29721794071387453], [33323, 0.3128189166377049], [33332, 0.31454512536062795], [33333, 0.3214487041627265], [33337, 0.3069004607335193], [33338, 0.3046337138674848], [33341, 0.31165627703596094], [33346, 0.3155785329561254], [33351, 0.3178727177773852], [33358, 0.31233216689665216], [33359, 0.3069893577571297], [33361, 0.30059388645937235], [33370, 0.3070658941353236], [33373, 0.3074435039458919], [33380, 0.31806426465416565], [33386, 0.31357582076840357], [33393, 0.32351908165235727], [33400, 0.31210849692493864], [33414, 0.294784876548301], [33424, 0.3047407808964766], [33428, 0.30808519482205576], [33437, 0.31301197483287996], [33444, 0.3093822373924508], [33453, 0.30349392231198535], [33516, 0.3131426826297445], [33517, 0.3075444005453756], [33518, 0.31184860128578495], [33520, 0.302398986426238], [33524, 0.3219795702424703], [33533, 0.31355097943878124], [33536, 0.3150901745598002], [33537, 0.3113521285508053], [33543, 0.30869681346743877], [33546, 0.3089979240558196], [33648, 0.31229449497342343], [33704, 0.310845067848803], [33707, 0.2955056728135459], [33708, 0.3092963512026977], [33712, 0.3152998569544796], [33715, 0.30096642451047034], [33722, 0.3094182864494452], [33733, 0.3058657453515335], [33734, 0.3099647482615445], [33756, 0.30876383389675094], [33766, 0.3111900056350314], [33802, 0.3181689065507667], [33808, 0.3130012461145359], [33813, 0.3094706731999054], [33818, 0.3166661763925684], [33820, 0.3129432915053211], [33826, 0.30237698810425123], [33833, 0.3098360375457582], [34031, 0.30409867635605514], [34034, 0.3007484786245174], [34046, 0.30803494977706314], [34049, 0.30865183856606104], [34052, 0.306019088219359], [34058, 0.32039825634702024], [34065, 0.3037752282706807], [34068, 0.29911137269403143], [34075, 0.3106275423887559], [34079, 0.30465200710165663], [34113, 0.31260917237427477], [34115, 0.3155184755411691], [34120, 0.30747146379701434], [34126, 0.2996752536377471], [34139, 0.30504060419066287], [34140, 0.3122143711238971], [34141, 0.30734534279659875], [34155, 0.30977056570577755], [34158, 0.31284656122860904], [34160, 0.310956860087073], [34162, 0.30931990613868254]] \ No newline at end of file +[[28497, 0.3051355901880866], [29215, 0.3051444166955154], [29225, 0.30095552034179734], [29227, 0.2993674928748154], [29228, 0.31102630137112003], [29229, 0.310054266263877], [29235, 0.3054260721628789], [29240, 0.30475037832615065], [29245, 0.30825967421612727], [29246, 0.30780839510402724], [29258, 0.3070823400206157], [29262, 0.30530553803114185], [29279, 0.31155757178541976], [29286, 0.3105927601316091], [29293, 0.3174896047112276], [29294, 0.31719074935438496], [29295, 0.3062463707626025], [29296, 0.29332698670575874], [29313, 0.3172831702613257], [29318, 0.325708016941584], [29319, 0.3157659287164844], [29322, 0.31370513789094734], [29325, 0.3109709866278612], [29327, 0.3229769137284453], [29328, 0.2985030423407546], [29340, 0.3136942298800128], [29344, 0.32151040113542806], [29349, 0.30149134397616606], [29364, 0.3053270300426712], [29371, 0.30498530415786024], [29376, 0.30600271678697394], [29381, 0.30106469859639373], [29383, 0.3051452351999759], [29387, 0.30977966816807245], [29401, 0.31187978837006575], [29404, 0.30604804554292864], [29409, 0.30860574414236513], [29414, 0.31488692823237857], [29415, 0.3047070244346215], [29420, 0.3238659709134957], [29421, 0.30380744752815936], [29425, 0.31005292623706515], [29429, 0.2919036073148203], [29435, 0.3013633545496021], [29443, 0.30224179258057426], [29446, 0.3124605401315249], [29453, 0.30974485730975604], [29454, 0.31946569460165913], [29455, 0.31503887934201796], [29457, 0.31961503424454696], [29458, 0.307952492165894], [29469, 0.31625252893068895], [29541, 0.29999344660501076], [29548, 0.3023642280096055], [29550, 0.29989997156745013], [29551, 0.3110980116566392], [29572, 0.3088939765117958], [29591, 0.3072443929554082], [29598, 0.3143335628535943], [29609, 0.3088053298684264], [29611, 0.32801178354224236], [29621, 0.30153211146235026], [29638, 0.3330567906535801], [29644, 0.3030212737757196], [29648, 0.31141210242218714], [29652, 0.3040859948295301], [29656, 0.3049508987366573], [29657, 0.30909144287053497], [29662, 0.32169310096342646], [29665, 0.325108995361994], [29667, 0.30692813788094264], [29735, 0.31432222044412167], [29742, 0.30347121954139544], [29750, 0.3087926723642837], [29753, 0.29322747682489797], [29757, 0.30287759195727637], [29761, 0.31473286051637844], [29765, 0.3140304129666544], [29766, 0.3044757739935926], [29768, 0.30483097928340924], [29776, 0.30811443376493], [29783, 0.29786732268702937], [29788, 0.31649491004977304], [29789, 0.31117564367744804], [29790, 0.29970609557570027], [29795, 0.30803248736603805], [29798, 0.30851301697358013], [29805, 0.3171044425991437], [29806, 0.3159903198048293], [29807, 0.3133566018038661], [29808, 0.30945198452005596], [29813, 0.3013429885853042], [29815, 0.31147829641308045], [29828, 0.32018423942476076], [29839, 0.309629598093665], [29844, 0.30827831618296386], [29858, 0.30698495312425605], [29865, 0.3143074933694528], [29999, 0.30974719664374284], [30002, 0.3038151227830538], [30010, 0.30555323110856175], [30013, 0.3076673518640553], [30023, 0.31330163903624286], [30028, 0.30922883463185696], [30035, 0.3148176495011402], [30046, 0.30560889528238194], [30053, 0.31255765533680663], [30066, 0.295555763659889], [30068, 0.3132296764978417], [30070, 0.3063811771352634], [30074, 0.30467834109229514], [30076, 0.3120336264990119], [30077, 0.2962859130748658], [30078, 0.3082006187851212], [30085, 0.31205182187820507], [30086, 0.310837061099105], [30096, 0.3128968994754925], [30104, 0.304947885989986], [30106, 0.29962948176011533], [30112, 0.30240994305247276], [30116, 0.3004193267189336], [30118, 0.3070351948573802], [30123, 0.2915936788039259], [30128, 0.3099684243615256], [30135, 0.30093343704394165], [30145, 0.32704660419375836], [30155, 0.30685862170562966], [30156, 0.3063479656400891], [30157, 0.3174303050030959], [30165, 0.3101332829661087], [30174, 0.31913964956838], [30179, 0.31615002754625743], [30185, 0.30371513457173976], [30189, 0.3058489304414809], [30190, 0.2985904467791236], [30198, 0.3145977717500085], [30202, 0.30524380470609475], [30203, 0.31327798116211236], [30208, 0.30823909263589033], [30212, 0.30786178900033073], [30213, 0.31676110634338894], [30215, 0.308663791976498], [30218, 0.314235453417157], [30225, 0.30617754174697936], [30227, 0.3211682777375455], [30233, 0.3078555880724531], [30235, 0.31271506354782214], [30238, 0.3070076084129068], [30244, 0.31479710871023214], [30248, 0.30957382366684333], [30254, 0.30643635019993487], [30259, 0.31093823986123587], [30260, 0.3127561231835987], [30501, 0.3273567342410305], [30502, 0.3196434937829604], [30506, 0.3193882978158203], [30507, 0.31642598585793336], [30510, 0.308363772142338], [30515, 0.3006593310245183], [30519, 0.30168390525768635], [30520, 0.3143796793982464], [30524, 0.30856016187338314], [30525, 0.29737148491949356], [30529, 0.3017857172133572], [30533, 0.3168468282493152], [30538, 0.30115922747752244], [30542, 0.30725760795749024], [30543, 0.3040457349072022], [30544, 0.3204923186352474], [30545, 0.31046172565779034], [30550, 0.30103184989179593], [30552, 0.29759230536844994], [30556, 0.31468337369732724], [30561, 0.30822581144821304], [30564, 0.3129854176067525], [30565, 0.30358362116234106], [30577, 0.30173322983049816], [30581, 0.3076497056680437], [30586, 0.3071251115846661], [30593, 0.2994918773811261], [30615, 0.3149488141297496], [30621, 0.3145649324815838], [30622, 0.3201175980179841], [30629, 0.30931275045352363], [30635, 0.3044521197570201], [30639, 0.2950130235655144], [30640, 0.3047013475029213], [30643, 0.31032068427910225], [30646, 0.29780682653332824], [30647, 0.3041669798412786], [30650, 0.3114652970462574], [30657, 0.30569946484587207], [30665, 0.30986850826685963], [30670, 0.3001077093216415], [30675, 0.32321926348273494], [30679, 0.3147373546403953], [30694, 0.31253890596683215], [30704, 0.3187348992249539], [30708, 0.3095708053539685], [30718, 0.31248760502255757], [30723, 0.2998349921088314], [30729, 0.31465991720903136], [30730, 0.3072868187453572], [30734, 0.30845409988948425], [30739, 0.3022442243001142], [30744, 0.3151800865970288], [30748, 0.3096151577383061], [30750, 0.31530582771271454], [30754, 0.30256797634216587], [30761, 0.3008359854085618], [30762, 0.30919457484532614], [30777, 0.30766275462853376], [30782, 0.3039857130983988], [30785, 0.3138092942860077], [30787, 0.3037960987735038], [30794, 0.30576120707793153], [30804, 0.30666093400232985], [30812, 0.31166959911989606], [30817, 0.2907284793486503], [30821, 0.3077563851836773], [30838, 0.32376361555417876], [30849, 0.29818976015240883], [30861, 0.3146355080345594], [30868, 0.31160872836688663], [30872, 0.31469787469260746], [30890, 0.2984554526177901], [30904, 0.29963650616196136], [30907, 0.28544196839952807], [30908, 0.3128894919523878], [30917, 0.3065142375299122], [30928, 0.3038756449580923], [30931, 0.3107060402949911], [30938, 0.32205272251469835], [30945, 0.31124378962658317], [30949, 0.29974945269309183], [30955, 0.2916770648756224], [30957, 0.3101853492176601], [30967, 0.3100704213235983], [30974, 0.3161717551661771], [30978, 0.29753974348978407], [30987, 0.3096384527735155], [30988, 0.310033378415511], [30994, 0.3031369889545075], [30997, 0.3137365494111708], [31009, 0.2923545321179314], [31019, 0.3081130795557638], [31031, 0.30652272785752877], [31039, 0.3155222453446974], [31040, 0.3023003534677022], [31041, 0.31203455885197356], [32090, 0.2999804836748685], [32101, 0.31178889751588806], [32104, 0.3133829372718549], [32112, 0.31214226690182506], [32115, 0.30930533757092815], [32116, 0.3167011633741555], [32120, 0.311788898578478], [32130, 0.30396236741112176], [32131, 0.3198988562123781], [32132, 0.3119911167772262], [32138, 0.3013609276418304], [32148, 0.2986508556558232], [32152, 0.3030932249620025], [32156, 0.3018411310558053], [32157, 0.3102755027404438], [32163, 0.3068002435821841], [32174, 0.3132309357889178], [32181, 0.3135621568219189], [32186, 0.30285791601719686], [32187, 0.29750903775711285], [32193, 0.30895171903464186], [32197, 0.3110997405235142], [32198, 0.30567918648736], [32204, 0.30940589654663947], [32213, 0.2940283391925977], [32218, 0.3206778041136635], [32220, 0.3049105822325592], [32224, 0.3087464915901611], [32241, 0.30827750851510954], [32249, 0.3155844624907498], [32252, 0.3021638022502738], [32256, 0.30904075853369906], [32259, 0.3018875056005814], [32261, 0.3158798037622359], [32265, 0.300646434008773], [32270, 0.3086541285732064], [32274, 0.30499161783550544], [32292, 0.31337126597448006], [32294, 0.3019623460410213], [33213, 0.30584507286222384], [33259, 0.31582916924224597], [33296, 0.3124594206093537], [33302, 0.30365794355516473], [33309, 0.30757261575016454], [33310, 0.3031934665440438], [33311, 0.3092853541013022], [33315, 0.29721794071387453], [33323, 0.3128189166377049], [33332, 0.31454512536062795], [33333, 0.3214487041627265], [33337, 0.3069004607335193], [33338, 0.3046337138674848], [33341, 0.31165627703596094], [33346, 0.3155785329561254], [33351, 0.3178727177773852], [33358, 0.31233216689665216], [33359, 0.3069893577571297], [33361, 0.30059388645937235], [33370, 0.3070658941353236], [33373, 0.3074435039458919], [33380, 0.31806426465416565], [33386, 0.31357582076840357], [33393, 0.32351908165235727], [33400, 0.31210849692493864], [33414, 0.294784876548301], [33424, 0.3047407808964766], [33428, 0.30808519482205576], [33437, 0.31301197483287996], [33444, 0.3093822373924508], [33453, 0.30349392231198535], [33516, 0.3131426826297445], [33517, 0.3075444005453756], [33518, 0.31184860128578495], [33520, 0.302398986426238], [33524, 0.3219795702424703], [33533, 0.31355097943878124], [33536, 0.3150901745598002], [33537, 0.3113521285508053], [33543, 0.30869681346743877], [33546, 0.3089979240558196], [33648, 0.31229449497342343], [33704, 0.310845067848803], [33707, 0.2955056728135459], [33708, 0.3092963512026977], [33712, 0.3152998569544796], [33715, 0.30096642451047034], [33722, 0.3094182864494452], [33733, 0.3058657453515335], [33734, 0.3099647482615445], [33756, 0.30876383389675094], [33766, 0.3111900056350314], [33802, 0.3181689065507667], [33808, 0.3130012461145359], [33813, 0.3094706731999054], [33818, 0.3166661763925684], [33820, 0.3129432915053211], [33826, 0.30237698810425123], [33833, 0.3098360375457582], [34031, 0.30409867635605514], [34034, 0.3007484786245174], [34046, 0.30803494977706314], [34049, 0.30865183856606104], [34052, 0.306019088219359], [34058, 0.32039825634702024], [34065, 0.3037752282706807], [34068, 0.29911137269403143], [34075, 0.3106275423887559], [34079, 0.30465200710165663], [34113, 0.31260917237427477], [34115, 0.3155184755411691], [34120, 0.30747146379701434], [34126, 0.2996752536377471], [34139, 0.30504060419066287], [34140, 0.3122143711238971], [34141, 0.30734534279659875], [34155, 0.30977056570577755], [34158, 0.31284656122860904], [34160, 0.310956860087073], [34162, 0.30931990613868254], [34164, 0.31279970802663487]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LinearRegressionBenchmark.track_train_score.json b/graphs/summary/linear_model.LinearRegressionBenchmark.track_train_score.json index daeaa380a6..f1c9da15a7 100644 --- a/graphs/summary/linear_model.LinearRegressionBenchmark.track_train_score.json +++ b/graphs/summary/linear_model.LinearRegressionBenchmark.track_train_score.json @@ -1 +1 @@ -[[28497, 0.9631212253681894], [29215, 0.9631212253789369], [29225, 0.9631212253789471], [29227, 0.9631212253789422], [29228, 0.9631212253789463], [29229, 0.9631212253789422], [29235, 0.963121225378954], [29240, 0.963121225357009], [29245, 0.9631212253570125], [29246, 0.9631212253570146], [29258, 0.9631212253570104], [29262, 0.9631212253570113], [29279, 0.9631212253570085], [29286, 0.9631212253570154], [29293, 0.9631212253570111], [29294, 0.9631212253570129], [29295, 0.9631212253570133], [29296, 0.9631212253570076], [29313, 0.9631212253570065], [29318, 0.9631212253570127], [29319, 0.9631212253570111], [29322, 0.9631212253570091], [29325, 0.9631212253570136], [29327, 0.9631212253570088], [29328, 0.9631212253570113], [29340, 0.9631212253570076], [29344, 0.9631212253570124], [29349, 0.9631212253570094], [29364, 0.9631212253570098], [29371, 0.9631212253570083], [29376, 0.9631212253570156], [29381, 0.9631212253570145], [29383, 0.9631212253570124], [29387, 0.9631212253570146], [29401, 0.9631212253570134], [29404, 0.963121225357012], [29409, 0.9631212253570117], [29414, 0.9631212253570053], [29415, 0.9631212253570138], [29420, 0.9631212253570105], [29421, 0.9631212253570086], [29425, 0.9631212253570132], [29429, 0.9631212253570102], [29435, 0.9631212253789406], [29443, 0.9631212253789445], [29446, 0.963121225378947], [29453, 0.9631212253789411], [29454, 0.963121225378954], [29455, 0.9631212253789534], [29457, 0.9631212253789464], [29458, 0.9631212253789466], [29469, 0.9631212253789426], [29541, 0.9631212253789403], [29548, 0.9631212253789438], [29550, 0.9631212253789473], [29551, 0.9631212253789404], [29572, 0.9631212253789475], [29591, 0.9631212253789468], [29598, 0.9631212253789497], [29609, 0.9631212253789476], [29611, 0.963121225378944], [29621, 0.9631212253789458], [29638, 0.9631212253789472], [29644, 0.9631212253789444], [29648, 0.963121225378945], [29652, 0.963121225378947], [29656, 0.9631212253789478], [29657, 0.963121225378944], [29662, 0.9631212253789422], [29665, 0.963121225378949], [29667, 0.9631212253789467], [29735, 0.9631212253789418], [29742, 0.9631212253789438], [29750, 0.963121225378947], [29753, 0.963121225378949], [29757, 0.9631212253789486], [29761, 0.9631212253789478], [29765, 0.9631212253789467], [29766, 0.9631212253789527], [29768, 0.9631212253789507], [29776, 0.9631212253789485], [29783, 0.9631212253789431], [29788, 0.9631212253789502], [29789, 0.9631212253789467], [29790, 0.9631212253789421], [29795, 0.9631212253789458], [29798, 0.9631212253789451], [29805, 0.9631212253789433], [29806, 0.9631212253789417], [29807, 0.9631212253789468], [29808, 0.9631212253789454], [29813, 0.9631212253789462], [29815, 0.9631212253789435], [29828, 0.9631212253789501], [29839, 0.9631212253789434], [29844, 0.9631212253789468], [29858, 0.9631212253789504], [29865, 0.9631212253789426], [29999, 0.9631212253789512], [30002, 0.9631212253789446], [30010, 0.9631212253789462], [30013, 0.9631212253789463], [30023, 0.9631212253789413], [30028, 0.9631212253789502], [30035, 0.9631212253971996], [30046, 0.9631212253972113], [30053, 0.9631212253972096], [30066, 0.9631212253972016], [30068, 0.9631212253972035], [30070, 0.9631212253972052], [30074, 0.9631212253972085], [30076, 0.9631212253972026], [30077, 0.9631212253971992], [30078, 0.963121225397206], [30085, 0.9631212253972079], [30086, 0.9631212253972019], [30096, 0.9631212253972005], [30104, 0.9631212253972077], [30106, 0.9631212253972012], [30112, 0.9631212253972065], [30116, 0.9631212253972015], [30118, 0.9631212253971975], [30123, 0.963121225397201], [30128, 0.9631212253971979], [30135, 0.9631212253972065], [30145, 0.9631212253972015], [30155, 0.9631212253972036], [30156, 0.9631212253972045], [30157, 0.9631212253972018], [30165, 0.9631212253972052], [30174, 0.9631212253972048], [30179, 0.9631212253972021], [30185, 0.963121225397204], [30189, 0.9631212253972103], [30190, 0.9631212253972048], [30198, 0.9631212253972002], [30202, 0.9631212253971985], [30203, 0.9631212253972082], [30208, 0.9631212253972024], [30212, 0.9631212253972045], [30213, 0.9631212253972036], [30215, 0.9631212253971967], [30218, 0.9631212253972081], [30225, 0.9631212253972026], [30227, 0.9631212253972012], [30233, 0.9631212253972024], [30235, 0.9631212253972036], [30238, 0.9631212253972011], [30244, 0.9631212253972024], [30248, 0.9631212253972017], [30254, 0.9631212253971991], [30259, 0.963121225397203], [30260, 0.9631212253972055], [30501, 0.9631212253972047], [30502, 0.9631212253972009], [30506, 0.9631212253971988], [30507, 0.9631212253972079], [30510, 0.9631212253971989], [30515, 0.9631212253972055], [30519, 0.9631212253972031], [30520, 0.9631212253972027], [30524, 0.9631212253972068], [30525, 0.9631212253972049], [30529, 0.9631212253972037], [30533, 0.9631212253972027], [30538, 0.9631212253972034], [30542, 0.963121225397203], [30543, 0.963121225397199], [30544, 0.9631212253972085], [30545, 0.9631212253972031], [30550, 0.9631212253972047], [30552, 0.9631212253972029], [30556, 0.963121225397199], [30561, 0.9631212253972085], [30564, 0.9631212253972022], [30565, 0.9631212253972032], [30577, 0.9631212253972055], [30581, 0.9631212253972017], [30586, 0.9631212253972025], [30593, 0.9631212253972057], [30615, 0.9631212253971998], [30621, 0.9631212253972042], [30622, 0.9631212253972031], [30629, 0.9631212253972136], [30635, 0.9631212253971992], [30639, 0.9631212253972041], [30640, 0.9631212253972058], [30643, 0.9631212253972047], [30646, 0.9631212253972029], [30647, 0.9631212253972075], [30650, 0.9631212253972045], [30657, 0.963121225397208], [30665, 0.963121225397207], [30670, 0.9631212253972059], [30675, 0.9631212253972032], [30679, 0.9631212253972026], [30694, 0.963121225397201], [30704, 0.9631212253972026], [30708, 0.9631212253971998], [30718, 0.9631212253972065], [30723, 0.9631212253972038], [30729, 0.9631212253972092], [30730, 0.9631212253972001], [30734, 0.9631212253972019], [30739, 0.9631212253972045], [30744, 0.963121225397207], [30748, 0.9631212253972057], [30750, 0.9631212253972045], [30754, 0.9631212253972027], [30761, 0.963121225397206], [30762, 0.9631212253972], [30777, 0.963121225397202], [30782, 0.9631212253972006], [30785, 0.9631212253972004], [30787, 0.9631212253971975], [30794, 0.963121225397203], [30804, 0.9631212253972002], [30812, 0.9631212253972089], [30817, 0.9631212253972053], [30821, 0.9631212253972028], [30838, 0.9631212253972032], [30849, 0.9631212253972058], [30861, 0.9631212253972034], [30868, 0.9631212253972026], [30872, 0.9631212253972032], [30890, 0.9631212253972052], [30904, 0.9631212253972018], [30907, 0.9631212253972044], [30908, 0.9631212253971992], [30917, 0.9631212253971996], [30928, 0.9631212253972036], [30931, 0.9631212253972024], [30938, 0.9631212253972027], [30945, 0.9631212253972056], [30949, 0.9631212253972008], [30955, 0.9631212253972073], [30957, 0.9631212253972008], [30967, 0.9631212253972009], [30974, 0.9631212253972092], [30978, 0.9631212253972031], [30987, 0.9631212253972006], [30988, 0.9631212253972028], [30994, 0.963121225397203], [30997, 0.9631212253972018], [31009, 0.963121225397203], [31019, 0.9631212253971978], [31031, 0.9631212253972032], [31039, 0.9631212253971939], [31040, 0.9631212253972035], [31041, 0.9631212253972075], [32090, 0.963121225397093], [32101, 0.9631212253971067], [32104, 0.9631212253970902], [32112, 0.9631212253970965], [32115, 0.9631212253970954], [32116, 0.9631212253971011], [32120, 0.9631212253971029], [32130, 0.9631212253970911], [32131, 0.963121225397102], [32132, 0.963121225397097], [32138, 0.9631212253970984], [32148, 0.963121225397088], [32152, 0.9631212253970836], [32156, 0.9631212253970962], [32157, 0.9631212253971063], [32163, 0.9631212253971002], [32174, 0.9631212253970923], [32181, 0.963121225397091], [32186, 0.963121225397085], [32187, 0.9631212253971017], [32193, 0.9631212253970907], [32197, 0.9631212253970893], [32198, 0.9631212253955468], [32204, 0.9631212253955649], [32213, 0.9631212253955671], [32218, 0.9631212253955285], [32220, 0.9631212253955751], [32224, 0.9631212253955214], [32241, 0.9631212253955416], [32249, 0.963121225395584], [32252, 0.9631212253955748], [32256, 0.9631212253955677], [32259, 0.9631212253955815], [32261, 0.9631212253956076], [32265, 0.9631212253955163], [32270, 0.9631212253955324], [32274, 0.9631212253955425], [32292, 0.9631212253955405], [32294, 0.9631212253955945], [33213, 0.9631212253742845], [33259, 0.9631212253742315], [33296, 0.9631212253742557], [33302, 0.9631212253742629], [33309, 0.9631212253742331], [33310, 0.9631212253742502], [33311, 0.9631212253742896], [33315, 0.9631212253742586], [33323, 0.9631212253742409], [33332, 0.9631212253743038], [33333, 0.9631212253743031], [33337, 0.9631212253742627], [33338, 0.9631212254053271], [33341, 0.9631212254053533], [33346, 0.9631212254053401], [33351, 0.9631212254053942], [33358, 0.9631212254053854], [33359, 0.9631212254053234], [33361, 0.963121225405373], [33370, 0.9631212254053413], [33373, 0.9631212254053546], [33380, 0.963121225405347], [33386, 0.9631212254053455], [33393, 0.9631212254053285], [33400, 0.9631212254053807], [33414, 0.9631212254053206], [33424, 0.9631212254053354], [33428, 0.9631212254054324], [33437, 0.9631212254053421], [33444, 0.9631212254053994], [33453, 0.9631212254054288], [33516, 0.9631212254053877], [33517, 0.963121225405414], [33518, 0.9631212254053314], [33520, 0.9631212254053677], [33524, 0.9631212254053543], [33533, 0.9631212254053301], [33536, 0.9631212254053355], [33537, 0.9631212254053789], [33543, 0.9631212254053397], [33546, 0.9631212254053765], [33648, 0.9631212254053672], [33704, 0.9631212254054043], [33707, 0.963121225405337], [33708, 0.9631212254053892], [33712, 0.9631212254053686], [33715, 0.9631212254053715], [33722, 0.9631212254053942], [33733, 0.9631212254053809], [33734, 0.9631212254053534], [33756, 0.963121225405382], [33766, 0.9631212254053731], [33802, 0.9631212254053069], [33808, 0.9631212254053388], [33813, 0.9631212254053405], [33818, 0.9631212254053965], [33820, 0.9631212254053236], [33826, 0.9631212254053905], [33833, 0.963121225405408], [34031, 0.9631212254052994], [34034, 0.9631212254053922], [34046, 0.9631212254053373], [34049, 0.9631212254053441], [34052, 0.9631212254053673], [34058, 0.9631212254053123], [34065, 0.9631212254053426], [34068, 0.9631212254053567], [34075, 0.96312122540533], [34079, 0.9631212254053721], [34113, 0.9631212254053191], [34115, 0.9631212254054008], [34120, 0.9631212254053703], [34126, 0.9631212254053522], [34139, 0.9631212254054209], [34140, 0.96312122540532], [34141, 0.9631212254053789], [34155, 0.9631212254053493], [34158, 0.9631212254053393], [34160, 0.963121225405348], [34162, 0.9631212254054097]] \ No newline at end of file +[[28497, 0.9631212253681894], [29215, 0.9631212253789369], [29225, 0.9631212253789471], [29227, 0.9631212253789422], [29228, 0.9631212253789463], [29229, 0.9631212253789422], [29235, 0.963121225378954], [29240, 0.963121225357009], [29245, 0.9631212253570125], [29246, 0.9631212253570146], [29258, 0.9631212253570104], [29262, 0.9631212253570113], [29279, 0.9631212253570085], [29286, 0.9631212253570154], [29293, 0.9631212253570111], [29294, 0.9631212253570129], [29295, 0.9631212253570133], [29296, 0.9631212253570076], [29313, 0.9631212253570065], [29318, 0.9631212253570127], [29319, 0.9631212253570111], [29322, 0.9631212253570091], [29325, 0.9631212253570136], [29327, 0.9631212253570088], [29328, 0.9631212253570113], [29340, 0.9631212253570076], [29344, 0.9631212253570124], [29349, 0.9631212253570094], [29364, 0.9631212253570098], [29371, 0.9631212253570083], [29376, 0.9631212253570156], [29381, 0.9631212253570145], [29383, 0.9631212253570124], [29387, 0.9631212253570146], [29401, 0.9631212253570134], [29404, 0.963121225357012], [29409, 0.9631212253570117], [29414, 0.9631212253570053], [29415, 0.9631212253570138], [29420, 0.9631212253570105], [29421, 0.9631212253570086], [29425, 0.9631212253570132], [29429, 0.9631212253570102], [29435, 0.9631212253789406], [29443, 0.9631212253789445], [29446, 0.963121225378947], [29453, 0.9631212253789411], [29454, 0.963121225378954], [29455, 0.9631212253789534], [29457, 0.9631212253789464], [29458, 0.9631212253789466], [29469, 0.9631212253789426], [29541, 0.9631212253789403], [29548, 0.9631212253789438], [29550, 0.9631212253789473], [29551, 0.9631212253789404], [29572, 0.9631212253789475], [29591, 0.9631212253789468], [29598, 0.9631212253789497], [29609, 0.9631212253789476], [29611, 0.963121225378944], [29621, 0.9631212253789458], [29638, 0.9631212253789472], [29644, 0.9631212253789444], [29648, 0.963121225378945], [29652, 0.963121225378947], [29656, 0.9631212253789478], [29657, 0.963121225378944], [29662, 0.9631212253789422], [29665, 0.963121225378949], [29667, 0.9631212253789467], [29735, 0.9631212253789418], [29742, 0.9631212253789438], [29750, 0.963121225378947], [29753, 0.963121225378949], [29757, 0.9631212253789486], [29761, 0.9631212253789478], [29765, 0.9631212253789467], [29766, 0.9631212253789527], [29768, 0.9631212253789507], [29776, 0.9631212253789485], [29783, 0.9631212253789431], [29788, 0.9631212253789502], [29789, 0.9631212253789467], [29790, 0.9631212253789421], [29795, 0.9631212253789458], [29798, 0.9631212253789451], [29805, 0.9631212253789433], [29806, 0.9631212253789417], [29807, 0.9631212253789468], [29808, 0.9631212253789454], [29813, 0.9631212253789462], [29815, 0.9631212253789435], [29828, 0.9631212253789501], [29839, 0.9631212253789434], [29844, 0.9631212253789468], [29858, 0.9631212253789504], [29865, 0.9631212253789426], [29999, 0.9631212253789512], [30002, 0.9631212253789446], [30010, 0.9631212253789462], [30013, 0.9631212253789463], [30023, 0.9631212253789413], [30028, 0.9631212253789502], [30035, 0.9631212253971996], [30046, 0.9631212253972113], [30053, 0.9631212253972096], [30066, 0.9631212253972016], [30068, 0.9631212253972035], [30070, 0.9631212253972052], [30074, 0.9631212253972085], [30076, 0.9631212253972026], [30077, 0.9631212253971992], [30078, 0.963121225397206], [30085, 0.9631212253972079], [30086, 0.9631212253972019], [30096, 0.9631212253972005], [30104, 0.9631212253972077], [30106, 0.9631212253972012], [30112, 0.9631212253972065], [30116, 0.9631212253972015], [30118, 0.9631212253971975], [30123, 0.963121225397201], [30128, 0.9631212253971979], [30135, 0.9631212253972065], [30145, 0.9631212253972015], [30155, 0.9631212253972036], [30156, 0.9631212253972045], [30157, 0.9631212253972018], [30165, 0.9631212253972052], [30174, 0.9631212253972048], [30179, 0.9631212253972021], [30185, 0.963121225397204], [30189, 0.9631212253972103], [30190, 0.9631212253972048], [30198, 0.9631212253972002], [30202, 0.9631212253971985], [30203, 0.9631212253972082], [30208, 0.9631212253972024], [30212, 0.9631212253972045], [30213, 0.9631212253972036], [30215, 0.9631212253971967], [30218, 0.9631212253972081], [30225, 0.9631212253972026], [30227, 0.9631212253972012], [30233, 0.9631212253972024], [30235, 0.9631212253972036], [30238, 0.9631212253972011], [30244, 0.9631212253972024], [30248, 0.9631212253972017], [30254, 0.9631212253971991], [30259, 0.963121225397203], [30260, 0.9631212253972055], [30501, 0.9631212253972047], [30502, 0.9631212253972009], [30506, 0.9631212253971988], [30507, 0.9631212253972079], [30510, 0.9631212253971989], [30515, 0.9631212253972055], [30519, 0.9631212253972031], [30520, 0.9631212253972027], [30524, 0.9631212253972068], [30525, 0.9631212253972049], [30529, 0.9631212253972037], [30533, 0.9631212253972027], [30538, 0.9631212253972034], [30542, 0.963121225397203], [30543, 0.963121225397199], [30544, 0.9631212253972085], [30545, 0.9631212253972031], [30550, 0.9631212253972047], [30552, 0.9631212253972029], [30556, 0.963121225397199], [30561, 0.9631212253972085], [30564, 0.9631212253972022], [30565, 0.9631212253972032], [30577, 0.9631212253972055], [30581, 0.9631212253972017], [30586, 0.9631212253972025], [30593, 0.9631212253972057], [30615, 0.9631212253971998], [30621, 0.9631212253972042], [30622, 0.9631212253972031], [30629, 0.9631212253972136], [30635, 0.9631212253971992], [30639, 0.9631212253972041], [30640, 0.9631212253972058], [30643, 0.9631212253972047], [30646, 0.9631212253972029], [30647, 0.9631212253972075], [30650, 0.9631212253972045], [30657, 0.963121225397208], [30665, 0.963121225397207], [30670, 0.9631212253972059], [30675, 0.9631212253972032], [30679, 0.9631212253972026], [30694, 0.963121225397201], [30704, 0.9631212253972026], [30708, 0.9631212253971998], [30718, 0.9631212253972065], [30723, 0.9631212253972038], [30729, 0.9631212253972092], [30730, 0.9631212253972001], [30734, 0.9631212253972019], [30739, 0.9631212253972045], [30744, 0.963121225397207], [30748, 0.9631212253972057], [30750, 0.9631212253972045], [30754, 0.9631212253972027], [30761, 0.963121225397206], [30762, 0.9631212253972], [30777, 0.963121225397202], [30782, 0.9631212253972006], [30785, 0.9631212253972004], [30787, 0.9631212253971975], [30794, 0.963121225397203], [30804, 0.9631212253972002], [30812, 0.9631212253972089], [30817, 0.9631212253972053], [30821, 0.9631212253972028], [30838, 0.9631212253972032], [30849, 0.9631212253972058], [30861, 0.9631212253972034], [30868, 0.9631212253972026], [30872, 0.9631212253972032], [30890, 0.9631212253972052], [30904, 0.9631212253972018], [30907, 0.9631212253972044], [30908, 0.9631212253971992], [30917, 0.9631212253971996], [30928, 0.9631212253972036], [30931, 0.9631212253972024], [30938, 0.9631212253972027], [30945, 0.9631212253972056], [30949, 0.9631212253972008], [30955, 0.9631212253972073], [30957, 0.9631212253972008], [30967, 0.9631212253972009], [30974, 0.9631212253972092], [30978, 0.9631212253972031], [30987, 0.9631212253972006], [30988, 0.9631212253972028], [30994, 0.963121225397203], [30997, 0.9631212253972018], [31009, 0.963121225397203], [31019, 0.9631212253971978], [31031, 0.9631212253972032], [31039, 0.9631212253971939], [31040, 0.9631212253972035], [31041, 0.9631212253972075], [32090, 0.963121225397093], [32101, 0.9631212253971067], [32104, 0.9631212253970902], [32112, 0.9631212253970965], [32115, 0.9631212253970954], [32116, 0.9631212253971011], [32120, 0.9631212253971029], [32130, 0.9631212253970911], [32131, 0.963121225397102], [32132, 0.963121225397097], [32138, 0.9631212253970984], [32148, 0.963121225397088], [32152, 0.9631212253970836], [32156, 0.9631212253970962], [32157, 0.9631212253971063], [32163, 0.9631212253971002], [32174, 0.9631212253970923], [32181, 0.963121225397091], [32186, 0.963121225397085], [32187, 0.9631212253971017], [32193, 0.9631212253970907], [32197, 0.9631212253970893], [32198, 0.9631212253955468], [32204, 0.9631212253955649], [32213, 0.9631212253955671], [32218, 0.9631212253955285], [32220, 0.9631212253955751], [32224, 0.9631212253955214], [32241, 0.9631212253955416], [32249, 0.963121225395584], [32252, 0.9631212253955748], [32256, 0.9631212253955677], [32259, 0.9631212253955815], [32261, 0.9631212253956076], [32265, 0.9631212253955163], [32270, 0.9631212253955324], [32274, 0.9631212253955425], [32292, 0.9631212253955405], [32294, 0.9631212253955945], [33213, 0.9631212253742845], [33259, 0.9631212253742315], [33296, 0.9631212253742557], [33302, 0.9631212253742629], [33309, 0.9631212253742331], [33310, 0.9631212253742502], [33311, 0.9631212253742896], [33315, 0.9631212253742586], [33323, 0.9631212253742409], [33332, 0.9631212253743038], [33333, 0.9631212253743031], [33337, 0.9631212253742627], [33338, 0.9631212254053271], [33341, 0.9631212254053533], [33346, 0.9631212254053401], [33351, 0.9631212254053942], [33358, 0.9631212254053854], [33359, 0.9631212254053234], [33361, 0.963121225405373], [33370, 0.9631212254053413], [33373, 0.9631212254053546], [33380, 0.963121225405347], [33386, 0.9631212254053455], [33393, 0.9631212254053285], [33400, 0.9631212254053807], [33414, 0.9631212254053206], [33424, 0.9631212254053354], [33428, 0.9631212254054324], [33437, 0.9631212254053421], [33444, 0.9631212254053994], [33453, 0.9631212254054288], [33516, 0.9631212254053877], [33517, 0.963121225405414], [33518, 0.9631212254053314], [33520, 0.9631212254053677], [33524, 0.9631212254053543], [33533, 0.9631212254053301], [33536, 0.9631212254053355], [33537, 0.9631212254053789], [33543, 0.9631212254053397], [33546, 0.9631212254053765], [33648, 0.9631212254053672], [33704, 0.9631212254054043], [33707, 0.963121225405337], [33708, 0.9631212254053892], [33712, 0.9631212254053686], [33715, 0.9631212254053715], [33722, 0.9631212254053942], [33733, 0.9631212254053809], [33734, 0.9631212254053534], [33756, 0.963121225405382], [33766, 0.9631212254053731], [33802, 0.9631212254053069], [33808, 0.9631212254053388], [33813, 0.9631212254053405], [33818, 0.9631212254053965], [33820, 0.9631212254053236], [33826, 0.9631212254053905], [33833, 0.963121225405408], [34031, 0.9631212254052994], [34034, 0.9631212254053922], [34046, 0.9631212254053373], [34049, 0.9631212254053441], [34052, 0.9631212254053673], [34058, 0.9631212254053123], [34065, 0.9631212254053426], [34068, 0.9631212254053567], [34075, 0.96312122540533], [34079, 0.9631212254053721], [34113, 0.9631212254053191], [34115, 0.9631212254054008], [34120, 0.9631212254053703], [34126, 0.9631212254053522], [34139, 0.9631212254054209], [34140, 0.96312122540532], [34141, 0.9631212254053789], [34155, 0.9631212254053493], [34158, 0.9631212254053393], [34160, 0.963121225405348], [34162, 0.9631212254054097], [34164, 0.9631212254053595]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LogisticRegressionBenchmark.peakmem_fit.json b/graphs/summary/linear_model.LogisticRegressionBenchmark.peakmem_fit.json index 592e2e2b73..49cec1a07f 100644 --- a/graphs/summary/linear_model.LogisticRegressionBenchmark.peakmem_fit.json +++ b/graphs/summary/linear_model.LogisticRegressionBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 117057380.40498912], [29225, 113934557.12497725], [29239, 113899745.90040553], [29253, 114839757.28381185], [29267, 114829277.72825989], [29281, 114957728.30874732], [29295, 114914338.97844136], [29309, 114949898.82707933], [29323, 114890526.03358155], [29337, 115092055.57490647], [29351, 114405551.79955369], [29365, 114103703.11566949], [29379, 114416517.8170138], [29393, 114397066.31107199], [29407, 114402116.04794362], [29421, 114269442.50943397], [29435, 114882151.82126206], [29449, 113948076.07343018], [29463, 113846937.98616128], [29477, 113811338.09870145], [29547, 114288697.89937145], [29561, 114036249.04821827], [29575, 113463109.60127974], [29603, 115318211.79374662], [29617, 115357723.67168406], [29631, 115770811.01852635], [29645, 115421995.76109898], [29659, 115410710.04689108], [29673, 115325531.9112765], [29743, 115257890.54112597], [29757, 114939051.63913183], [29771, 115210978.94578679], [29785, 115377245.34163971], [29799, 115438325.73611411], [29813, 115644183.51548865], [29827, 115818593.28580853], [29841, 115169926.39097434], [29855, 115462125.70381996], [29869, 115794189.65088703], [30009, 115579660.58410344], [30023, 115522543.21584404], [30037, 115563567.78388445], [30051, 115499023.7600922], [30065, 115745313.37343821], [30079, 115625761.0987202], [30093, 115647206.29976174], [30107, 115537847.65031667], [30121, 115729589.98409207], [30135, 115715927.88252723], [30149, 115484274.23833145], [30163, 116194395.91391806], [30177, 116270367.91162568], [30191, 116257624.16701168], [30205, 116268344.97502917], [30219, 116263065.3394124], [30233, 116082087.48172039], [30247, 116298101.24064666], [30261, 116033573.50149517], [30513, 116196343.97986257], [30527, 116116799.27043934], [30541, 116015399.86725117], [30555, 115976937.7449174], [30569, 115889197.0990737], [30583, 116144609.3648018], [30597, 115985189.76471108], [30625, 115967345.6274479], [30639, 116228991.15799263], [30653, 116058387.09085603], [30667, 116083869.44932947], [30681, 116100772.26737118], [30695, 116059577.64061524], [30709, 115992743.35744372], [30723, 116108266.86768651], [30737, 116033591.76969543], [30751, 116103689.43241857], [30765, 116500169.4369822], [30779, 116025676.90796626], [30793, 116114093.67876114], [30807, 116067494.6637035], [30821, 116267717.21389489], [30835, 116358481.2255657], [30849, 116309908.68864977], [30863, 116140127.37932107], [30877, 116289834.52442722], [30891, 116182668.40613765], [30905, 116147928.69606268], [30919, 116016793.02243643], [30933, 116007757.2256442], [30947, 116046062.22479165], [30961, 116165573.53011326], [30975, 116119840.06257632], [30989, 115995348.84145766], [31003, 116198993.75045761], [31017, 116341904.1485447], [31031, 115961176.02211477], [31045, 116137124.70965847], [32095, 128811300.15913475], [32109, 128549864.49155113], [32123, 128691741.90311378], [32137, 128704106.95423956], [32151, 128497307.20185742], [32165, 128678756.69546089], [32179, 128329556.41857459], [32193, 128577075.84852917], [32207, 130274012.72057566], [32221, 132477184.35230829], [32235, 132645515.90319331], [32249, 132594956.1803424], [32263, 132481867.21306601], [32277, 131777975.54451708], [32305, 134205706.72879653], [32319, 139557328.39223054], [32333, 139809243.58638504], [32347, 139735572.52221525], [32361, 139889968.1004582], [32375, 139856892.5535432], [32389, 139471525.12478837], [32403, 139614176.6118954], [32417, 139567273.5995939], [32431, 139718844.72954935], [32445, 139941176.44198373], [32585, 136545817.68059352], [32599, 136621536.8032508], [32613, 136403962.8811843], [32627, 136789252.89402077], [32641, 136415080.66715878], [32655, 136554246.7549397], [32851, 137712878.0639653], [32865, 137702875.1775431], [32879, 137601096.80958137], [32893, 137727138.31668726], [32907, 138618858.8134745], [32921, 138506867.64941606], [32991, 138752022.69069818], [33005, 138503266.4946428], [33019, 138253519.8528654], [33033, 138462679.11588684], [33047, 138749212.19554064], [33061, 138987543.01493475], [33075, 138796246.4792272], [33089, 154887960.56394988], [33103, 170772059.20000517], [33117, 170986049.00819463], [33131, 170530599.97743294], [33145, 171035545.10956743], [33159, 171069774.14847142], [33187, 139238779.43003824], [33201, 138925688.50189254], [33215, 137667105.03924677], [33229, 133865641.4291865], [33243, 133710978.17670247], [33271, 128477839.04332052], [33299, 128869583.40107028], [33313, 128520592.30983423], [33327, 128880848.63077971], [33341, 128867697.42071912], [33355, 129220656.91883911], [33369, 129634329.29533345], [33383, 129945272.70359387], [33397, 130449380.05666047], [33411, 130307394.62330566], [33425, 130512735.32998617], [33439, 131593699.6749146], [33453, 126282689.97069816], [33467, 126326438.48812672], [33523, 126322524.27216624], [33537, 126341847.90422827], [33551, 125708279.06654315], [33649, 125170667.45047571], [33705, 124727467.09314048], [33719, 124875534.73369314], [33733, 124883209.13201807], [33747, 124840058.08736864], [33761, 124866258.80754852], [33775, 124758578.3069062], [33803, 124786872.89369261], [33817, 124514225.92462257], [33831, 124550440.80551751], [33845, 124601470.70388886], [34041, 124307829.45003045], [34055, 124593733.48144098], [34069, 124526617.56751995], [34083, 124373993.45972633], [34125, 118196713.15438448], [34139, 118429402.21787056], [34153, 118159248.51144843], [34167, 118124506.8333182]] \ No newline at end of file +[[28511, 117057380.40498912], [29225, 113934557.12497725], [29239, 113899745.90040553], [29253, 114839757.28381185], [29267, 114829277.72825989], [29281, 114957728.30874732], [29295, 114914338.97844136], [29309, 114949898.82707933], [29323, 114890526.03358155], [29337, 115092055.57490647], [29351, 114405551.79955369], [29365, 114103703.11566949], [29379, 114416517.8170138], [29393, 114397066.31107199], [29407, 114402116.04794362], [29421, 114269442.50943397], [29435, 114882151.82126206], [29449, 113948076.07343018], [29463, 113846937.98616128], [29477, 113811338.09870145], [29547, 114288697.89937145], [29561, 114036249.04821827], [29575, 113463109.60127974], [29603, 115318211.79374662], [29617, 115357723.67168406], [29631, 115770811.01852635], [29645, 115421995.76109898], [29659, 115410710.04689108], [29673, 115325531.9112765], [29743, 115257890.54112597], [29757, 114939051.63913183], [29771, 115210978.94578679], [29785, 115377245.34163971], [29799, 115438325.73611411], [29813, 115644183.51548865], [29827, 115818593.28580853], [29841, 115169926.39097434], [29855, 115462125.70381996], [29869, 115794189.65088703], [30009, 115579660.58410344], [30023, 115522543.21584404], [30037, 115563567.78388445], [30051, 115499023.7600922], [30065, 115745313.37343821], [30079, 115625761.0987202], [30093, 115647206.29976174], [30107, 115537847.65031667], [30121, 115729589.98409207], [30135, 115715927.88252723], [30149, 115484274.23833145], [30163, 116194395.91391806], [30177, 116270367.91162568], [30191, 116257624.16701168], [30205, 116268344.97502917], [30219, 116263065.3394124], [30233, 116082087.48172039], [30247, 116298101.24064666], [30261, 116033573.50149517], [30513, 116196343.97986257], [30527, 116116799.27043934], [30541, 116015399.86725117], [30555, 115976937.7449174], [30569, 115889197.0990737], [30583, 116144609.3648018], [30597, 115985189.76471108], [30625, 115967345.6274479], [30639, 116228991.15799263], [30653, 116058387.09085603], [30667, 116083869.44932947], [30681, 116100772.26737118], [30695, 116059577.64061524], [30709, 115992743.35744372], [30723, 116108266.86768651], [30737, 116033591.76969543], [30751, 116103689.43241857], [30765, 116500169.4369822], [30779, 116025676.90796626], [30793, 116114093.67876114], [30807, 116067494.6637035], [30821, 116267717.21389489], [30835, 116358481.2255657], [30849, 116309908.68864977], [30863, 116140127.37932107], [30877, 116289834.52442722], [30891, 116182668.40613765], [30905, 116147928.69606268], [30919, 116016793.02243643], [30933, 116007757.2256442], [30947, 116046062.22479165], [30961, 116165573.53011326], [30975, 116119840.06257632], [30989, 115995348.84145766], [31003, 116198993.75045761], [31017, 116341904.1485447], [31031, 115961176.02211477], [31045, 116137124.70965847], [32095, 128811300.15913475], [32109, 128549864.49155113], [32123, 128691741.90311378], [32137, 128704106.95423956], [32151, 128497307.20185742], [32165, 128678756.69546089], [32179, 128329556.41857459], [32193, 128577075.84852917], [32207, 130274012.72057566], [32221, 132477184.35230829], [32235, 132645515.90319331], [32249, 132594956.1803424], [32263, 132481867.21306601], [32277, 131777975.54451708], [32305, 134205706.72879653], [32319, 139557328.39223054], [32333, 139809243.58638504], [32347, 139735572.52221525], [32361, 139889968.1004582], [32375, 139856892.5535432], [32389, 139471525.12478837], [32403, 139614176.6118954], [32417, 139567273.5995939], [32431, 139718844.72954935], [32445, 139941176.44198373], [32585, 136545817.68059352], [32599, 136621536.8032508], [32613, 136403962.8811843], [32627, 136789252.89402077], [32641, 136415080.66715878], [32655, 136554246.7549397], [32851, 137712878.0639653], [32865, 137702875.1775431], [32879, 137601096.80958137], [32893, 137727138.31668726], [32907, 138618858.8134745], [32921, 138506867.64941606], [32991, 138752022.69069818], [33005, 138503266.4946428], [33019, 138253519.8528654], [33033, 138462679.11588684], [33047, 138749212.19554064], [33061, 138987543.01493475], [33075, 138796246.4792272], [33089, 154887960.56394988], [33103, 170772059.20000517], [33117, 170986049.00819463], [33131, 170530599.97743294], [33145, 171035545.10956743], [33159, 171069774.14847142], [33187, 139238779.43003824], [33201, 138925688.50189254], [33215, 137667105.03924677], [33229, 133865641.4291865], [33243, 133710978.17670247], [33271, 128477839.04332052], [33299, 128869583.40107028], [33313, 128520592.30983423], [33327, 128880848.63077971], [33341, 128867697.42071912], [33355, 129220656.91883911], [33369, 129634329.29533345], [33383, 129945272.70359387], [33397, 130449380.05666047], [33411, 130307394.62330566], [33425, 130512735.32998617], [33439, 131593699.6749146], [33453, 126282689.97069816], [33467, 126326438.48812672], [33523, 126322524.27216624], [33537, 126341847.90422827], [33551, 125708279.06654315], [33649, 125170667.45047571], [33705, 124727467.09314048], [33719, 124875534.73369314], [33733, 124883209.13201807], [33747, 124840058.08736864], [33761, 124866258.80754852], [33775, 124758578.3069062], [33803, 124786872.89369261], [33817, 124514225.92462257], [33831, 124550440.80551751], [33845, 124601470.70388886], [34041, 124307829.45003045], [34055, 124593733.48144098], [34069, 124526617.56751995], [34083, 124373993.45972633], [34125, 118196713.15438448], [34139, 118429402.21787056], [34153, 118159248.51144843], [34167, 118111230.76687531]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LogisticRegressionBenchmark.peakmem_predict.json b/graphs/summary/linear_model.LogisticRegressionBenchmark.peakmem_predict.json index be302436f3..24b3a8a428 100644 --- a/graphs/summary/linear_model.LogisticRegressionBenchmark.peakmem_predict.json +++ b/graphs/summary/linear_model.LogisticRegressionBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28511, 89229939.7421569], [29225, 85502052.99934964], [29239, 85447370.35046363], [29253, 87192422.3012463], [29267, 87205643.14671153], [29281, 87384205.7521628], [29295, 87397568.34714632], [29309, 87196899.8675749], [29323, 87151927.49129605], [29337, 87311043.6916507], [29351, 86597516.96919243], [29365, 86449893.11328356], [29379, 86780722.55790251], [29393, 86790755.91266312], [29407, 86618715.06499897], [29421, 86510034.05173132], [29435, 87063426.44837706], [29449, 85657133.62887305], [29463, 85682961.06060736], [29477, 85745996.19327049], [29547, 85887150.480656], [29561, 85811221.99070887], [29575, 85249055.93155167], [29603, 86388832.09498164], [29617, 86401583.61808617], [29631, 86658620.30105256], [29645, 86541505.24242035], [29659, 86509494.56642169], [29673, 86491771.79981293], [29743, 86458664.9167768], [29757, 86151263.30252226], [29771, 86336591.8112199], [29785, 86614658.41496578], [29799, 86582051.0106356], [29813, 86608637.92683923], [29827, 86695395.08178705], [29841, 86307607.48632753], [29855, 86559287.9203344], [29869, 86717158.9054037], [30009, 86619667.2703762], [30023, 86596469.60709396], [30037, 86502541.19320218], [30051, 86464019.52769795], [30065, 86513327.82554354], [30079, 86617292.76182766], [30093, 86533742.57507312], [30107, 86513127.91824232], [30121, 86624539.05172847], [30135, 86600987.04598269], [30149, 86473124.71417755], [30163, 86964893.64521332], [30177, 87199184.24498823], [30191, 87066302.342517], [30205, 86981918.71466385], [30219, 87047305.1597494], [30233, 86859130.01052754], [30247, 87107832.53020903], [30261, 86896754.7587707], [30513, 87026741.89921315], [30527, 86945840.78578492], [30541, 86946332.22289424], [30555, 86807511.89394073], [30569, 86811422.09019993], [30583, 86984391.36595246], [30597, 86812896.93786198], [30625, 87001509.38728344], [30639, 86905960.22989571], [30653, 86835395.52808236], [30667, 86802456.6081076], [30681, 86879065.81881933], [30695, 86994747.47272107], [30709, 86882869.92936699], [30723, 86915934.28661758], [30737, 86953029.58804679], [30751, 87038505.5830152], [30765, 87331895.52916366], [30779, 86865618.28634733], [30793, 86863230.97863318], [30807, 86933524.86501688], [30821, 87072375.57727791], [30835, 87113422.64559716], [30849, 87034870.01408336], [30863, 87044676.90423977], [30877, 87219543.61254561], [30891, 87303091.66255796], [30905, 87257136.47751348], [30919, 86960127.87671514], [30933, 86985619.49956079], [30947, 87100253.28800315], [30961, 87026197.64022578], [30975, 87151317.16720316], [30989, 86881508.65034236], [31003, 87294530.99365488], [31017, 87168963.06075567], [31031, 86872082.4865784], [31045, 87100155.08704996], [32095, 98063402.44415288], [32109, 97779321.8447846], [32123, 97851667.36433019], [32137, 97872197.6310755], [32151, 97852876.89913934], [32165, 97824546.91368578], [32179, 97744761.85749102], [32193, 98021546.39882], [32207, 99278899.6681699], [32221, 101168366.40752876], [32235, 101512778.99534549], [32249, 101389943.36926857], [32263, 101248144.06101704], [32277, 100325643.81815125], [32305, 101695279.7812831], [32319, 104373961.12625216], [32333, 104415529.87625648], [32347, 104428975.06046897], [32361, 104461293.56375124], [32375, 104545247.3079679], [32389, 104330579.66585894], [32403, 104455360.6619818], [32417, 104363014.70950247], [32431, 104450338.3749899], [32445, 104586951.21623637], [32585, 104660877.59372003], [32599, 104652518.1666563], [32613, 104629914.26269422], [32627, 104724976.39870773], [32641, 104520061.86286986], [32655, 104663669.56467849], [32851, 105507682.89721225], [32865, 105600725.1931701], [32879, 105656027.15899564], [32893, 105719605.33514649], [32907, 105797600.67638306], [32921, 105759212.15349916], [32991, 105781067.55658273], [33005, 105817735.61321315], [33019, 105444468.6690862], [33033, 105685140.49825619], [33047, 105857065.16807765], [33061, 106077159.10124095], [33075, 105882141.85296862], [33089, 120949153.35367943], [33103, 135824117.00517282], [33117, 136080537.11143747], [33131, 135585129.93928817], [33145, 136135420.46963206], [33159, 136168408.1207976], [33187, 106134723.77836809], [33201, 106089732.6601859], [33215, 104891835.05029276], [33229, 101352364.60232705], [33243, 101459628.41722639], [33271, 96662432.14202112], [33299, 96798829.92719838], [33313, 96947158.83630317], [33327, 97390777.69707301], [33341, 97303793.59363425], [33355, 97527413.74608183], [33369, 98056876.33631329], [33383, 98289406.04110233], [33397, 98513052.66482878], [33411, 98491617.69085734], [33425, 98578972.55708674], [33439, 99594245.88030508], [33453, 94711534.96015601], [33467, 94922127.12265928], [33523, 94952597.98440519], [33537, 95009967.67744637], [33551, 94373699.08181988], [33649, 93668345.51854181], [33705, 93157059.19251803], [33719, 93343589.21392438], [33733, 93509485.1269097], [33747, 93330209.7593031], [33761, 93441469.41054346], [33775, 93188762.58552428], [33803, 93413248.83848341], [33817, 93066564.34523359], [33831, 93305365.48341219], [33845, 93125757.41397442], [34041, 92867197.27759582], [34055, 93163865.35066603], [34069, 93167870.97393231], [34083, 92920520.00748345], [34125, 93156152.19191225], [34139, 93334386.82034135], [34153, 93059635.39608069], [34167, 93112399.380092]] \ No newline at end of file +[[28511, 89229939.7421569], [29225, 85502052.99934964], [29239, 85447370.35046363], [29253, 87192422.3012463], [29267, 87205643.14671153], [29281, 87384205.7521628], [29295, 87397568.34714632], [29309, 87196899.8675749], [29323, 87151927.49129605], [29337, 87311043.6916507], [29351, 86597516.96919243], [29365, 86449893.11328356], [29379, 86780722.55790251], [29393, 86790755.91266312], [29407, 86618715.06499897], [29421, 86510034.05173132], [29435, 87063426.44837706], [29449, 85657133.62887305], [29463, 85682961.06060736], [29477, 85745996.19327049], [29547, 85887150.480656], [29561, 85811221.99070887], [29575, 85249055.93155167], [29603, 86388832.09498164], [29617, 86401583.61808617], [29631, 86658620.30105256], [29645, 86541505.24242035], [29659, 86509494.56642169], [29673, 86491771.79981293], [29743, 86458664.9167768], [29757, 86151263.30252226], [29771, 86336591.8112199], [29785, 86614658.41496578], [29799, 86582051.0106356], [29813, 86608637.92683923], [29827, 86695395.08178705], [29841, 86307607.48632753], [29855, 86559287.9203344], [29869, 86717158.9054037], [30009, 86619667.2703762], [30023, 86596469.60709396], [30037, 86502541.19320218], [30051, 86464019.52769795], [30065, 86513327.82554354], [30079, 86617292.76182766], [30093, 86533742.57507312], [30107, 86513127.91824232], [30121, 86624539.05172847], [30135, 86600987.04598269], [30149, 86473124.71417755], [30163, 86964893.64521332], [30177, 87199184.24498823], [30191, 87066302.342517], [30205, 86981918.71466385], [30219, 87047305.1597494], [30233, 86859130.01052754], [30247, 87107832.53020903], [30261, 86896754.7587707], [30513, 87026741.89921315], [30527, 86945840.78578492], [30541, 86946332.22289424], [30555, 86807511.89394073], [30569, 86811422.09019993], [30583, 86984391.36595246], [30597, 86812896.93786198], [30625, 87001509.38728344], [30639, 86905960.22989571], [30653, 86835395.52808236], [30667, 86802456.6081076], [30681, 86879065.81881933], [30695, 86994747.47272107], [30709, 86882869.92936699], [30723, 86915934.28661758], [30737, 86953029.58804679], [30751, 87038505.5830152], [30765, 87331895.52916366], [30779, 86865618.28634733], [30793, 86863230.97863318], [30807, 86933524.86501688], [30821, 87072375.57727791], [30835, 87113422.64559716], [30849, 87034870.01408336], [30863, 87044676.90423977], [30877, 87219543.61254561], [30891, 87303091.66255796], [30905, 87257136.47751348], [30919, 86960127.87671514], [30933, 86985619.49956079], [30947, 87100253.28800315], [30961, 87026197.64022578], [30975, 87151317.16720316], [30989, 86881508.65034236], [31003, 87294530.99365488], [31017, 87168963.06075567], [31031, 86872082.4865784], [31045, 87100155.08704996], [32095, 98063402.44415288], [32109, 97779321.8447846], [32123, 97851667.36433019], [32137, 97872197.6310755], [32151, 97852876.89913934], [32165, 97824546.91368578], [32179, 97744761.85749102], [32193, 98021546.39882], [32207, 99278899.6681699], [32221, 101168366.40752876], [32235, 101512778.99534549], [32249, 101389943.36926857], [32263, 101248144.06101704], [32277, 100325643.81815125], [32305, 101695279.7812831], [32319, 104373961.12625216], [32333, 104415529.87625648], [32347, 104428975.06046897], [32361, 104461293.56375124], [32375, 104545247.3079679], [32389, 104330579.66585894], [32403, 104455360.6619818], [32417, 104363014.70950247], [32431, 104450338.3749899], [32445, 104586951.21623637], [32585, 104660877.59372003], [32599, 104652518.1666563], [32613, 104629914.26269422], [32627, 104724976.39870773], [32641, 104520061.86286986], [32655, 104663669.56467849], [32851, 105507682.89721225], [32865, 105600725.1931701], [32879, 105656027.15899564], [32893, 105719605.33514649], [32907, 105797600.67638306], [32921, 105759212.15349916], [32991, 105781067.55658273], [33005, 105817735.61321315], [33019, 105444468.6690862], [33033, 105685140.49825619], [33047, 105857065.16807765], [33061, 106077159.10124095], [33075, 105882141.85296862], [33089, 120949153.35367943], [33103, 135824117.00517282], [33117, 136080537.11143747], [33131, 135585129.93928817], [33145, 136135420.46963206], [33159, 136168408.1207976], [33187, 106134723.77836809], [33201, 106089732.6601859], [33215, 104891835.05029276], [33229, 101352364.60232705], [33243, 101459628.41722639], [33271, 96662432.14202112], [33299, 96798829.92719838], [33313, 96947158.83630317], [33327, 97390777.69707301], [33341, 97303793.59363425], [33355, 97527413.74608183], [33369, 98056876.33631329], [33383, 98289406.04110233], [33397, 98513052.66482878], [33411, 98491617.69085734], [33425, 98578972.55708674], [33439, 99594245.88030508], [33453, 94711534.96015601], [33467, 94922127.12265928], [33523, 94952597.98440519], [33537, 95009967.67744637], [33551, 94373699.08181988], [33649, 93668345.51854181], [33705, 93157059.19251803], [33719, 93343589.21392438], [33733, 93509485.1269097], [33747, 93330209.7593031], [33761, 93441469.41054346], [33775, 93188762.58552428], [33803, 93413248.83848341], [33817, 93066564.34523359], [33831, 93305365.48341219], [33845, 93125757.41397442], [34041, 92867197.27759582], [34055, 93163865.35066603], [34069, 93167870.97393231], [34083, 92920520.00748345], [34125, 93156152.19191225], [34139, 93334386.82034135], [34153, 93059635.39608069], [34167, 93083227.83592859]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LogisticRegressionBenchmark.time_fit.json b/graphs/summary/linear_model.LogisticRegressionBenchmark.time_fit.json index f667d44c73..177072c8e4 100644 --- a/graphs/summary/linear_model.LogisticRegressionBenchmark.time_fit.json +++ b/graphs/summary/linear_model.LogisticRegressionBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 2.7448217920907183], [29225, 3.806193446901157], [29239, 3.762807712852046], [29253, 2.6673714175789454], [29267, 2.7603802315634183], [29281, 2.727607562672634], [29295, 2.6823607626569537], [29309, 2.67594802006999], [29323, 2.651190826220706], [29337, 2.7299080921400023], [29351, 2.79965078900001], [29365, 2.6780809298271038], [29379, 2.6223409000922047], [29393, 2.662370762505183], [29407, 2.7181941056902774], [29421, 2.700520545559366], [29435, 2.7689704631853935], [29449, 4.567770842151904], [29463, 4.3751271191592265], [29477, 4.645003244794997], [29547, 5.017267359562292], [29561, 4.238939996342145], [29575, 3.8458838659792955], [29603, 3.7250800033257008], [29617, 3.706557585545063], [29631, 3.7800637086974644], [29645, 3.7872797266570357], [29659, 3.7057736204259455], [29673, 3.657376030516889], [29743, 3.5241398760415326], [29757, 3.8733183714896784], [29771, 3.7195041351356117], [29785, 4.38206532194342], [29799, 3.8641027560605026], [29813, 3.9102373869050693], [29827, 3.9310285718936457], [29841, 4.025728648687759], [29855, 3.9706319011930913], [29869, 3.957429517470403], [30009, 4.002333143350927], [30023, 3.8115791827489605], [30037, 3.7812370452465642], [30051, 3.9012247362474546], [30065, 3.882808424512617], [30079, 3.912402585418962], [30093, 3.73475450369638], [30107, 3.777825531754363], [30121, 3.9034040900659566], [30135, 3.8124387860183644], [30149, 4.1196030163887345], [30163, 3.837178624013493], [30177, 3.844919877746814], [30191, 3.846993464438373], [30205, 3.909492890161861], [30219, 4.012358747069375], [30233, 3.729232979366894], [30247, 3.955925887435634], [30261, 3.814586604011262], [30513, 3.928699773385941], [30527, 3.8343530391189553], [30541, 3.8726245542228974], [30555, 3.7176461169275328], [30569, 3.8940016426166393], [30583, 3.8202429852146977], [30597, 3.904475942472128], [30625, 3.863825156991844], [30639, 3.8643456571895767], [30653, 3.879120270533825], [30667, 3.942545830968948], [30681, 3.9054367048979786], [30695, 3.3385229154734293], [30709, 3.4831656371176827], [30723, 3.4999409507529986], [30737, 3.4994970896992172], [30751, 3.423330008105606], [30765, 3.4061328098399257], [30779, 3.6015561929262536], [30793, 3.5212082651850096], [30807, 3.450537862193667], [30821, 3.586778936825243], [30835, 3.3941554318261393], [30849, 3.387301744184181], [30863, 3.3832115711758166], [30877, 3.3573419076941935], [30891, 3.4654072836426075], [30905, 3.396243351851261], [30919, 3.509479681954343], [30933, 3.4937205040939903], [30947, 3.3702057131235126], [30961, 3.492076743004111], [30975, 3.5146925218424343], [30989, 3.4732824872583863], [31003, 3.357475740574029], [31017, 3.4869472090794607], [31031, 3.9200867595094797], [31045, 3.348341307182353], [32095, 3.3235059168372683], [32109, 3.547731413075244], [32123, 3.5847095786768586], [32137, 3.542288798512745], [32151, 3.5410743974693877], [32165, 3.5629199713702064], [32179, 3.4661504719409586], [32193, 3.45301079577341], [32207, 3.472446983549998], [32221, 3.5292886218409323], [32235, 3.2923228126787287], [32249, 3.44460353040306], [32263, 3.600558639322732], [32277, 3.5676821969274015], [32305, 3.632411308739011], [32319, 3.4910492655596634], [32333, 3.3555243071092136], [32347, 3.5438877518532377], [32361, 3.605196359801904], [32375, 3.3989848847804542], [32389, 3.3701069078788777], [32403, 3.514729619330329], [32417, 3.4324293310211353], [32431, 3.437741860864489], [32445, 3.4030907967572803], [32585, 4.063161672527547], [32599, 4.216806599742113], [32613, 4.121663718004987], [32627, 4.072750593150336], [32641, 4.075119767057533], [32655, 4.170240816572746], [32851, 4.060735558826447], [32865, 3.930578780250963], [32879, 4.029794916492239], [32893, 4.159401448621656], [32907, 3.9974178037915578], [32921, 3.951674999535526], [32991, 3.862999509331257], [33005, 4.161815638430194], [33019, 4.037423148347252], [33033, 4.016536566988961], [33047, 4.072246490476949], [33061, 3.9397626271753907], [33075, 4.019712511608665], [33089, 4.001795324524808], [33103, 4.00109908623632], [33117, 4.0354351359620715], [33131, 4.09653635180662], [33145, 4.2523993490993215], [33159, 4.244039274403032], [33187, 3.9718770647439556], [33201, 3.987727804652728], [33215, 4.0091051969639535], [33229, 4.054842808326033], [33243, 4.019995986769571], [33271, 4.2521266662113995], [33299, 4.001255050773296], [33313, 3.9087827666613917], [33327, 4.0080884913576025], [33341, 4.009794278972436], [33355, 3.9666315339171128], [33369, 3.8912496602660838], [33383, 3.9391659103704963], [33397, 3.9936921667885903], [33411, 4.087237095440084], [33425, 4.041738162871217], [33439, 4.047110763622149], [33453, 4.0615802641526395], [33467, 4.343999099740428], [33523, 3.947396039357904], [33537, 3.827939362566864], [33551, 4.0219695415734025], [33649, 4.06851040511171], [33705, 4.001484126993788], [33719, 3.9713525703754127], [33733, 4.207957001897864], [33747, 3.9728034699861423], [33761, 3.7863825643144393], [33775, 3.8536613912630453], [33803, 3.91031912179306], [33817, 3.778991747021168], [33831, 3.804164265431061], [33845, 3.835904553930859], [34041, 3.801838954466294], [34055, 3.925739869097843], [34069, 3.996556648934767], [34083, 3.7554315222651993], [34125, 1.2092283888257074], [34139, 1.2424183635405848], [34153, 1.2727324205981478], [34167, 1.2257533642268958]] \ No newline at end of file +[[28511, 2.7448217920907183], [29225, 3.806193446901157], [29239, 3.762807712852046], [29253, 2.6673714175789454], [29267, 2.7603802315634183], [29281, 2.727607562672634], [29295, 2.6823607626569537], [29309, 2.67594802006999], [29323, 2.651190826220706], [29337, 2.7299080921400023], [29351, 2.79965078900001], [29365, 2.6780809298271038], [29379, 2.6223409000922047], [29393, 2.662370762505183], [29407, 2.7181941056902774], [29421, 2.700520545559366], [29435, 2.7689704631853935], [29449, 4.567770842151904], [29463, 4.3751271191592265], [29477, 4.645003244794997], [29547, 5.017267359562292], [29561, 4.238939996342145], [29575, 3.8458838659792955], [29603, 3.7250800033257008], [29617, 3.706557585545063], [29631, 3.7800637086974644], [29645, 3.7872797266570357], [29659, 3.7057736204259455], [29673, 3.657376030516889], [29743, 3.5241398760415326], [29757, 3.8733183714896784], [29771, 3.7195041351356117], [29785, 4.38206532194342], [29799, 3.8641027560605026], [29813, 3.9102373869050693], [29827, 3.9310285718936457], [29841, 4.025728648687759], [29855, 3.9706319011930913], [29869, 3.957429517470403], [30009, 4.002333143350927], [30023, 3.8115791827489605], [30037, 3.7812370452465642], [30051, 3.9012247362474546], [30065, 3.882808424512617], [30079, 3.912402585418962], [30093, 3.73475450369638], [30107, 3.777825531754363], [30121, 3.9034040900659566], [30135, 3.8124387860183644], [30149, 4.1196030163887345], [30163, 3.837178624013493], [30177, 3.844919877746814], [30191, 3.846993464438373], [30205, 3.909492890161861], [30219, 4.012358747069375], [30233, 3.729232979366894], [30247, 3.955925887435634], [30261, 3.814586604011262], [30513, 3.928699773385941], [30527, 3.8343530391189553], [30541, 3.8726245542228974], [30555, 3.7176461169275328], [30569, 3.8940016426166393], [30583, 3.8202429852146977], [30597, 3.904475942472128], [30625, 3.863825156991844], [30639, 3.8643456571895767], [30653, 3.879120270533825], [30667, 3.942545830968948], [30681, 3.9054367048979786], [30695, 3.3385229154734293], [30709, 3.4831656371176827], [30723, 3.4999409507529986], [30737, 3.4994970896992172], [30751, 3.423330008105606], [30765, 3.4061328098399257], [30779, 3.6015561929262536], [30793, 3.5212082651850096], [30807, 3.450537862193667], [30821, 3.586778936825243], [30835, 3.3941554318261393], [30849, 3.387301744184181], [30863, 3.3832115711758166], [30877, 3.3573419076941935], [30891, 3.4654072836426075], [30905, 3.396243351851261], [30919, 3.509479681954343], [30933, 3.4937205040939903], [30947, 3.3702057131235126], [30961, 3.492076743004111], [30975, 3.5146925218424343], [30989, 3.4732824872583863], [31003, 3.357475740574029], [31017, 3.4869472090794607], [31031, 3.9200867595094797], [31045, 3.348341307182353], [32095, 3.3235059168372683], [32109, 3.547731413075244], [32123, 3.5847095786768586], [32137, 3.542288798512745], [32151, 3.5410743974693877], [32165, 3.5629199713702064], [32179, 3.4661504719409586], [32193, 3.45301079577341], [32207, 3.472446983549998], [32221, 3.5292886218409323], [32235, 3.2923228126787287], [32249, 3.44460353040306], [32263, 3.600558639322732], [32277, 3.5676821969274015], [32305, 3.632411308739011], [32319, 3.4910492655596634], [32333, 3.3555243071092136], [32347, 3.5438877518532377], [32361, 3.605196359801904], [32375, 3.3989848847804542], [32389, 3.3701069078788777], [32403, 3.514729619330329], [32417, 3.4324293310211353], [32431, 3.437741860864489], [32445, 3.4030907967572803], [32585, 4.063161672527547], [32599, 4.216806599742113], [32613, 4.121663718004987], [32627, 4.072750593150336], [32641, 4.075119767057533], [32655, 4.170240816572746], [32851, 4.060735558826447], [32865, 3.930578780250963], [32879, 4.029794916492239], [32893, 4.159401448621656], [32907, 3.9974178037915578], [32921, 3.951674999535526], [32991, 3.862999509331257], [33005, 4.161815638430194], [33019, 4.037423148347252], [33033, 4.016536566988961], [33047, 4.072246490476949], [33061, 3.9397626271753907], [33075, 4.019712511608665], [33089, 4.001795324524808], [33103, 4.00109908623632], [33117, 4.0354351359620715], [33131, 4.09653635180662], [33145, 4.2523993490993215], [33159, 4.244039274403032], [33187, 3.9718770647439556], [33201, 3.987727804652728], [33215, 4.0091051969639535], [33229, 4.054842808326033], [33243, 4.019995986769571], [33271, 4.2521266662113995], [33299, 4.001255050773296], [33313, 3.9087827666613917], [33327, 4.0080884913576025], [33341, 4.009794278972436], [33355, 3.9666315339171128], [33369, 3.8912496602660838], [33383, 3.9391659103704963], [33397, 3.9936921667885903], [33411, 4.087237095440084], [33425, 4.041738162871217], [33439, 4.047110763622149], [33453, 4.0615802641526395], [33467, 4.343999099740428], [33523, 3.947396039357904], [33537, 3.827939362566864], [33551, 4.0219695415734025], [33649, 4.06851040511171], [33705, 4.001484126993788], [33719, 3.9713525703754127], [33733, 4.207957001897864], [33747, 3.9728034699861423], [33761, 3.7863825643144393], [33775, 3.8536613912630453], [33803, 3.91031912179306], [33817, 3.778991747021168], [33831, 3.804164265431061], [33845, 3.835904553930859], [34041, 3.801838954466294], [34055, 3.925739869097843], [34069, 3.996556648934767], [34083, 3.7554315222651993], [34125, 1.2092283888257074], [34139, 1.2424183635405848], [34153, 1.2727324205981478], [34167, 1.2322561795546805]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LogisticRegressionBenchmark.time_predict.json b/graphs/summary/linear_model.LogisticRegressionBenchmark.time_predict.json index 13ef0c1222..9551fbfbb2 100644 --- a/graphs/summary/linear_model.LogisticRegressionBenchmark.time_predict.json +++ b/graphs/summary/linear_model.LogisticRegressionBenchmark.time_predict.json @@ -1 +1 @@ -[[28511, 0.0033935218987848114], [29225, 0.004595619857389839], [29239, 0.004502922429440747], [29253, 0.003281788549402705], [29267, 0.0033384814500727828], [29281, 0.003429475088785768], [29295, 0.0034891507747894564], [29309, 0.00339135096197849], [29323, 0.0032096340817811294], [29337, 0.0034742966227129263], [29351, 0.0034946402746177815], [29365, 0.003395374251274228], [29379, 0.003332023380062168], [29393, 0.003271336250521038], [29407, 0.0035315239345078313], [29421, 0.003419589727789765], [29435, 0.0033233639584127283], [29449, 0.004843766887464081], [29463, 0.004899236379329599], [29477, 0.004715964893732405], [29547, 0.00512893658090305], [29561, 0.005056540848034134], [29575, 0.00431147373754637], [29603, 0.0042150424814493175], [29617, 0.0039376657678875625], [29631, 0.004187927524780182], [29645, 0.004237624357959591], [29659, 0.0041988230537733495], [29673, 0.004134826025567282], [29743, 0.0040917590526156535], [29757, 0.004316233473139346], [29771, 0.004292399221888748], [29785, 0.004618753633266735], [29799, 0.004639436503190454], [29813, 0.004542088391054112], [29827, 0.004884748699273233], [29841, 0.004667408316355733], [29855, 0.0044618927445945165], [29869, 0.004590008482759937], [30009, 0.004545743974619372], [30023, 0.004767518598419665], [30037, 0.004657723767683867], [30051, 0.004601966497433438], [30065, 0.004650947169666352], [30079, 0.004588257868667346], [30093, 0.004734924548166642], [30107, 0.004441999158338927], [30121, 0.004749195439649348], [30135, 0.004759361438136572], [30149, 0.004810026318427689], [30163, 0.004802058311775599], [30177, 0.004797513439886396], [30191, 0.004805343733493128], [30205, 0.004524943674953184], [30219, 0.004834056860062713], [30233, 0.004605831652319058], [30247, 0.004609843408927179], [30261, 0.004517083344972963], [30513, 0.004566017442939815], [30527, 0.004758443732616452], [30541, 0.004576345572891965], [30555, 0.004702791300006378], [30569, 0.004617697986725454], [30583, 0.004770065171979221], [30597, 0.004598942659276678], [30625, 0.004439937234153428], [30639, 0.004470476216554178], [30653, 0.004643831354544178], [30667, 0.004833232122016981], [30681, 0.00465787589854482], [30695, 0.005073268560640968], [30709, 0.004541035009000586], [30723, 0.004721904911264465], [30737, 0.004718753625612261], [30751, 0.004884745239591722], [30765, 0.004544986171401859], [30779, 0.004877917796789273], [30793, 0.004595827449112126], [30807, 0.00464898135092397], [30821, 0.004462572657782977], [30835, 0.00475826282520608], [30849, 0.0045634487783408], [30863, 0.00453240459899477], [30877, 0.0045638732029182946], [30891, 0.004728563105665274], [30905, 0.004841088057475155], [30919, 0.004587004428694247], [30933, 0.004492735658183788], [30947, 0.00457490680687248], [30961, 0.004636838818538364], [30975, 0.004589607582374559], [30989, 0.0048393767369458735], [31003, 0.004452483706487288], [31017, 0.005139350052110729], [31031, 0.004591356786754843], [31045, 0.004764606701174878], [32095, 0.00400806226949959], [32109, 0.004065551020128831], [32123, 0.004078957272697788], [32137, 0.003931540196296821], [32151, 0.004281051414381124], [32165, 0.0041495165394893315], [32179, 0.004089495007818861], [32193, 0.003911869317626896], [32207, 0.004107062289714496], [32221, 0.004171456528936719], [32235, 0.0040338956820321886], [32249, 0.004147407854952483], [32263, 0.004273612068747809], [32277, 0.004081254371365761], [32305, 0.004118681756675107], [32319, 0.004155430413280696], [32333, 0.0042337468428350535], [32347, 0.00429827897128819], [32361, 0.0041309726801151345], [32375, 0.004161638316535083], [32389, 0.003973560797719568], [32403, 0.004180269414596809], [32417, 0.004486404821981445], [32431, 0.004063831261327217], [32445, 0.004222795673158852], [32585, 0.0039435204996738716], [32599, 0.00416790529142031], [32613, 0.0038533916822508472], [32627, 0.0040364545502531825], [32641, 0.003906603105039203], [32655, 0.00404689958031906], [32851, 0.004015021787942147], [32865, 0.003945988783621916], [32879, 0.003962688027515429], [32893, 0.003999366582082571], [32907, 0.0041072671815880635], [32921, 0.003954040679439733], [32991, 0.004006770692077466], [33005, 0.004134488656824124], [33019, 0.003918700539080694], [33033, 0.0040139053024830906], [33047, 0.004188385057173512], [33061, 0.003995383394893472], [33075, 0.004122538862625798], [33089, 0.004004201267211566], [33103, 0.004181445901327696], [33117, 0.0038659891464983094], [33131, 0.004115350965059614], [33145, 0.0038972655340831796], [33159, 0.00401143749946991], [33187, 0.0041917619670325855], [33201, 0.0040955799500291806], [33215, 0.004175081961557886], [33229, 0.004615323087750372], [33243, 0.004511164352717025], [33271, 0.004764520601216743], [33299, 0.005246522134057713], [33313, 0.004936737299190701], [33327, 0.004775385359921363], [33341, 0.00476980926773858], [33355, 0.005051703956058722], [33369, 0.004815012878072401], [33383, 0.004949517608935406], [33397, 0.0048585214492898755], [33411, 0.004548907390142052], [33425, 0.0046461061527304035], [33439, 0.005137893661175301], [33453, 0.004961552564500937], [33467, 0.0047323970444961725], [33523, 0.004722305669109982], [33537, 0.004918633349290303], [33551, 0.004821285352441618], [33649, 0.004782164696561316], [33705, 0.00473756314315295], [33719, 0.004695196736997171], [33733, 0.004120838684084699], [33747, 0.004169309511066945], [33761, 0.00416095101525671], [33775, 0.004592442840437661], [33803, 0.004082514323318309], [33817, 0.0042317013672149035], [33831, 0.00419215202118297], [33845, 0.00382416822037819], [34041, 0.004081395596235658], [34055, 0.004048275233115977], [34069, 0.004189463968509983], [34083, 0.004183904606944299], [34125, 0.003999905500539337], [34139, 0.004021847917616697], [34153, 0.003944874733634544], [34167, 0.004018493619025949]] \ No newline at end of file +[[28511, 0.0033935218987848114], [29225, 0.004595619857389839], [29239, 0.004502922429440747], [29253, 0.003281788549402705], [29267, 0.0033384814500727828], [29281, 0.003429475088785768], [29295, 0.0034891507747894564], [29309, 0.00339135096197849], [29323, 0.0032096340817811294], [29337, 0.0034742966227129263], [29351, 0.0034946402746177815], [29365, 0.003395374251274228], [29379, 0.003332023380062168], [29393, 0.003271336250521038], [29407, 0.0035315239345078313], [29421, 0.003419589727789765], [29435, 0.0033233639584127283], [29449, 0.004843766887464081], [29463, 0.004899236379329599], [29477, 0.004715964893732405], [29547, 0.00512893658090305], [29561, 0.005056540848034134], [29575, 0.00431147373754637], [29603, 0.0042150424814493175], [29617, 0.0039376657678875625], [29631, 0.004187927524780182], [29645, 0.004237624357959591], [29659, 0.0041988230537733495], [29673, 0.004134826025567282], [29743, 0.0040917590526156535], [29757, 0.004316233473139346], [29771, 0.004292399221888748], [29785, 0.004618753633266735], [29799, 0.004639436503190454], [29813, 0.004542088391054112], [29827, 0.004884748699273233], [29841, 0.004667408316355733], [29855, 0.0044618927445945165], [29869, 0.004590008482759937], [30009, 0.004545743974619372], [30023, 0.004767518598419665], [30037, 0.004657723767683867], [30051, 0.004601966497433438], [30065, 0.004650947169666352], [30079, 0.004588257868667346], [30093, 0.004734924548166642], [30107, 0.004441999158338927], [30121, 0.004749195439649348], [30135, 0.004759361438136572], [30149, 0.004810026318427689], [30163, 0.004802058311775599], [30177, 0.004797513439886396], [30191, 0.004805343733493128], [30205, 0.004524943674953184], [30219, 0.004834056860062713], [30233, 0.004605831652319058], [30247, 0.004609843408927179], [30261, 0.004517083344972963], [30513, 0.004566017442939815], [30527, 0.004758443732616452], [30541, 0.004576345572891965], [30555, 0.004702791300006378], [30569, 0.004617697986725454], [30583, 0.004770065171979221], [30597, 0.004598942659276678], [30625, 0.004439937234153428], [30639, 0.004470476216554178], [30653, 0.004643831354544178], [30667, 0.004833232122016981], [30681, 0.00465787589854482], [30695, 0.005073268560640968], [30709, 0.004541035009000586], [30723, 0.004721904911264465], [30737, 0.004718753625612261], [30751, 0.004884745239591722], [30765, 0.004544986171401859], [30779, 0.004877917796789273], [30793, 0.004595827449112126], [30807, 0.00464898135092397], [30821, 0.004462572657782977], [30835, 0.00475826282520608], [30849, 0.0045634487783408], [30863, 0.00453240459899477], [30877, 0.0045638732029182946], [30891, 0.004728563105665274], [30905, 0.004841088057475155], [30919, 0.004587004428694247], [30933, 0.004492735658183788], [30947, 0.00457490680687248], [30961, 0.004636838818538364], [30975, 0.004589607582374559], [30989, 0.0048393767369458735], [31003, 0.004452483706487288], [31017, 0.005139350052110729], [31031, 0.004591356786754843], [31045, 0.004764606701174878], [32095, 0.00400806226949959], [32109, 0.004065551020128831], [32123, 0.004078957272697788], [32137, 0.003931540196296821], [32151, 0.004281051414381124], [32165, 0.0041495165394893315], [32179, 0.004089495007818861], [32193, 0.003911869317626896], [32207, 0.004107062289714496], [32221, 0.004171456528936719], [32235, 0.0040338956820321886], [32249, 0.004147407854952483], [32263, 0.004273612068747809], [32277, 0.004081254371365761], [32305, 0.004118681756675107], [32319, 0.004155430413280696], [32333, 0.0042337468428350535], [32347, 0.00429827897128819], [32361, 0.0041309726801151345], [32375, 0.004161638316535083], [32389, 0.003973560797719568], [32403, 0.004180269414596809], [32417, 0.004486404821981445], [32431, 0.004063831261327217], [32445, 0.004222795673158852], [32585, 0.0039435204996738716], [32599, 0.00416790529142031], [32613, 0.0038533916822508472], [32627, 0.0040364545502531825], [32641, 0.003906603105039203], [32655, 0.00404689958031906], [32851, 0.004015021787942147], [32865, 0.003945988783621916], [32879, 0.003962688027515429], [32893, 0.003999366582082571], [32907, 0.0041072671815880635], [32921, 0.003954040679439733], [32991, 0.004006770692077466], [33005, 0.004134488656824124], [33019, 0.003918700539080694], [33033, 0.0040139053024830906], [33047, 0.004188385057173512], [33061, 0.003995383394893472], [33075, 0.004122538862625798], [33089, 0.004004201267211566], [33103, 0.004181445901327696], [33117, 0.0038659891464983094], [33131, 0.004115350965059614], [33145, 0.0038972655340831796], [33159, 0.00401143749946991], [33187, 0.0041917619670325855], [33201, 0.0040955799500291806], [33215, 0.004175081961557886], [33229, 0.004615323087750372], [33243, 0.004511164352717025], [33271, 0.004764520601216743], [33299, 0.005246522134057713], [33313, 0.004936737299190701], [33327, 0.004775385359921363], [33341, 0.00476980926773858], [33355, 0.005051703956058722], [33369, 0.004815012878072401], [33383, 0.004949517608935406], [33397, 0.0048585214492898755], [33411, 0.004548907390142052], [33425, 0.0046461061527304035], [33439, 0.005137893661175301], [33453, 0.004961552564500937], [33467, 0.0047323970444961725], [33523, 0.004722305669109982], [33537, 0.004918633349290303], [33551, 0.004821285352441618], [33649, 0.004782164696561316], [33705, 0.00473756314315295], [33719, 0.004695196736997171], [33733, 0.004120838684084699], [33747, 0.004169309511066945], [33761, 0.00416095101525671], [33775, 0.004592442840437661], [33803, 0.004082514323318309], [33817, 0.0042317013672149035], [33831, 0.00419215202118297], [33845, 0.00382416822037819], [34041, 0.004081395596235658], [34055, 0.004048275233115977], [34069, 0.004189463968509983], [34083, 0.004183904606944299], [34125, 0.003999905500539337], [34139, 0.004021847917616697], [34153, 0.003944874733634544], [34167, 0.0039918484816180285]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LogisticRegressionBenchmark.track_test_score.json b/graphs/summary/linear_model.LogisticRegressionBenchmark.track_test_score.json index 58548ad9c5..0884b95463 100644 --- a/graphs/summary/linear_model.LogisticRegressionBenchmark.track_test_score.json +++ b/graphs/summary/linear_model.LogisticRegressionBenchmark.track_test_score.json @@ -1 +1 @@ -[[28511, 0.7148723373040053], [29225, 0.7104671194181618], [29239, 0.7123406393089862], [29253, 0.7127618934701903], [29267, 0.7124890126436767], [29281, 0.7132431859574727], [29295, 0.7125645627227004], [29309, 0.7132268787050842], [29323, 0.7109973325236796], [29337, 0.7107276632526428], [29351, 0.7137257718819042], [29365, 0.7157197806901316], [29379, 0.711295151734791], [29393, 0.7147276783505502], [29407, 0.7145990925955611], [29421, 0.712142540535229], [29435, 0.7132500484688883], [29449, 0.7129141084791262], [29463, 0.7123699679688843], [29477, 0.7152047561729259], [29547, 0.7118261873383477], [29561, 0.7110184110911503], [29575, 0.7118124850667946], [29603, 0.7133429947004757], [29617, 0.7104101451647369], [29631, 0.7131621742313101], [29645, 0.7120506409599343], [29659, 0.7119196771603973], [29673, 0.712396191233395], [29743, 0.7146191011605146], [29757, 0.7146134686739396], [29771, 0.7134320241542387], [29785, 0.711645911166763], [29799, 0.7120264413321142], [29813, 0.7127534641038091], [29827, 0.7143106080446332], [29841, 0.7105367748310243], [29855, 0.7093123431862726], [29869, 0.7126279663295207], [30009, 0.7121973264708233], [30023, 0.710788241891134], [30037, 0.7127032999015434], [30051, 0.7138174643873476], [30065, 0.7119543253454047], [30079, 0.7134306371049207], [30093, 0.7106222794072632], [30107, 0.7125739048177365], [30121, 0.7134934899241087], [30135, 0.7132387964677712], [30149, 0.7125826819908343], [30163, 0.7109992686719471], [30177, 0.7136337318666255], [30191, 0.7104408041714442], [30205, 0.7112365967566016], [30219, 0.7129269525215509], [30233, 0.7130510786179083], [30247, 0.7121775758680716], [30261, 0.7130284503691673], [30513, 0.712000582957326], [30527, 0.7141173823976918], [30541, 0.7137652705499519], [30555, 0.7118025072880227], [30569, 0.7126845517597669], [30583, 0.7108706220205505], [30597, 0.7128378473469822], [30625, 0.7133960175966872], [30639, 0.7140001826349154], [30653, 0.7126434733859627], [30667, 0.7131104168325579], [30681, 0.7114285451951271], [30695, 0.7138379412784184], [30709, 0.7116197453097706], [30723, 0.7110828278757436], [30737, 0.7127876579237906], [30751, 0.7133113993829128], [30765, 0.7118203371020956], [30779, 0.7153914668023675], [30793, 0.7097744243254502], [30807, 0.7130650726748373], [30821, 0.7134579925600547], [30835, 0.708585653751415], [30849, 0.713069072589857], [30863, 0.7121076594522849], [30877, 0.7122473042231281], [30891, 0.7111104862901964], [30905, 0.7140387084665226], [30919, 0.7138066959992049], [30933, 0.7091561441627877], [30947, 0.7111245535410873], [30961, 0.711141981840503], [30975, 0.7140928421088719], [30989, 0.7104443852448984], [31003, 0.7138936568840549], [31017, 0.7116280274355214], [31031, 0.7110899109081472], [31045, 0.7130985118579146], [32095, 0.7132009730693568], [32109, 0.7123300613448107], [32123, 0.7109717798285603], [32137, 0.7108718159491024], [32151, 0.7109130708932287], [32165, 0.7142636768816264], [32179, 0.7123623242649393], [32193, 0.7120003673635479], [32207, 0.7139166353899485], [32221, 0.7141160682147296], [32235, 0.7107105417275709], [32249, 0.7083610898531756], [32263, 0.7118877854318855], [32277, 0.7104103862572503], [32305, 0.7134489724389655], [32319, 0.7101280232088419], [32333, 0.7143000077140587], [32347, 0.7145286026095341], [32361, 0.7135554855639687], [32375, 0.7138330528360934], [32389, 0.7146325907735183], [32403, 0.7111306119734238], [32417, 0.7124705281552132], [32431, 0.711914701120663], [32445, 0.713550939691927], [32585, 0.7124829743200255], [32599, 0.713149639888296], [32613, 0.7121672281183257], [32627, 0.7143644427512071], [32641, 0.7110892345679549], [32655, 0.7106376640475799], [32851, 0.7135832680044677], [32865, 0.7117284194999031], [32879, 0.7120508524226628], [32893, 0.7152100938827349], [32907, 0.7131708676185188], [32921, 0.7130630916792735], [32991, 0.7133383398506485], [33005, 0.7122492864044739], [33019, 0.7114729879250251], [33033, 0.7130257641850325], [33047, 0.7120814435914131], [33061, 0.7142618152155611], [33075, 0.7129320517284182], [33089, 0.7113479809636676], [33103, 0.7122150297222246], [33117, 0.7123491638833713], [33131, 0.7122117170647089], [33145, 0.7079183615822562], [33159, 0.7143376897158943], [33187, 0.7128520960835203], [33201, 0.7140151848121925], [33215, 0.7144225743795517], [33229, 0.714453288074408], [33243, 0.7124454022604509], [33271, 0.7132176259206178], [33299, 0.709954998644352], [33313, 0.7123488076016581], [33327, 0.7141236937152464], [33341, 0.7109132576612516], [33355, 0.7129104918355381], [33369, 0.7128973675771366], [33383, 0.7147906751575709], [33397, 0.7130378042684279], [33411, 0.7125228615575374], [33425, 0.7120296657652939], [33439, 0.7124287001708403], [33453, 0.7147924141150326], [33467, 0.7122311142644819], [33523, 0.7129093364583168], [33537, 0.7117536684140622], [33551, 0.7117277206344007], [33649, 0.7142121352542478], [33705, 0.7112688677580684], [33719, 0.7123314467380344], [33733, 0.7125715512301866], [33747, 0.712253968032343], [33761, 0.7125820289010845], [33775, 0.711196672483869], [33803, 0.7096484073236038], [33817, 0.7122410149405303], [33831, 0.7135921535305814], [33845, 0.7126630388413958], [34041, 0.7122775093380993], [34055, 0.7129811569227845], [34069, 0.7101665268047537], [34083, 0.711619484190308], [34125, 0.2674543471316951], [34139, 0.26781248293801285], [34153, 0.2666456196610909], [34167, 0.2669576128892149]] \ No newline at end of file +[[28511, 0.7148723373040053], [29225, 0.7104671194181618], [29239, 0.7123406393089862], [29253, 0.7127618934701903], [29267, 0.7124890126436767], [29281, 0.7132431859574727], [29295, 0.7125645627227004], [29309, 0.7132268787050842], [29323, 0.7109973325236796], [29337, 0.7107276632526428], [29351, 0.7137257718819042], [29365, 0.7157197806901316], [29379, 0.711295151734791], [29393, 0.7147276783505502], [29407, 0.7145990925955611], [29421, 0.712142540535229], [29435, 0.7132500484688883], [29449, 0.7129141084791262], [29463, 0.7123699679688843], [29477, 0.7152047561729259], [29547, 0.7118261873383477], [29561, 0.7110184110911503], [29575, 0.7118124850667946], [29603, 0.7133429947004757], [29617, 0.7104101451647369], [29631, 0.7131621742313101], [29645, 0.7120506409599343], [29659, 0.7119196771603973], [29673, 0.712396191233395], [29743, 0.7146191011605146], [29757, 0.7146134686739396], [29771, 0.7134320241542387], [29785, 0.711645911166763], [29799, 0.7120264413321142], [29813, 0.7127534641038091], [29827, 0.7143106080446332], [29841, 0.7105367748310243], [29855, 0.7093123431862726], [29869, 0.7126279663295207], [30009, 0.7121973264708233], [30023, 0.710788241891134], [30037, 0.7127032999015434], [30051, 0.7138174643873476], [30065, 0.7119543253454047], [30079, 0.7134306371049207], [30093, 0.7106222794072632], [30107, 0.7125739048177365], [30121, 0.7134934899241087], [30135, 0.7132387964677712], [30149, 0.7125826819908343], [30163, 0.7109992686719471], [30177, 0.7136337318666255], [30191, 0.7104408041714442], [30205, 0.7112365967566016], [30219, 0.7129269525215509], [30233, 0.7130510786179083], [30247, 0.7121775758680716], [30261, 0.7130284503691673], [30513, 0.712000582957326], [30527, 0.7141173823976918], [30541, 0.7137652705499519], [30555, 0.7118025072880227], [30569, 0.7126845517597669], [30583, 0.7108706220205505], [30597, 0.7128378473469822], [30625, 0.7133960175966872], [30639, 0.7140001826349154], [30653, 0.7126434733859627], [30667, 0.7131104168325579], [30681, 0.7114285451951271], [30695, 0.7138379412784184], [30709, 0.7116197453097706], [30723, 0.7110828278757436], [30737, 0.7127876579237906], [30751, 0.7133113993829128], [30765, 0.7118203371020956], [30779, 0.7153914668023675], [30793, 0.7097744243254502], [30807, 0.7130650726748373], [30821, 0.7134579925600547], [30835, 0.708585653751415], [30849, 0.713069072589857], [30863, 0.7121076594522849], [30877, 0.7122473042231281], [30891, 0.7111104862901964], [30905, 0.7140387084665226], [30919, 0.7138066959992049], [30933, 0.7091561441627877], [30947, 0.7111245535410873], [30961, 0.711141981840503], [30975, 0.7140928421088719], [30989, 0.7104443852448984], [31003, 0.7138936568840549], [31017, 0.7116280274355214], [31031, 0.7110899109081472], [31045, 0.7130985118579146], [32095, 0.7132009730693568], [32109, 0.7123300613448107], [32123, 0.7109717798285603], [32137, 0.7108718159491024], [32151, 0.7109130708932287], [32165, 0.7142636768816264], [32179, 0.7123623242649393], [32193, 0.7120003673635479], [32207, 0.7139166353899485], [32221, 0.7141160682147296], [32235, 0.7107105417275709], [32249, 0.7083610898531756], [32263, 0.7118877854318855], [32277, 0.7104103862572503], [32305, 0.7134489724389655], [32319, 0.7101280232088419], [32333, 0.7143000077140587], [32347, 0.7145286026095341], [32361, 0.7135554855639687], [32375, 0.7138330528360934], [32389, 0.7146325907735183], [32403, 0.7111306119734238], [32417, 0.7124705281552132], [32431, 0.711914701120663], [32445, 0.713550939691927], [32585, 0.7124829743200255], [32599, 0.713149639888296], [32613, 0.7121672281183257], [32627, 0.7143644427512071], [32641, 0.7110892345679549], [32655, 0.7106376640475799], [32851, 0.7135832680044677], [32865, 0.7117284194999031], [32879, 0.7120508524226628], [32893, 0.7152100938827349], [32907, 0.7131708676185188], [32921, 0.7130630916792735], [32991, 0.7133383398506485], [33005, 0.7122492864044739], [33019, 0.7114729879250251], [33033, 0.7130257641850325], [33047, 0.7120814435914131], [33061, 0.7142618152155611], [33075, 0.7129320517284182], [33089, 0.7113479809636676], [33103, 0.7122150297222246], [33117, 0.7123491638833713], [33131, 0.7122117170647089], [33145, 0.7079183615822562], [33159, 0.7143376897158943], [33187, 0.7128520960835203], [33201, 0.7140151848121925], [33215, 0.7144225743795517], [33229, 0.714453288074408], [33243, 0.7124454022604509], [33271, 0.7132176259206178], [33299, 0.709954998644352], [33313, 0.7123488076016581], [33327, 0.7141236937152464], [33341, 0.7109132576612516], [33355, 0.7129104918355381], [33369, 0.7128973675771366], [33383, 0.7147906751575709], [33397, 0.7130378042684279], [33411, 0.7125228615575374], [33425, 0.7120296657652939], [33439, 0.7124287001708403], [33453, 0.7147924141150326], [33467, 0.7122311142644819], [33523, 0.7129093364583168], [33537, 0.7117536684140622], [33551, 0.7117277206344007], [33649, 0.7142121352542478], [33705, 0.7112688677580684], [33719, 0.7123314467380344], [33733, 0.7125715512301866], [33747, 0.712253968032343], [33761, 0.7125820289010845], [33775, 0.711196672483869], [33803, 0.7096484073236038], [33817, 0.7122410149405303], [33831, 0.7135921535305814], [33845, 0.7126630388413958], [34041, 0.7122775093380993], [34055, 0.7129811569227845], [34069, 0.7101665268047537], [34083, 0.711619484190308], [34125, 0.2674543471316951], [34139, 0.26781248293801285], [34153, 0.2666456196610909], [34167, 0.2670942784792445]] \ No newline at end of file diff --git a/graphs/summary/linear_model.LogisticRegressionBenchmark.track_train_score.json b/graphs/summary/linear_model.LogisticRegressionBenchmark.track_train_score.json index e168b7cee7..162f96b683 100644 --- a/graphs/summary/linear_model.LogisticRegressionBenchmark.track_train_score.json +++ b/graphs/summary/linear_model.LogisticRegressionBenchmark.track_train_score.json @@ -1 +1 @@ -[[28511, 0.8042877152343607], [29225, 0.8050934201668343], [29239, 0.8044898560418116], [29253, 0.8041005224108747], [29267, 0.8044382176367346], [29281, 0.8048403227114933], [29295, 0.8040769794292357], [29309, 0.8058811333863221], [29323, 0.8039131508333268], [29337, 0.8039444472384201], [29351, 0.8041451326259486], [29365, 0.8056635943105478], [29379, 0.8052270322701044], [29393, 0.8042564635502192], [29407, 0.8040112728371853], [29421, 0.8044336178881787], [29435, 0.8041295858750827], [29449, 0.8039778388701685], [29463, 0.8039309232567824], [29477, 0.8033745461743818], [29547, 0.8026734357276983], [29561, 0.8047784361423473], [29575, 0.8066372498225912], [29603, 0.8041228112261604], [29617, 0.8044002243056134], [29631, 0.803136603652527], [29645, 0.8036888241748257], [29659, 0.8040019463607297], [29673, 0.8035331640920621], [29743, 0.8039547191329937], [29757, 0.8039488637842226], [29771, 0.8045905360174335], [29785, 0.8034102009069193], [29799, 0.8043865780442182], [29813, 0.8042764878677722], [29827, 0.8044433789192416], [29841, 0.8047028379262934], [29855, 0.8038064802862184], [29869, 0.8059796308399719], [30009, 0.804490507358106], [30023, 0.8037327091059482], [30037, 0.804035842761603], [30051, 0.8048673787736923], [30065, 0.8039783504156984], [30079, 0.8045545575563391], [30093, 0.8039139619454094], [30107, 0.8045019406252538], [30121, 0.8046508477842672], [30135, 0.8045825006533149], [30149, 0.8033870694867906], [30163, 0.8042163045212015], [30177, 0.8044914086863347], [30191, 0.8035248229228364], [30205, 0.8044655531541646], [30219, 0.8042038225723033], [30233, 0.8044893645072473], [30247, 0.804487427627986], [30261, 0.8037321038492455], [30513, 0.8040373094161939], [30527, 0.805038303716216], [30541, 0.8039135475153029], [30555, 0.8040964764569593], [30569, 0.8042478896842333], [30583, 0.8054039716433183], [30597, 0.8042412365440383], [30625, 0.8042992128791383], [30639, 0.8039876351026412], [30653, 0.8044159152762532], [30667, 0.8036230440591325], [30681, 0.8046896755682532], [30695, 0.8041126303915233], [30709, 0.8030692595774984], [30723, 0.8040762325495006], [30737, 0.8040765494621583], [30751, 0.8042303157799233], [30765, 0.8038456119702827], [30779, 0.804054477618942], [30793, 0.8041655365641884], [30807, 0.8042226975980296], [30821, 0.8050577073276427], [30835, 0.8042266239019618], [30849, 0.8039203799731064], [30863, 0.8043088746884526], [30877, 0.8049766664316186], [30891, 0.8043156458340006], [30905, 0.8062904009771108], [30919, 0.805088893054756], [30933, 0.8042016839877344], [30947, 0.8049698361510336], [30961, 0.8035541686640791], [30975, 0.8047685533437297], [30989, 0.8033870013279465], [31003, 0.8042209041493007], [31017, 0.8037001971233046], [31031, 0.8049852612574401], [31045, 0.8038711520599855], [32095, 0.8033301190631472], [32109, 0.8050648149632917], [32123, 0.8044965056555856], [32137, 0.8047249750335954], [32151, 0.8042222162157355], [32165, 0.8043824873987236], [32179, 0.8040238830393226], [32193, 0.8039651631975636], [32207, 0.8037755933319416], [32221, 0.8041825175920931], [32235, 0.8022181431080634], [32249, 0.8030985271391887], [32263, 0.804671292647232], [32277, 0.803526167934382], [32305, 0.8047924451397969], [32319, 0.8040110388910602], [32333, 0.8044067588662162], [32347, 0.80500246044083], [32361, 0.8041923516900129], [32375, 0.8063247413929485], [32389, 0.805832809153991], [32403, 0.8044154960601164], [32417, 0.8034491020284761], [32431, 0.8042401062845816], [32445, 0.8044023692575557], [32585, 0.8041877629821238], [32599, 0.804164310582058], [32613, 0.8039169677821603], [32627, 0.8036745869222507], [32641, 0.8040336665109507], [32655, 0.8045800989884165], [32851, 0.8054204668679449], [32865, 0.8037307788646102], [32879, 0.8036328340703144], [32893, 0.8036118401643266], [32907, 0.8035486152396064], [32921, 0.8033976829847906], [32991, 0.8046850313074252], [33005, 0.8037346617941664], [33019, 0.80315588743652], [33033, 0.804678897979324], [33047, 0.8017516225323513], [33061, 0.8048479302216835], [33075, 0.8048575882355355], [33089, 0.8037039606357783], [33103, 0.8041959419462247], [33117, 0.8036083896863148], [33131, 0.804041353083982], [33145, 0.8034524298244842], [33159, 0.8052050364646947], [33187, 0.8061601720247398], [33201, 0.80488582379067], [33215, 0.8040813336085277], [33229, 0.8037592287113396], [33243, 0.8047120346607959], [33271, 0.8038643587004304], [33299, 0.8041835808862503], [33313, 0.8041682433506886], [33327, 0.8035948806691715], [33341, 0.8041535345912874], [33355, 0.8046255376552117], [33369, 0.8038842291867839], [33383, 0.8047037068015852], [33397, 0.8047874397393875], [33411, 0.8051917287512532], [33425, 0.8053498126837035], [33439, 0.8046310041886973], [33453, 0.8052728262330482], [33467, 0.8043022646570149], [33523, 0.8044263677254648], [33537, 0.8054996171410761], [33551, 0.803474685030536], [33649, 0.8045027989535667], [33705, 0.8046168409332701], [33719, 0.803793590031559], [33733, 0.8037928147405908], [33747, 0.8045383588249724], [33761, 0.8046929998356191], [33775, 0.8055621069573273], [33803, 0.8036499536831205], [33817, 0.8046620378831415], [33831, 0.8050959858793149], [33845, 0.804581856029855], [34041, 0.8046143538787958], [34055, 0.8034937145143443], [34069, 0.8041735188344029], [34083, 0.8040714007169587], [34125, 0.28639068007201146], [34139, 0.2871648952031764], [34153, 0.2868010362679643], [34167, 0.2864495065351701]] \ No newline at end of file +[[28511, 0.8042877152343607], [29225, 0.8050934201668343], [29239, 0.8044898560418116], [29253, 0.8041005224108747], [29267, 0.8044382176367346], [29281, 0.8048403227114933], [29295, 0.8040769794292357], [29309, 0.8058811333863221], [29323, 0.8039131508333268], [29337, 0.8039444472384201], [29351, 0.8041451326259486], [29365, 0.8056635943105478], [29379, 0.8052270322701044], [29393, 0.8042564635502192], [29407, 0.8040112728371853], [29421, 0.8044336178881787], [29435, 0.8041295858750827], [29449, 0.8039778388701685], [29463, 0.8039309232567824], [29477, 0.8033745461743818], [29547, 0.8026734357276983], [29561, 0.8047784361423473], [29575, 0.8066372498225912], [29603, 0.8041228112261604], [29617, 0.8044002243056134], [29631, 0.803136603652527], [29645, 0.8036888241748257], [29659, 0.8040019463607297], [29673, 0.8035331640920621], [29743, 0.8039547191329937], [29757, 0.8039488637842226], [29771, 0.8045905360174335], [29785, 0.8034102009069193], [29799, 0.8043865780442182], [29813, 0.8042764878677722], [29827, 0.8044433789192416], [29841, 0.8047028379262934], [29855, 0.8038064802862184], [29869, 0.8059796308399719], [30009, 0.804490507358106], [30023, 0.8037327091059482], [30037, 0.804035842761603], [30051, 0.8048673787736923], [30065, 0.8039783504156984], [30079, 0.8045545575563391], [30093, 0.8039139619454094], [30107, 0.8045019406252538], [30121, 0.8046508477842672], [30135, 0.8045825006533149], [30149, 0.8033870694867906], [30163, 0.8042163045212015], [30177, 0.8044914086863347], [30191, 0.8035248229228364], [30205, 0.8044655531541646], [30219, 0.8042038225723033], [30233, 0.8044893645072473], [30247, 0.804487427627986], [30261, 0.8037321038492455], [30513, 0.8040373094161939], [30527, 0.805038303716216], [30541, 0.8039135475153029], [30555, 0.8040964764569593], [30569, 0.8042478896842333], [30583, 0.8054039716433183], [30597, 0.8042412365440383], [30625, 0.8042992128791383], [30639, 0.8039876351026412], [30653, 0.8044159152762532], [30667, 0.8036230440591325], [30681, 0.8046896755682532], [30695, 0.8041126303915233], [30709, 0.8030692595774984], [30723, 0.8040762325495006], [30737, 0.8040765494621583], [30751, 0.8042303157799233], [30765, 0.8038456119702827], [30779, 0.804054477618942], [30793, 0.8041655365641884], [30807, 0.8042226975980296], [30821, 0.8050577073276427], [30835, 0.8042266239019618], [30849, 0.8039203799731064], [30863, 0.8043088746884526], [30877, 0.8049766664316186], [30891, 0.8043156458340006], [30905, 0.8062904009771108], [30919, 0.805088893054756], [30933, 0.8042016839877344], [30947, 0.8049698361510336], [30961, 0.8035541686640791], [30975, 0.8047685533437297], [30989, 0.8033870013279465], [31003, 0.8042209041493007], [31017, 0.8037001971233046], [31031, 0.8049852612574401], [31045, 0.8038711520599855], [32095, 0.8033301190631472], [32109, 0.8050648149632917], [32123, 0.8044965056555856], [32137, 0.8047249750335954], [32151, 0.8042222162157355], [32165, 0.8043824873987236], [32179, 0.8040238830393226], [32193, 0.8039651631975636], [32207, 0.8037755933319416], [32221, 0.8041825175920931], [32235, 0.8022181431080634], [32249, 0.8030985271391887], [32263, 0.804671292647232], [32277, 0.803526167934382], [32305, 0.8047924451397969], [32319, 0.8040110388910602], [32333, 0.8044067588662162], [32347, 0.80500246044083], [32361, 0.8041923516900129], [32375, 0.8063247413929485], [32389, 0.805832809153991], [32403, 0.8044154960601164], [32417, 0.8034491020284761], [32431, 0.8042401062845816], [32445, 0.8044023692575557], [32585, 0.8041877629821238], [32599, 0.804164310582058], [32613, 0.8039169677821603], [32627, 0.8036745869222507], [32641, 0.8040336665109507], [32655, 0.8045800989884165], [32851, 0.8054204668679449], [32865, 0.8037307788646102], [32879, 0.8036328340703144], [32893, 0.8036118401643266], [32907, 0.8035486152396064], [32921, 0.8033976829847906], [32991, 0.8046850313074252], [33005, 0.8037346617941664], [33019, 0.80315588743652], [33033, 0.804678897979324], [33047, 0.8017516225323513], [33061, 0.8048479302216835], [33075, 0.8048575882355355], [33089, 0.8037039606357783], [33103, 0.8041959419462247], [33117, 0.8036083896863148], [33131, 0.804041353083982], [33145, 0.8034524298244842], [33159, 0.8052050364646947], [33187, 0.8061601720247398], [33201, 0.80488582379067], [33215, 0.8040813336085277], [33229, 0.8037592287113396], [33243, 0.8047120346607959], [33271, 0.8038643587004304], [33299, 0.8041835808862503], [33313, 0.8041682433506886], [33327, 0.8035948806691715], [33341, 0.8041535345912874], [33355, 0.8046255376552117], [33369, 0.8038842291867839], [33383, 0.8047037068015852], [33397, 0.8047874397393875], [33411, 0.8051917287512532], [33425, 0.8053498126837035], [33439, 0.8046310041886973], [33453, 0.8052728262330482], [33467, 0.8043022646570149], [33523, 0.8044263677254648], [33537, 0.8054996171410761], [33551, 0.803474685030536], [33649, 0.8045027989535667], [33705, 0.8046168409332701], [33719, 0.803793590031559], [33733, 0.8037928147405908], [33747, 0.8045383588249724], [33761, 0.8046929998356191], [33775, 0.8055621069573273], [33803, 0.8036499536831205], [33817, 0.8046620378831415], [33831, 0.8050959858793149], [33845, 0.804581856029855], [34041, 0.8046143538787958], [34055, 0.8034937145143443], [34069, 0.8041735188344029], [34083, 0.8040714007169587], [34125, 0.28639068007201146], [34139, 0.2871648952031764], [34153, 0.2868010362679643], [34167, 0.28650313678848793]] \ No newline at end of file diff --git a/graphs/summary/linear_model.RidgeBenchmark.peakmem_fit.json b/graphs/summary/linear_model.RidgeBenchmark.peakmem_fit.json index 6025aac635..fb14e86f98 100644 --- a/graphs/summary/linear_model.RidgeBenchmark.peakmem_fit.json +++ b/graphs/summary/linear_model.RidgeBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28497, 363054369.2191392], [29215, 359164934.2771482], [29225, 359800638.06228423], [29227, 360514117.7164347], [29228, 359282909.5242869], [29229, 360013003.5243189], [29235, 360457161.4357038], [29240, 360108258.87493837], [29245, 361121101.9366862], [29246, 360936649.7000913], [29258, 361266930.59624326], [29262, 361134394.1320998], [29279, 361252127.43771815], [29286, 361041551.72556394], [29293, 361044306.55251914], [29294, 360829624.966645], [29295, 360717272.25772864], [29296, 361529184.4202655], [29313, 361089314.802524], [29318, 361301853.79122823], [29319, 361130161.36241764], [29322, 361168114.78717595], [29325, 361738622.33141494], [29327, 361470629.51871145], [29328, 361357749.0570621], [29340, 360777580.70131963], [29344, 359930719.8677546], [29349, 360207528.3336454], [29364, 360221381.64289135], [29371, 360833666.08063483], [29376, 360639466.89683336], [29381, 360381236.7762184], [29383, 360802435.4267732], [29387, 360878184.9905306], [29401, 360064742.9309108], [29404, 360842549.1622037], [29409, 360669862.6005588], [29414, 359760000.1991326], [29415, 360217106.71407515], [29420, 360219880.9998095], [29421, 360753244.92251074], [29425, 360957795.1572051], [29429, 361172828.37313503], [29435, 360570141.9433113], [29443, 360423442.93394357], [29446, 360517461.97813106], [29453, 360076373.81835234], [29454, 360346021.937626], [29455, 360291831.3123189], [29457, 360238487.2282543], [29458, 360679193.8335376], [29469, 360318123.7491145], [29541, 360713417.0016813], [29548, 360262617.74429137], [29550, 360415759.4440005], [29551, 360946690.904145], [29572, 359923850.1732528], [29591, 360435898.34645826], [29598, 360062991.7733901], [29609, 360492325.0429151], [29611, 360125053.2025992], [29621, 360478606.5661861], [29638, 360492878.2639576], [29644, 360755974.8844076], [29648, 360565888.51579714], [29652, 360642636.6197926], [29656, 360602485.66541034], [29657, 360084476.9689012], [29662, 360233646.989097], [29665, 360635785.86225325], [29667, 360291493.96249413], [29735, 360317879.44218403], [29742, 360506636.1933438], [29750, 360475600.01733756], [29753, 360596102.80617666], [29757, 360315098.9688083], [29761, 360184787.3841716], [29765, 360815128.1849716], [29766, 360619171.2074683], [29768, 360471090.38907045], [29776, 360399630.5585596], [29783, 360573154.48446876], [29788, 360301428.8507548], [29789, 360653530.1047434], [29790, 360466394.82107437], [29795, 360513329.4597986], [29798, 360778495.48859453], [29805, 360886466.61620706], [29806, 360595770.5412676], [29807, 360493272.4116185], [29808, 360442350.8431877], [29813, 360744700.5876916], [29815, 360762651.6057989], [29828, 360429984.9108294], [29839, 360532084.3697515], [29844, 360405510.6416504], [29858, 360598586.77512467], [29865, 361168214.4124273], [29999, 360658570.26111186], [30002, 360422940.3133238], [30010, 360766535.63012797], [30013, 360585350.0085867], [30023, 360308493.9917997], [30028, 360464716.5646204], [30035, 360603639.31366193], [30046, 360804542.88969254], [30053, 360651066.2516552], [30066, 360550717.2508093], [30068, 360554302.06808615], [30070, 360765826.33519125], [30074, 360688475.0988678], [30076, 360583252.46979314], [30077, 360830254.18497384], [30078, 360730852.8122437], [30085, 360704773.46127236], [30086, 360472115.44270194], [30096, 360437692.3813615], [30104, 360765429.5121153], [30106, 360735243.66268235], [30112, 361230209.14750177], [30116, 360819164.1569858], [30118, 360479062.88550824], [30123, 360618933.170527], [30128, 360712493.2824262], [30135, 361298944.6359747], [30145, 361251375.53313404], [30155, 361003632.77297306], [30156, 361098353.2191081], [30157, 361074991.3058972], [30165, 361265821.5541183], [30174, 361172095.71709085], [30179, 361025740.95844126], [30185, 361476649.97369576], [30189, 361223057.7633353], [30190, 361248053.55001664], [30198, 361262809.9873703], [30202, 361593559.1844232], [30203, 361025363.89885694], [30208, 361419037.8313204], [30212, 361069564.96903515], [30213, 360956256.8331483], [30215, 361490025.47946954], [30218, 361370893.0204133], [30225, 360971189.72095513], [30227, 360936686.12868583], [30233, 361205091.0923818], [30235, 361122701.7901613], [30238, 361066843.7836295], [30244, 361142354.2467124], [30248, 361157263.3768945], [30254, 360636744.07146066], [30259, 361215315.94095933], [30260, 361073071.63664776], [30501, 361514199.13010144], [30502, 361483148.60713184], [30506, 361546456.7466552], [30507, 361539043.1476933], [30510, 361456989.458338], [30515, 360956676.3764039], [30519, 361235596.6422021], [30520, 361158368.5177364], [30524, 361165066.27265924], [30525, 361455263.2816658], [30529, 361381944.7731546], [30533, 360764163.41892946], [30538, 360966399.1021395], [30542, 361013364.20290995], [30543, 361004601.2296973], [30544, 361512679.17822105], [30545, 360618530.2469018], [30550, 361055198.3438969], [30552, 360515458.2131457], [30556, 360667500.47630143], [30561, 360878970.17597973], [30564, 361130412.60216], [30565, 361026813.8078623], [30577, 361067053.5731284], [30581, 361167379.86367935], [30586, 360903897.5441536], [30593, 360949894.00646937], [30615, 360796748.5875195], [30621, 361176314.6107146], [30622, 361270383.2827531], [30629, 361131139.948447], [30635, 361287854.7617296], [30639, 360832214.03788453], [30640, 360894898.8344037], [30643, 361069357.22959536], [30646, 361010403.381163], [30647, 360865058.12351257], [30650, 360804347.694636], [30657, 360855311.0748219], [30665, 361119567.1955379], [30670, 360657168.00715], [30675, 361136654.16188836], [30679, 360845069.6013101], [30694, 361070865.3968474], [30704, 361121909.7952233], [30708, 360930950.62540466], [30718, 360979554.09432614], [30723, 361291189.0497843], [30729, 361078107.1944605], [30730, 360709545.8601283], [30734, 360799271.5860939], [30739, 361373514.05867606], [30744, 360755782.33141994], [30748, 361083044.15261084], [30750, 361192648.24971634], [30754, 361086326.53907275], [30761, 361755023.27614796], [30762, 361572127.9914095], [30777, 360878136.1863476], [30782, 360678512.066514], [30785, 361045251.8578509], [30787, 361286026.76381093], [30794, 360796612.7248674], [30804, 361016576.6022369], [30812, 361305650.65304726], [30817, 361354498.7749726], [30821, 361267336.1351059], [30838, 361230433.59095675], [30849, 360992061.5227886], [30861, 361115509.04143584], [30868, 361314857.2673176], [30872, 361363757.8426736], [30890, 361427433.91236705], [30904, 361480989.460689], [30907, 361311329.04242915], [30908, 361287289.10858697], [30917, 360865417.6389384], [30928, 361346538.1926865], [30931, 361260386.1956427], [30938, 361092470.18013954], [30945, 361459043.8593052], [30949, 361289915.8538544], [30955, 361179442.5488214], [30957, 361525855.3085044], [30967, 361543566.46677744], [30974, 361771390.5502253], [30978, 361387245.34433717], [30987, 361593448.43031245], [30988, 361651086.73651683], [30994, 361935926.1436106], [30997, 362094701.55638796], [31009, 361700499.9117403], [31019, 361211618.1463887], [31031, 361279244.5880478], [31039, 361641654.6252732], [31040, 361867605.9366872], [31041, 361666858.3923394], [32218, 379949645.02876467], [32220, 380352743.28660166], [32224, 380287944.9296677], [32241, 379870769.20939887], [32249, 379965826.9007728], [32252, 380304254.01199496], [32256, 380004638.7428288], [32259, 379963067.48940855], [33213, 368787950.2932328], [33259, 368806800.8072029], [33296, 368951208.1050684], [33302, 368927926.90372485], [33309, 369138848.6923739], [33310, 368723750.97824854], [33311, 369299275.866913], [33315, 369044598.046218], [33323, 369767182.5188628], [33332, 368752752.0984509], [33333, 369636591.87406], [33337, 369605976.85100967], [33338, 369454113.6285204], [33341, 369912595.6603348], [33346, 369752775.67340624], [33351, 369563985.0009384], [33358, 370496409.63784605], [33359, 370277648.2540609], [33361, 370047376.1821334], [33370, 370300841.0728661], [33373, 370222879.6596526], [33380, 371094229.41805214], [33386, 371012504.76439613], [33393, 371021101.0959501], [33400, 370865525.56796175], [33414, 371133260.7076038], [33424, 370913838.30091214], [33428, 372124661.4777047], [33437, 372027673.0791932], [33444, 366256567.24915475], [33453, 366490355.57922304], [33516, 366433846.29748017], [33517, 366537946.90143174], [33518, 366543391.13887686], [33520, 366716606.825857], [33524, 366536165.0460536], [33533, 366700361.82562315], [33536, 366719955.62838393], [33537, 365885482.6033088], [33543, 365960878.4182125], [33546, 365564045.5705419], [33648, 364843895.7943025], [33704, 364738257.1036946], [33707, 364919069.6881637], [33708, 364901194.290068], [33712, 364604357.63202375], [33715, 364595996.7680823], [33722, 364606981.515001], [33733, 364571343.41888463], [33734, 364435563.96613085], [33756, 364786594.7833631], [33766, 364529887.190606], [33802, 364542252.96087784], [33808, 364438595.70615673], [33813, 364238628.1544411], [33818, 364604141.619194], [33820, 364299395.6564371], [33826, 364222445.18696725], [33833, 364501931.9925416], [34031, 364096651.53195596], [34034, 363912271.5443134], [34046, 364486016.2445896], [34049, 364440999.1929555], [34052, 364083540.7113465], [34058, 364570371.8275397], [34065, 364130870.85012126], [34068, 363932053.5839987], [34075, 364006970.18218464], [34079, 364131099.0288184], [34113, 364347676.75064564], [34115, 364165819.21254396], [34120, 364185024.5965101], [34126, 364319259.00707304], [34139, 364093860.633978], [34140, 364043591.14150655], [34141, 364375424.16063666], [34155, 364292811.99000514], [34158, 364116335.0448665], [34160, 364222375.5190123], [34162, 364194229.65064675]] \ No newline at end of file +[[28497, 363054369.2191392], [29215, 359164934.2771482], [29225, 359800638.06228423], [29227, 360514117.7164347], [29228, 359282909.5242869], [29229, 360013003.5243189], [29235, 360457161.4357038], [29240, 360108258.87493837], [29245, 361121101.9366862], [29246, 360936649.7000913], [29258, 361266930.59624326], [29262, 361134394.1320998], [29279, 361252127.43771815], [29286, 361041551.72556394], [29293, 361044306.55251914], [29294, 360829624.966645], [29295, 360717272.25772864], [29296, 361529184.4202655], [29313, 361089314.802524], [29318, 361301853.79122823], [29319, 361130161.36241764], [29322, 361168114.78717595], [29325, 361738622.33141494], [29327, 361470629.51871145], [29328, 361357749.0570621], [29340, 360777580.70131963], [29344, 359930719.8677546], [29349, 360207528.3336454], [29364, 360221381.64289135], [29371, 360833666.08063483], [29376, 360639466.89683336], [29381, 360381236.7762184], [29383, 360802435.4267732], [29387, 360878184.9905306], [29401, 360064742.9309108], [29404, 360842549.1622037], [29409, 360669862.6005588], [29414, 359760000.1991326], [29415, 360217106.71407515], [29420, 360219880.9998095], [29421, 360753244.92251074], [29425, 360957795.1572051], [29429, 361172828.37313503], [29435, 360570141.9433113], [29443, 360423442.93394357], [29446, 360517461.97813106], [29453, 360076373.81835234], [29454, 360346021.937626], [29455, 360291831.3123189], [29457, 360238487.2282543], [29458, 360679193.8335376], [29469, 360318123.7491145], [29541, 360713417.0016813], [29548, 360262617.74429137], [29550, 360415759.4440005], [29551, 360946690.904145], [29572, 359923850.1732528], [29591, 360435898.34645826], [29598, 360062991.7733901], [29609, 360492325.0429151], [29611, 360125053.2025992], [29621, 360478606.5661861], [29638, 360492878.2639576], [29644, 360755974.8844076], [29648, 360565888.51579714], [29652, 360642636.6197926], [29656, 360602485.66541034], [29657, 360084476.9689012], [29662, 360233646.989097], [29665, 360635785.86225325], [29667, 360291493.96249413], [29735, 360317879.44218403], [29742, 360506636.1933438], [29750, 360475600.01733756], [29753, 360596102.80617666], [29757, 360315098.9688083], [29761, 360184787.3841716], [29765, 360815128.1849716], [29766, 360619171.2074683], [29768, 360471090.38907045], [29776, 360399630.5585596], [29783, 360573154.48446876], [29788, 360301428.8507548], [29789, 360653530.1047434], [29790, 360466394.82107437], [29795, 360513329.4597986], [29798, 360778495.48859453], [29805, 360886466.61620706], [29806, 360595770.5412676], [29807, 360493272.4116185], [29808, 360442350.8431877], [29813, 360744700.5876916], [29815, 360762651.6057989], [29828, 360429984.9108294], [29839, 360532084.3697515], [29844, 360405510.6416504], [29858, 360598586.77512467], [29865, 361168214.4124273], [29999, 360658570.26111186], [30002, 360422940.3133238], [30010, 360766535.63012797], [30013, 360585350.0085867], [30023, 360308493.9917997], [30028, 360464716.5646204], [30035, 360603639.31366193], [30046, 360804542.88969254], [30053, 360651066.2516552], [30066, 360550717.2508093], [30068, 360554302.06808615], [30070, 360765826.33519125], [30074, 360688475.0988678], [30076, 360583252.46979314], [30077, 360830254.18497384], [30078, 360730852.8122437], [30085, 360704773.46127236], [30086, 360472115.44270194], [30096, 360437692.3813615], [30104, 360765429.5121153], [30106, 360735243.66268235], [30112, 361230209.14750177], [30116, 360819164.1569858], [30118, 360479062.88550824], [30123, 360618933.170527], [30128, 360712493.2824262], [30135, 361298944.6359747], [30145, 361251375.53313404], [30155, 361003632.77297306], [30156, 361098353.2191081], [30157, 361074991.3058972], [30165, 361265821.5541183], [30174, 361172095.71709085], [30179, 361025740.95844126], [30185, 361476649.97369576], [30189, 361223057.7633353], [30190, 361248053.55001664], [30198, 361262809.9873703], [30202, 361593559.1844232], [30203, 361025363.89885694], [30208, 361419037.8313204], [30212, 361069564.96903515], [30213, 360956256.8331483], [30215, 361490025.47946954], [30218, 361370893.0204133], [30225, 360971189.72095513], [30227, 360936686.12868583], [30233, 361205091.0923818], [30235, 361122701.7901613], [30238, 361066843.7836295], [30244, 361142354.2467124], [30248, 361157263.3768945], [30254, 360636744.07146066], [30259, 361215315.94095933], [30260, 361073071.63664776], [30501, 361514199.13010144], [30502, 361483148.60713184], [30506, 361546456.7466552], [30507, 361539043.1476933], [30510, 361456989.458338], [30515, 360956676.3764039], [30519, 361235596.6422021], [30520, 361158368.5177364], [30524, 361165066.27265924], [30525, 361455263.2816658], [30529, 361381944.7731546], [30533, 360764163.41892946], [30538, 360966399.1021395], [30542, 361013364.20290995], [30543, 361004601.2296973], [30544, 361512679.17822105], [30545, 360618530.2469018], [30550, 361055198.3438969], [30552, 360515458.2131457], [30556, 360667500.47630143], [30561, 360878970.17597973], [30564, 361130412.60216], [30565, 361026813.8078623], [30577, 361067053.5731284], [30581, 361167379.86367935], [30586, 360903897.5441536], [30593, 360949894.00646937], [30615, 360796748.5875195], [30621, 361176314.6107146], [30622, 361270383.2827531], [30629, 361131139.948447], [30635, 361287854.7617296], [30639, 360832214.03788453], [30640, 360894898.8344037], [30643, 361069357.22959536], [30646, 361010403.381163], [30647, 360865058.12351257], [30650, 360804347.694636], [30657, 360855311.0748219], [30665, 361119567.1955379], [30670, 360657168.00715], [30675, 361136654.16188836], [30679, 360845069.6013101], [30694, 361070865.3968474], [30704, 361121909.7952233], [30708, 360930950.62540466], [30718, 360979554.09432614], [30723, 361291189.0497843], [30729, 361078107.1944605], [30730, 360709545.8601283], [30734, 360799271.5860939], [30739, 361373514.05867606], [30744, 360755782.33141994], [30748, 361083044.15261084], [30750, 361192648.24971634], [30754, 361086326.53907275], [30761, 361755023.27614796], [30762, 361572127.9914095], [30777, 360878136.1863476], [30782, 360678512.066514], [30785, 361045251.8578509], [30787, 361286026.76381093], [30794, 360796612.7248674], [30804, 361016576.6022369], [30812, 361305650.65304726], [30817, 361354498.7749726], [30821, 361267336.1351059], [30838, 361230433.59095675], [30849, 360992061.5227886], [30861, 361115509.04143584], [30868, 361314857.2673176], [30872, 361363757.8426736], [30890, 361427433.91236705], [30904, 361480989.460689], [30907, 361311329.04242915], [30908, 361287289.10858697], [30917, 360865417.6389384], [30928, 361346538.1926865], [30931, 361260386.1956427], [30938, 361092470.18013954], [30945, 361459043.8593052], [30949, 361289915.8538544], [30955, 361179442.5488214], [30957, 361525855.3085044], [30967, 361543566.46677744], [30974, 361771390.5502253], [30978, 361387245.34433717], [30987, 361593448.43031245], [30988, 361651086.73651683], [30994, 361935926.1436106], [30997, 362094701.55638796], [31009, 361700499.9117403], [31019, 361211618.1463887], [31031, 361279244.5880478], [31039, 361641654.6252732], [31040, 361867605.9366872], [31041, 361666858.3923394], [32218, 379949645.02876467], [32220, 380352743.28660166], [32224, 380287944.9296677], [32241, 379870769.20939887], [32249, 379965826.9007728], [32252, 380304254.01199496], [32256, 380004638.7428288], [32259, 379963067.48940855], [33213, 368787950.2932328], [33259, 368806800.8072029], [33296, 368951208.1050684], [33302, 368927926.90372485], [33309, 369138848.6923739], [33310, 368723750.97824854], [33311, 369299275.866913], [33315, 369044598.046218], [33323, 369767182.5188628], [33332, 368752752.0984509], [33333, 369636591.87406], [33337, 369605976.85100967], [33338, 369454113.6285204], [33341, 369912595.6603348], [33346, 369752775.67340624], [33351, 369563985.0009384], [33358, 370496409.63784605], [33359, 370277648.2540609], [33361, 370047376.1821334], [33370, 370300841.0728661], [33373, 370222879.6596526], [33380, 371094229.41805214], [33386, 371012504.76439613], [33393, 371021101.0959501], [33400, 370865525.56796175], [33414, 371133260.7076038], [33424, 370913838.30091214], [33428, 372124661.4777047], [33437, 372027673.0791932], [33444, 366256567.24915475], [33453, 366490355.57922304], [33516, 366433846.29748017], [33517, 366537946.90143174], [33518, 366543391.13887686], [33520, 366716606.825857], [33524, 366536165.0460536], [33533, 366700361.82562315], [33536, 366719955.62838393], [33537, 365885482.6033088], [33543, 365960878.4182125], [33546, 365564045.5705419], [33648, 364843895.7943025], [33704, 364738257.1036946], [33707, 364919069.6881637], [33708, 364901194.290068], [33712, 364604357.63202375], [33715, 364595996.7680823], [33722, 364606981.515001], [33733, 364571343.41888463], [33734, 364435563.96613085], [33756, 364786594.7833631], [33766, 364529887.190606], [33802, 364542252.96087784], [33808, 364438595.70615673], [33813, 364238628.1544411], [33818, 364604141.619194], [33820, 364299395.6564371], [33826, 364222445.18696725], [33833, 364501931.9925416], [34031, 364096651.53195596], [34034, 363912271.5443134], [34046, 364486016.2445896], [34049, 364440999.1929555], [34052, 364083540.7113465], [34058, 364570371.8275397], [34065, 364130870.85012126], [34068, 363932053.5839987], [34075, 364006970.18218464], [34079, 364131099.0288184], [34113, 364347676.75064564], [34115, 364165819.21254396], [34120, 364185024.5965101], [34126, 364319259.00707304], [34139, 364093860.633978], [34140, 364043591.14150655], [34141, 364375424.16063666], [34155, 364292811.99000514], [34158, 364116335.0448665], [34160, 364222375.5190123], [34162, 364194229.65064675], [34164, 364112815.2832731]] \ No newline at end of file diff --git a/graphs/summary/linear_model.RidgeBenchmark.peakmem_predict.json b/graphs/summary/linear_model.RidgeBenchmark.peakmem_predict.json index 95891d1e14..618580a60f 100644 --- a/graphs/summary/linear_model.RidgeBenchmark.peakmem_predict.json +++ b/graphs/summary/linear_model.RidgeBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28497, 183312160.42446414], [29215, 180487683.9416947], [29225, 180873406.6562741], [29227, 181359252.43440658], [29228, 180527645.13084984], [29229, 181357533.12857184], [29235, 181708462.56363103], [29240, 179410061.8798442], [29245, 180591343.343677], [29246, 180667285.61393404], [29258, 181699118.6716666], [29262, 181345705.58807474], [29279, 180786472.9813077], [29286, 180886343.70481107], [29293, 181090088.67394856], [29294, 180698542.26618344], [29295, 180128306.6833449], [29296, 181248755.32213706], [29313, 180773020.22827038], [29318, 181466859.8933833], [29319, 180535409.75765643], [29322, 181193029.26636028], [29325, 180771778.1098962], [29327, 180867710.35359243], [29328, 181687058.24229765], [29340, 180851378.83700866], [29344, 180174596.44700268], [29349, 180082331.38821623], [29364, 180414395.89479497], [29371, 180657836.17198217], [29376, 180447634.3163575], [29381, 180357845.01539725], [29383, 180688843.78944868], [29387, 180534552.2177956], [29401, 179944922.76042157], [29404, 180374809.00563994], [29409, 180654497.473831], [29414, 179809748.11441213], [29415, 180250651.41570988], [29420, 180101906.6066259], [29421, 180645604.44792458], [29425, 180781367.69409168], [29429, 180996248.17857274], [29435, 181896921.95210987], [29443, 181677300.52598405], [29446, 181738801.1148193], [29453, 181650916.0505071], [29454, 181667824.25786588], [29455, 181665046.80664036], [29457, 181717364.84061986], [29458, 181803645.45694914], [29469, 181578179.59125295], [29541, 181812694.70133856], [29548, 182313558.8688987], [29550, 181407217.84601614], [29551, 182359674.410337], [29572, 181665739.55032235], [29591, 181964297.17552304], [29598, 182024330.88001767], [29609, 181856047.3625464], [29611, 182013834.00717625], [29621, 182541588.01800862], [29638, 182003084.7045381], [29644, 182176158.63280478], [29648, 182416677.25072184], [29652, 182472896.62940288], [29656, 182451829.21781093], [29657, 181662352.06399533], [29662, 182392521.52345428], [29665, 182356619.00551027], [29667, 182540261.16233775], [29735, 181932964.9476047], [29742, 182451683.04387018], [29750, 182442316.84397405], [29753, 182202359.4292139], [29757, 182563705.9326854], [29761, 181736223.15530896], [29765, 182668614.51389918], [29766, 182673929.54559222], [29768, 182195900.80395725], [29776, 182275418.653812], [29783, 182325448.81025866], [29788, 181998530.8136393], [29789, 182087128.40378776], [29790, 182029675.08918595], [29795, 182001417.48465163], [29798, 182337671.05295584], [29805, 182549006.6056551], [29806, 181554531.1577778], [29807, 182456271.01905504], [29808, 182036328.73871613], [29813, 182315786.43472725], [29815, 182328566.06783992], [29828, 182369344.85335964], [29839, 182519548.30964175], [29844, 182539589.91992545], [29858, 182774180.14509055], [29865, 182405220.79372126], [29999, 182296651.38079405], [30002, 182005091.3351186], [30010, 181727195.2738431], [30013, 182595993.94710103], [30023, 182264188.50111145], [30028, 182443477.0059752], [30035, 182557909.0269541], [30046, 182290649.8527127], [30053, 182164183.85833278], [30066, 182371134.19215238], [30068, 182440700.46639538], [30070, 182741283.0317358], [30074, 182576518.8549654], [30076, 182556107.18011314], [30077, 182879485.503569], [30078, 182498967.20056713], [30085, 182261263.21285167], [30086, 182531345.06949076], [30096, 182303121.2924435], [30104, 182573747.25006124], [30106, 182266844.24617207], [30112, 182763774.3087188], [30116, 182246657.3521643], [30118, 182086051.60224786], [30123, 182288935.31471887], [30128, 182386162.1577509], [30135, 182919718.35228133], [30145, 182546291.23162198], [30155, 182471585.52752274], [30156, 183163592.95920834], [30157, 182848226.7761267], [30165, 182817081.42442545], [30174, 183342146.6294026], [30179, 182020464.21717617], [30185, 182871504.48755342], [30189, 182225395.24522817], [30190, 183232321.018563], [30198, 182617449.37116137], [30202, 182828655.97626778], [30203, 182345411.33055985], [30208, 183206065.94611034], [30212, 183154411.34617764], [30213, 182053802.9683925], [30215, 182342997.9518218], [30218, 183275080.38790917], [30225, 182599823.76259452], [30227, 182235780.96049818], [30233, 182350625.37670156], [30235, 182276495.49360964], [30238, 183126293.8527339], [30244, 182793590.40606475], [30248, 183047970.34002686], [30254, 182152107.04086697], [30259, 182258492.84166756], [30260, 182157596.1408257], [30501, 182457926.76833084], [30502, 183007205.80940923], [30506, 182797387.2576383], [30507, 182842444.5423098], [30510, 183077861.78842446], [30515, 182519899.3147312], [30519, 183028751.08317897], [30520, 182915317.68856966], [30524, 182953573.83723179], [30525, 183241495.27956453], [30529, 183143742.28265065], [30533, 181889506.38762587], [30538, 182146703.38731217], [30542, 182914552.452059], [30543, 182334562.07331777], [30544, 182497128.02606016], [30545, 182231511.67810363], [30550, 182384000.92700014], [30552, 182139104.8340915], [30556, 182244810.06676304], [30561, 182701743.419551], [30564, 182458059.15045312], [30565, 182619979.34338024], [30577, 182624969.32851753], [30581, 182748514.8788219], [30586, 182220233.19150347], [30593, 182738758.28552368], [30615, 182211790.00237006], [30621, 182275187.47750387], [30622, 182587256.1648839], [30629, 182578750.01261294], [30635, 182612227.45424423], [30639, 182475318.49949405], [30640, 182826042.741888], [30643, 182461516.87044388], [30646, 182270248.06884542], [30647, 182798257.28761476], [30650, 182274125.14655218], [30657, 182370723.89549473], [30665, 182381782.91657728], [30670, 182171819.98747462], [30675, 182723208.32897], [30679, 182338082.23728853], [30694, 182700232.3804517], [30704, 182569853.3043599], [30708, 182878512.1373626], [30718, 182295395.84479973], [30723, 182726869.24308026], [30729, 182569709.415828], [30730, 181879980.4201951], [30734, 183046107.82802427], [30739, 183168303.1145282], [30744, 182658693.19394335], [30748, 183168484.81763035], [30750, 182507360.36749235], [30754, 182951331.64239573], [30761, 183240242.97922415], [30762, 182687801.49536353], [30777, 182712939.44063994], [30782, 182249149.7506496], [30785, 181989527.74946982], [30787, 182232759.84544554], [30794, 183021133.21549258], [30804, 182700493.8844295], [30812, 182724923.1974448], [30817, 182785247.92652756], [30821, 182357742.6041566], [30838, 182747874.81063044], [30849, 182477392.60864753], [30861, 182693519.80890167], [30868, 182685626.2193757], [30872, 182608551.2111616], [30890, 182585000.49649075], [30904, 182578316.62015933], [30907, 183080523.99818644], [30908, 183348394.44210148], [30917, 181925697.384401], [30928, 182378239.3584483], [30931, 182673223.2938798], [30938, 182506887.7694963], [30945, 182749760.6299596], [30949, 182731093.80328742], [30955, 182511985.09184542], [30957, 182638812.84245294], [30967, 182691569.0121375], [30974, 182934186.8877611], [30978, 182405889.42011967], [30987, 182759033.7586011], [30988, 182744675.4590571], [30994, 183010396.99470788], [30997, 183017839.29307804], [31009, 182805018.6121199], [31019, 182662883.11988685], [31031, 182210349.186517], [31039, 182919792.12722227], [31040, 182815788.80877703], [31041, 182416719.06742263], [32218, 200123048.4350834], [32220, 199165792.02592874], [32224, 199629001.47181165], [32241, 199611843.72469658], [32249, 199770499.16236424], [32252, 199416370.7923717], [32256, 199051144.0551062], [32259, 200043586.80139694], [33213, 193414362.1868325], [33259, 193388865.71994996], [33296, 193820850.26916686], [33302, 193459061.7083089], [33309, 194470433.85298443], [33310, 193777205.07682315], [33311, 193979454.16011262], [33315, 193969691.80031908], [33323, 194173518.77445614], [33332, 193937321.80287254], [33333, 194394595.46356913], [33337, 194283459.09702474], [33338, 193792446.65458944], [33341, 194028399.78094512], [33346, 194640012.70485792], [33351, 194218791.09036845], [33358, 195023244.32679945], [33359, 194660626.08089164], [33361, 194784470.12218767], [33370, 195132874.6733214], [33373, 194640454.1943661], [33380, 195171331.39495423], [33386, 195192982.61071575], [33393, 195700353.93159485], [33400, 195780573.24753216], [33414, 195733322.4032465], [33424, 195901106.36127165], [33428, 196692957.55989817], [33437, 197146468.9517791], [33444, 191816809.22065347], [33453, 191125233.3195316], [33516, 192299414.8723837], [33517, 191312811.59412605], [33518, 191238803.45004892], [33520, 191405236.092363], [33524, 191528173.90892902], [33533, 190955108.1882297], [33536, 191238127.53522032], [33537, 191779929.33397225], [33543, 191772857.54492506], [33546, 190818370.82364416], [33648, 190178930.4068979], [33704, 189400335.6485997], [33707, 189955995.44310006], [33708, 189535487.41360435], [33712, 189542331.367757], [33715, 189302989.93041512], [33722, 190035227.93719918], [33733, 189944953.58908665], [33734, 190114472.63868803], [33756, 190413341.8165866], [33766, 189331411.68682835], [33802, 190259279.83436087], [33808, 190075991.3450107], [33813, 189006692.20743278], [33818, 189347055.38299337], [33820, 189772514.6019161], [33826, 189562435.14887878], [33833, 189977066.678814], [34031, 188932015.67205724], [34034, 189140069.32065716], [34046, 189507460.45572272], [34049, 189462412.8276537], [34052, 189123119.2553191], [34058, 189650583.12183946], [34065, 189353770.16562286], [34068, 189372169.98572966], [34075, 188707282.61614874], [34079, 189099794.15041414], [34113, 189150993.78537917], [34115, 189604201.8557246], [34120, 188771172.77290264], [34126, 190269763.48925874], [34139, 189980461.90395752], [34140, 188899789.4056498], [34141, 189003833.1229254], [34155, 189148513.242183], [34158, 188829453.39784113], [34160, 188785083.46062505], [34162, 189383138.1626308]] \ No newline at end of file +[[28497, 183312160.42446414], [29215, 180487683.9416947], [29225, 180873406.6562741], [29227, 181359252.43440658], [29228, 180527645.13084984], [29229, 181357533.12857184], [29235, 181708462.56363103], [29240, 179410061.8798442], [29245, 180591343.343677], [29246, 180667285.61393404], [29258, 181699118.6716666], [29262, 181345705.58807474], [29279, 180786472.9813077], [29286, 180886343.70481107], [29293, 181090088.67394856], [29294, 180698542.26618344], [29295, 180128306.6833449], [29296, 181248755.32213706], [29313, 180773020.22827038], [29318, 181466859.8933833], [29319, 180535409.75765643], [29322, 181193029.26636028], [29325, 180771778.1098962], [29327, 180867710.35359243], [29328, 181687058.24229765], [29340, 180851378.83700866], [29344, 180174596.44700268], [29349, 180082331.38821623], [29364, 180414395.89479497], [29371, 180657836.17198217], [29376, 180447634.3163575], [29381, 180357845.01539725], [29383, 180688843.78944868], [29387, 180534552.2177956], [29401, 179944922.76042157], [29404, 180374809.00563994], [29409, 180654497.473831], [29414, 179809748.11441213], [29415, 180250651.41570988], [29420, 180101906.6066259], [29421, 180645604.44792458], [29425, 180781367.69409168], [29429, 180996248.17857274], [29435, 181896921.95210987], [29443, 181677300.52598405], [29446, 181738801.1148193], [29453, 181650916.0505071], [29454, 181667824.25786588], [29455, 181665046.80664036], [29457, 181717364.84061986], [29458, 181803645.45694914], [29469, 181578179.59125295], [29541, 181812694.70133856], [29548, 182313558.8688987], [29550, 181407217.84601614], [29551, 182359674.410337], [29572, 181665739.55032235], [29591, 181964297.17552304], [29598, 182024330.88001767], [29609, 181856047.3625464], [29611, 182013834.00717625], [29621, 182541588.01800862], [29638, 182003084.7045381], [29644, 182176158.63280478], [29648, 182416677.25072184], [29652, 182472896.62940288], [29656, 182451829.21781093], [29657, 181662352.06399533], [29662, 182392521.52345428], [29665, 182356619.00551027], [29667, 182540261.16233775], [29735, 181932964.9476047], [29742, 182451683.04387018], [29750, 182442316.84397405], [29753, 182202359.4292139], [29757, 182563705.9326854], [29761, 181736223.15530896], [29765, 182668614.51389918], [29766, 182673929.54559222], [29768, 182195900.80395725], [29776, 182275418.653812], [29783, 182325448.81025866], [29788, 181998530.8136393], [29789, 182087128.40378776], [29790, 182029675.08918595], [29795, 182001417.48465163], [29798, 182337671.05295584], [29805, 182549006.6056551], [29806, 181554531.1577778], [29807, 182456271.01905504], [29808, 182036328.73871613], [29813, 182315786.43472725], [29815, 182328566.06783992], [29828, 182369344.85335964], [29839, 182519548.30964175], [29844, 182539589.91992545], [29858, 182774180.14509055], [29865, 182405220.79372126], [29999, 182296651.38079405], [30002, 182005091.3351186], [30010, 181727195.2738431], [30013, 182595993.94710103], [30023, 182264188.50111145], [30028, 182443477.0059752], [30035, 182557909.0269541], [30046, 182290649.8527127], [30053, 182164183.85833278], [30066, 182371134.19215238], [30068, 182440700.46639538], [30070, 182741283.0317358], [30074, 182576518.8549654], [30076, 182556107.18011314], [30077, 182879485.503569], [30078, 182498967.20056713], [30085, 182261263.21285167], [30086, 182531345.06949076], [30096, 182303121.2924435], [30104, 182573747.25006124], [30106, 182266844.24617207], [30112, 182763774.3087188], [30116, 182246657.3521643], [30118, 182086051.60224786], [30123, 182288935.31471887], [30128, 182386162.1577509], [30135, 182919718.35228133], [30145, 182546291.23162198], [30155, 182471585.52752274], [30156, 183163592.95920834], [30157, 182848226.7761267], [30165, 182817081.42442545], [30174, 183342146.6294026], [30179, 182020464.21717617], [30185, 182871504.48755342], [30189, 182225395.24522817], [30190, 183232321.018563], [30198, 182617449.37116137], [30202, 182828655.97626778], [30203, 182345411.33055985], [30208, 183206065.94611034], [30212, 183154411.34617764], [30213, 182053802.9683925], [30215, 182342997.9518218], [30218, 183275080.38790917], [30225, 182599823.76259452], [30227, 182235780.96049818], [30233, 182350625.37670156], [30235, 182276495.49360964], [30238, 183126293.8527339], [30244, 182793590.40606475], [30248, 183047970.34002686], [30254, 182152107.04086697], [30259, 182258492.84166756], [30260, 182157596.1408257], [30501, 182457926.76833084], [30502, 183007205.80940923], [30506, 182797387.2576383], [30507, 182842444.5423098], [30510, 183077861.78842446], [30515, 182519899.3147312], [30519, 183028751.08317897], [30520, 182915317.68856966], [30524, 182953573.83723179], [30525, 183241495.27956453], [30529, 183143742.28265065], [30533, 181889506.38762587], [30538, 182146703.38731217], [30542, 182914552.452059], [30543, 182334562.07331777], [30544, 182497128.02606016], [30545, 182231511.67810363], [30550, 182384000.92700014], [30552, 182139104.8340915], [30556, 182244810.06676304], [30561, 182701743.419551], [30564, 182458059.15045312], [30565, 182619979.34338024], [30577, 182624969.32851753], [30581, 182748514.8788219], [30586, 182220233.19150347], [30593, 182738758.28552368], [30615, 182211790.00237006], [30621, 182275187.47750387], [30622, 182587256.1648839], [30629, 182578750.01261294], [30635, 182612227.45424423], [30639, 182475318.49949405], [30640, 182826042.741888], [30643, 182461516.87044388], [30646, 182270248.06884542], [30647, 182798257.28761476], [30650, 182274125.14655218], [30657, 182370723.89549473], [30665, 182381782.91657728], [30670, 182171819.98747462], [30675, 182723208.32897], [30679, 182338082.23728853], [30694, 182700232.3804517], [30704, 182569853.3043599], [30708, 182878512.1373626], [30718, 182295395.84479973], [30723, 182726869.24308026], [30729, 182569709.415828], [30730, 181879980.4201951], [30734, 183046107.82802427], [30739, 183168303.1145282], [30744, 182658693.19394335], [30748, 183168484.81763035], [30750, 182507360.36749235], [30754, 182951331.64239573], [30761, 183240242.97922415], [30762, 182687801.49536353], [30777, 182712939.44063994], [30782, 182249149.7506496], [30785, 181989527.74946982], [30787, 182232759.84544554], [30794, 183021133.21549258], [30804, 182700493.8844295], [30812, 182724923.1974448], [30817, 182785247.92652756], [30821, 182357742.6041566], [30838, 182747874.81063044], [30849, 182477392.60864753], [30861, 182693519.80890167], [30868, 182685626.2193757], [30872, 182608551.2111616], [30890, 182585000.49649075], [30904, 182578316.62015933], [30907, 183080523.99818644], [30908, 183348394.44210148], [30917, 181925697.384401], [30928, 182378239.3584483], [30931, 182673223.2938798], [30938, 182506887.7694963], [30945, 182749760.6299596], [30949, 182731093.80328742], [30955, 182511985.09184542], [30957, 182638812.84245294], [30967, 182691569.0121375], [30974, 182934186.8877611], [30978, 182405889.42011967], [30987, 182759033.7586011], [30988, 182744675.4590571], [30994, 183010396.99470788], [30997, 183017839.29307804], [31009, 182805018.6121199], [31019, 182662883.11988685], [31031, 182210349.186517], [31039, 182919792.12722227], [31040, 182815788.80877703], [31041, 182416719.06742263], [32218, 200123048.4350834], [32220, 199165792.02592874], [32224, 199629001.47181165], [32241, 199611843.72469658], [32249, 199770499.16236424], [32252, 199416370.7923717], [32256, 199051144.0551062], [32259, 200043586.80139694], [33213, 193414362.1868325], [33259, 193388865.71994996], [33296, 193820850.26916686], [33302, 193459061.7083089], [33309, 194470433.85298443], [33310, 193777205.07682315], [33311, 193979454.16011262], [33315, 193969691.80031908], [33323, 194173518.77445614], [33332, 193937321.80287254], [33333, 194394595.46356913], [33337, 194283459.09702474], [33338, 193792446.65458944], [33341, 194028399.78094512], [33346, 194640012.70485792], [33351, 194218791.09036845], [33358, 195023244.32679945], [33359, 194660626.08089164], [33361, 194784470.12218767], [33370, 195132874.6733214], [33373, 194640454.1943661], [33380, 195171331.39495423], [33386, 195192982.61071575], [33393, 195700353.93159485], [33400, 195780573.24753216], [33414, 195733322.4032465], [33424, 195901106.36127165], [33428, 196692957.55989817], [33437, 197146468.9517791], [33444, 191816809.22065347], [33453, 191125233.3195316], [33516, 192299414.8723837], [33517, 191312811.59412605], [33518, 191238803.45004892], [33520, 191405236.092363], [33524, 191528173.90892902], [33533, 190955108.1882297], [33536, 191238127.53522032], [33537, 191779929.33397225], [33543, 191772857.54492506], [33546, 190818370.82364416], [33648, 190178930.4068979], [33704, 189400335.6485997], [33707, 189955995.44310006], [33708, 189535487.41360435], [33712, 189542331.367757], [33715, 189302989.93041512], [33722, 190035227.93719918], [33733, 189944953.58908665], [33734, 190114472.63868803], [33756, 190413341.8165866], [33766, 189331411.68682835], [33802, 190259279.83436087], [33808, 190075991.3450107], [33813, 189006692.20743278], [33818, 189347055.38299337], [33820, 189772514.6019161], [33826, 189562435.14887878], [33833, 189977066.678814], [34031, 188932015.67205724], [34034, 189140069.32065716], [34046, 189507460.45572272], [34049, 189462412.8276537], [34052, 189123119.2553191], [34058, 189650583.12183946], [34065, 189353770.16562286], [34068, 189372169.98572966], [34075, 188707282.61614874], [34079, 189099794.15041414], [34113, 189150993.78537917], [34115, 189604201.8557246], [34120, 188771172.77290264], [34126, 190269763.48925874], [34139, 189980461.90395752], [34140, 188899789.4056498], [34141, 189003833.1229254], [34155, 189148513.242183], [34158, 188829453.39784113], [34160, 188785083.46062505], [34162, 189383138.1626308], [34164, 189077217.94491133]] \ No newline at end of file diff --git a/graphs/summary/linear_model.RidgeBenchmark.time_fit.json b/graphs/summary/linear_model.RidgeBenchmark.time_fit.json index 4e3647f3b1..b3f478a731 100644 --- a/graphs/summary/linear_model.RidgeBenchmark.time_fit.json +++ b/graphs/summary/linear_model.RidgeBenchmark.time_fit.json @@ -1 +1 @@ -[[28497, 0.7526780189333017], [29215, 0.8507534756665868], [29225, 0.7005334676380224], [29227, 0.7841483921102415], [29228, 0.7314639643518157], [29229, 0.7324364923986977], [29235, 0.7040224008699925], [29240, 0.7276944553728499], [29245, 0.7356848270790537], [29246, 0.7302111146138104], [29258, 0.7401338973472159], [29262, 0.7235579771318436], [29279, 0.7668733941056846], [29286, 0.8217859295963662], [29293, 0.7481213094178158], [29294, 0.7347481286326688], [29295, 0.7256569007733399], [29296, 0.7844851761819011], [29313, 0.7874063462060984], [29318, 0.7335691406716653], [29319, 0.7293731848878663], [29322, 0.731059538892119], [29325, 0.7593141693280913], [29327, 0.7562916118104943], [29328, 0.7301735294917935], [29340, 0.7780978203917103], [29344, 0.6693366948558809], [29349, 0.6795531968248348], [29364, 0.7009302970633745], [29371, 0.6767138049011046], [29376, 0.7442080797100622], [29381, 0.6747525958365298], [29383, 0.7737677278309443], [29387, 0.6891993934462884], [29401, 0.676001208065765], [29404, 0.6742001507635631], [29409, 0.6849387572554968], [29414, 0.6604277035961882], [29415, 0.6621501890495022], [29420, 0.6685365990832924], [29421, 0.7440760628947235], [29425, 0.6642367757952481], [29429, 0.6638174715315627], [29435, 0.8951188200853029], [29443, 0.891498265557012], [29446, 0.84064614075643], [29453, 0.8565824129902533], [29454, 0.8459483196465882], [29455, 0.8844992761951176], [29457, 0.823030304161635], [29458, 0.7412383094600662], [29469, 0.7461606719031302], [29541, 0.7712021101088584], [29548, 0.7624532064413112], [29550, 0.7445312346805069], [29551, 0.6357954698975494], [29572, 0.6408236470132002], [29591, 0.6342462394809482], [29598, 0.6333612789583255], [29609, 0.6457467695393637], [29611, 0.6189064806858295], [29621, 0.6428803835583334], [29638, 0.6347337684354577], [29644, 0.6178550089533764], [29648, 0.6175054478568539], [29652, 0.608647345838167], [29656, 0.6334194728598258], [29657, 0.6367252117937446], [29662, 0.6392925628641598], [29665, 0.632173076082263], [29667, 0.6140890971357357], [29735, 0.6379218826399515], [29742, 0.6356763892533754], [29750, 0.7266121158523493], [29753, 0.6373579401694748], [29757, 0.6347854010588715], [29761, 0.6390012728532407], [29765, 0.6334272785974743], [29766, 0.6380935535025208], [29768, 0.6476310380503432], [29776, 0.7400308869439842], [29783, 0.6910553501656244], [29788, 0.6414809655471349], [29789, 0.6616174416802582], [29790, 0.6315814269066959], [29795, 0.6942084616706065], [29798, 0.6628282906619425], [29805, 0.6519447349857057], [29806, 0.6533941228202331], [29807, 0.6664077459618643], [29808, 0.6487637439510047], [29813, 0.6691734352776115], [29815, 0.6630046389520706], [29828, 0.674750687727083], [29839, 0.6560980643825451], [29844, 0.6813657016798743], [29858, 0.6592499494762075], [29865, 0.6899627730758842], [29999, 0.6459352792067379], [30002, 0.6920432040805999], [30010, 0.6666496328332081], [30013, 0.6585222574502299], [30023, 0.6798299462492758], [30028, 0.6692499781104833], [30035, 0.6276923006673906], [30046, 0.6811664411725686], [30053, 0.6633623146363343], [30066, 0.6603438641521139], [30068, 0.6770654826636922], [30070, 0.6426087242788764], [30074, 0.6780282186006927], [30076, 0.6620855058880313], [30077, 0.6952138872230402], [30078, 0.6605681037653099], [30085, 0.650518593788598], [30086, 0.6789917569308065], [30096, 0.6786237740410281], [30104, 0.6939205594929256], [30106, 0.6783548997888572], [30112, 0.6667228747296258], [30116, 0.6732578155646025], [30118, 0.6726659712995882], [30123, 0.6499174862666336], [30128, 0.6634084837799926], [30135, 0.6444924219209175], [30145, 0.688567040843405], [30155, 0.6362497068299979], [30156, 0.6765593470414598], [30157, 0.6707469752540252], [30165, 0.6665032256322843], [30174, 0.6642347589504496], [30179, 0.6280805660200198], [30185, 0.6665464111649426], [30189, 0.6710754171795678], [30190, 0.6588383457548916], [30198, 0.6722766152983642], [30202, 0.6469038913633718], [30203, 0.6607430765262748], [30208, 0.6749014435813128], [30212, 0.6777057110024471], [30213, 0.6412609143837057], [30215, 0.6588847303223906], [30218, 0.6831809883476527], [30225, 0.6507271140932773], [30227, 0.6650795770775582], [30233, 0.666755593405344], [30235, 0.6413385253968523], [30238, 0.679948098142255], [30244, 0.6735700106006709], [30248, 0.6618588798366963], [30254, 0.6779407154108515], [30259, 0.671694134199462], [30260, 0.6607698940806389], [30501, 0.6717283945042956], [30502, 0.7080655246359976], [30506, 0.6230879588404792], [30507, 0.6675304703749905], [30510, 0.6531739428946907], [30515, 0.673824279260232], [30519, 0.6748005221482393], [30520, 0.6871913875263249], [30524, 0.6741672090257484], [30525, 0.6649474601362362], [30529, 0.6674692415876228], [30533, 0.7363338947379463], [30538, 0.7248767057331437], [30542, 0.7078609399521728], [30543, 0.7032174512317912], [30544, 0.7085024821775754], [30545, 0.7033627143895351], [30550, 0.755545832764181], [30552, 0.7472932018859326], [30556, 0.7575650736612627], [30561, 0.7292608388774076], [30564, 0.7578547497899897], [30565, 0.7057171325856129], [30577, 0.7115699804794589], [30581, 0.7428940946440482], [30586, 0.7063125831879641], [30593, 0.7319540510672953], [30615, 0.7716802850755932], [30621, 0.7373768402801076], [30622, 0.7495442140458213], [30629, 0.7317705276357042], [30635, 0.7214061325451454], [30639, 0.7323307136521859], [30640, 0.7310787342497764], [30643, 0.7575360348300361], [30646, 0.7332031101152063], [30647, 0.7233913823095112], [30650, 0.7559955234281506], [30657, 0.734788014699214], [30665, 0.7391388843754212], [30670, 0.7371912433368206], [30675, 0.7245301561982247], [30679, 0.7074473241672398], [30694, 0.7427264271281999], [30704, 0.6984816894954674], [30708, 0.7201426692140512], [30718, 0.6408245430925432], [30723, 0.6844043674667099], [30729, 0.6491641826974139], [30730, 0.6611130919824112], [30734, 0.6759503678339707], [30739, 0.6296011332412466], [30744, 0.6842440456800395], [30748, 0.6732032061953583], [30750, 0.679000961875111], [30754, 0.6715089278995519], [30761, 0.6452804041832333], [30762, 0.6569412471347778], [30777, 0.6411480806530547], [30782, 0.6408960186452626], [30785, 0.6496698468491053], [30787, 0.669078112432247], [30794, 0.6849050306694098], [30804, 0.6811475018907811], [30812, 0.6580096832732253], [30817, 0.6716793136612421], [30821, 0.6440144301271696], [30838, 0.6534770485440903], [30849, 0.6638553683571237], [30861, 0.6765007938563886], [30868, 0.6640868455598318], [30872, 0.6700290204076854], [30890, 0.6520179444720836], [30904, 0.6600497077195081], [30907, 0.6698828753461392], [30908, 0.6711242286969846], [30917, 0.64119041648439], [30928, 0.6647352228009208], [30931, 0.645920360176669], [30938, 0.6808608339838554], [30945, 0.6666708358191799], [30949, 0.6793868421333568], [30955, 0.6482599710698216], [30957, 0.6436445603639643], [30967, 0.6559145017839461], [30974, 0.6407040257094406], [30978, 0.6501468883532845], [30987, 0.6950767538235261], [30988, 0.7445356081552125], [30994, 0.7348597137887946], [30997, 0.7182919131580036], [31009, 0.7524432578126182], [31019, 0.7919452414703676], [31031, 0.720763487630303], [31039, 0.7136681589147796], [31040, 0.7175439436761293], [31041, 0.8165730845656137], [32218, 0.729711458573955], [32220, 0.7265675478919424], [32224, 0.7366414595556144], [32241, 0.7213544552857597], [32249, 0.7185940138208129], [32252, 0.6971807858191664], [32256, 0.7061573278142939], [32259, 0.6950702015198814], [33213, 0.8803064851184284], [33259, 0.8821084831839892], [33296, 0.8583313038150681], [33302, 0.8720915886192258], [33309, 0.8660069257605115], [33310, 0.8862879618278011], [33311, 0.8715423801958357], [33315, 0.8866582233161322], [33323, 0.8640872364021378], [33332, 0.8762189426357689], [33333, 0.8707213418081459], [33337, 0.909276113677693], [33338, 0.8949029787886731], [33341, 0.9365836874064226], [33346, 0.8975857049391185], [33351, 0.9161146493957396], [33358, 0.9087668358136597], [33359, 0.8746417429549008], [33361, 0.893114218557973], [33370, 0.8976467149811846], [33373, 0.8673642408332886], [33380, 0.8661055589981947], [33386, 0.8790263056255527], [33393, 0.8915589159788706], [33400, 0.8787639243732728], [33414, 0.8971069414901426], [33424, 0.9067176880860129], [33428, 0.902538174123705], [33437, 0.9016918424164887], [33444, 0.8874271870761075], [33453, 0.9400539321402723], [33516, 0.9039717362791704], [33517, 0.8695003379373198], [33518, 0.8853979473977008], [33520, 0.8854012585822685], [33524, 0.9220791107967138], [33533, 0.8918679298793099], [33536, 0.8932950889764406], [33537, 0.8809639981363171], [33543, 0.9149766591137487], [33546, 0.8910324982584641], [33648, 0.9243810660649225], [33704, 0.8889031573165536], [33707, 0.9307889410015118], [33708, 0.9059926285176506], [33712, 0.980167187438088], [33715, 0.9160550770037768], [33722, 0.8989790266044754], [33733, 0.8674379079584553], [33734, 0.8557419958337109], [33756, 0.875667407162526], [33766, 0.8622622032239892], [33802, 0.8557484685810197], [33808, 0.8781901528991796], [33813, 0.8706360332067605], [33818, 0.8562354238072932], [33820, 0.861428104164772], [33826, 0.8799905433332141], [33833, 0.8590625490876018], [34031, 0.8879694262260878], [34034, 0.8902255484405703], [34046, 0.8562503434203027], [34049, 0.8747622637598156], [34052, 0.9378763940561258], [34058, 0.9021968190073616], [34065, 0.8979305129431238], [34068, 0.9080523891470353], [34075, 0.9114233931655474], [34079, 0.8992897494743587], [34113, 0.8713811635548312], [34115, 0.8623594780543284], [34120, 0.8714277016146138], [34126, 0.8728586131528632], [34139, 0.8607858876530878], [34140, 0.8781966308265042], [34141, 0.8876829744148214], [34155, 0.8746903913479119], [34158, 0.8893178504364835], [34160, 0.8947085094358459], [34162, 0.8740213491735034]] \ No newline at end of file +[[28497, 0.7526780189333017], [29215, 0.8507534756665868], [29225, 0.7005334676380224], [29227, 0.7841483921102415], [29228, 0.7314639643518157], [29229, 0.7324364923986977], [29235, 0.7040224008699925], [29240, 0.7276944553728499], [29245, 0.7356848270790537], [29246, 0.7302111146138104], [29258, 0.7401338973472159], [29262, 0.7235579771318436], [29279, 0.7668733941056846], [29286, 0.8217859295963662], [29293, 0.7481213094178158], [29294, 0.7347481286326688], [29295, 0.7256569007733399], [29296, 0.7844851761819011], [29313, 0.7874063462060984], [29318, 0.7335691406716653], [29319, 0.7293731848878663], [29322, 0.731059538892119], [29325, 0.7593141693280913], [29327, 0.7562916118104943], [29328, 0.7301735294917935], [29340, 0.7780978203917103], [29344, 0.6693366948558809], [29349, 0.6795531968248348], [29364, 0.7009302970633745], [29371, 0.6767138049011046], [29376, 0.7442080797100622], [29381, 0.6747525958365298], [29383, 0.7737677278309443], [29387, 0.6891993934462884], [29401, 0.676001208065765], [29404, 0.6742001507635631], [29409, 0.6849387572554968], [29414, 0.6604277035961882], [29415, 0.6621501890495022], [29420, 0.6685365990832924], [29421, 0.7440760628947235], [29425, 0.6642367757952481], [29429, 0.6638174715315627], [29435, 0.8951188200853029], [29443, 0.891498265557012], [29446, 0.84064614075643], [29453, 0.8565824129902533], [29454, 0.8459483196465882], [29455, 0.8844992761951176], [29457, 0.823030304161635], [29458, 0.7412383094600662], [29469, 0.7461606719031302], [29541, 0.7712021101088584], [29548, 0.7624532064413112], [29550, 0.7445312346805069], [29551, 0.6357954698975494], [29572, 0.6408236470132002], [29591, 0.6342462394809482], [29598, 0.6333612789583255], [29609, 0.6457467695393637], [29611, 0.6189064806858295], [29621, 0.6428803835583334], [29638, 0.6347337684354577], [29644, 0.6178550089533764], [29648, 0.6175054478568539], [29652, 0.608647345838167], [29656, 0.6334194728598258], [29657, 0.6367252117937446], [29662, 0.6392925628641598], [29665, 0.632173076082263], [29667, 0.6140890971357357], [29735, 0.6379218826399515], [29742, 0.6356763892533754], [29750, 0.7266121158523493], [29753, 0.6373579401694748], [29757, 0.6347854010588715], [29761, 0.6390012728532407], [29765, 0.6334272785974743], [29766, 0.6380935535025208], [29768, 0.6476310380503432], [29776, 0.7400308869439842], [29783, 0.6910553501656244], [29788, 0.6414809655471349], [29789, 0.6616174416802582], [29790, 0.6315814269066959], [29795, 0.6942084616706065], [29798, 0.6628282906619425], [29805, 0.6519447349857057], [29806, 0.6533941228202331], [29807, 0.6664077459618643], [29808, 0.6487637439510047], [29813, 0.6691734352776115], [29815, 0.6630046389520706], [29828, 0.674750687727083], [29839, 0.6560980643825451], [29844, 0.6813657016798743], [29858, 0.6592499494762075], [29865, 0.6899627730758842], [29999, 0.6459352792067379], [30002, 0.6920432040805999], [30010, 0.6666496328332081], [30013, 0.6585222574502299], [30023, 0.6798299462492758], [30028, 0.6692499781104833], [30035, 0.6276923006673906], [30046, 0.6811664411725686], [30053, 0.6633623146363343], [30066, 0.6603438641521139], [30068, 0.6770654826636922], [30070, 0.6426087242788764], [30074, 0.6780282186006927], [30076, 0.6620855058880313], [30077, 0.6952138872230402], [30078, 0.6605681037653099], [30085, 0.650518593788598], [30086, 0.6789917569308065], [30096, 0.6786237740410281], [30104, 0.6939205594929256], [30106, 0.6783548997888572], [30112, 0.6667228747296258], [30116, 0.6732578155646025], [30118, 0.6726659712995882], [30123, 0.6499174862666336], [30128, 0.6634084837799926], [30135, 0.6444924219209175], [30145, 0.688567040843405], [30155, 0.6362497068299979], [30156, 0.6765593470414598], [30157, 0.6707469752540252], [30165, 0.6665032256322843], [30174, 0.6642347589504496], [30179, 0.6280805660200198], [30185, 0.6665464111649426], [30189, 0.6710754171795678], [30190, 0.6588383457548916], [30198, 0.6722766152983642], [30202, 0.6469038913633718], [30203, 0.6607430765262748], [30208, 0.6749014435813128], [30212, 0.6777057110024471], [30213, 0.6412609143837057], [30215, 0.6588847303223906], [30218, 0.6831809883476527], [30225, 0.6507271140932773], [30227, 0.6650795770775582], [30233, 0.666755593405344], [30235, 0.6413385253968523], [30238, 0.679948098142255], [30244, 0.6735700106006709], [30248, 0.6618588798366963], [30254, 0.6779407154108515], [30259, 0.671694134199462], [30260, 0.6607698940806389], [30501, 0.6717283945042956], [30502, 0.7080655246359976], [30506, 0.6230879588404792], [30507, 0.6675304703749905], [30510, 0.6531739428946907], [30515, 0.673824279260232], [30519, 0.6748005221482393], [30520, 0.6871913875263249], [30524, 0.6741672090257484], [30525, 0.6649474601362362], [30529, 0.6674692415876228], [30533, 0.7363338947379463], [30538, 0.7248767057331437], [30542, 0.7078609399521728], [30543, 0.7032174512317912], [30544, 0.7085024821775754], [30545, 0.7033627143895351], [30550, 0.755545832764181], [30552, 0.7472932018859326], [30556, 0.7575650736612627], [30561, 0.7292608388774076], [30564, 0.7578547497899897], [30565, 0.7057171325856129], [30577, 0.7115699804794589], [30581, 0.7428940946440482], [30586, 0.7063125831879641], [30593, 0.7319540510672953], [30615, 0.7716802850755932], [30621, 0.7373768402801076], [30622, 0.7495442140458213], [30629, 0.7317705276357042], [30635, 0.7214061325451454], [30639, 0.7323307136521859], [30640, 0.7310787342497764], [30643, 0.7575360348300361], [30646, 0.7332031101152063], [30647, 0.7233913823095112], [30650, 0.7559955234281506], [30657, 0.734788014699214], [30665, 0.7391388843754212], [30670, 0.7371912433368206], [30675, 0.7245301561982247], [30679, 0.7074473241672398], [30694, 0.7427264271281999], [30704, 0.6984816894954674], [30708, 0.7201426692140512], [30718, 0.6408245430925432], [30723, 0.6844043674667099], [30729, 0.6491641826974139], [30730, 0.6611130919824112], [30734, 0.6759503678339707], [30739, 0.6296011332412466], [30744, 0.6842440456800395], [30748, 0.6732032061953583], [30750, 0.679000961875111], [30754, 0.6715089278995519], [30761, 0.6452804041832333], [30762, 0.6569412471347778], [30777, 0.6411480806530547], [30782, 0.6408960186452626], [30785, 0.6496698468491053], [30787, 0.669078112432247], [30794, 0.6849050306694098], [30804, 0.6811475018907811], [30812, 0.6580096832732253], [30817, 0.6716793136612421], [30821, 0.6440144301271696], [30838, 0.6534770485440903], [30849, 0.6638553683571237], [30861, 0.6765007938563886], [30868, 0.6640868455598318], [30872, 0.6700290204076854], [30890, 0.6520179444720836], [30904, 0.6600497077195081], [30907, 0.6698828753461392], [30908, 0.6711242286969846], [30917, 0.64119041648439], [30928, 0.6647352228009208], [30931, 0.645920360176669], [30938, 0.6808608339838554], [30945, 0.6666708358191799], [30949, 0.6793868421333568], [30955, 0.6482599710698216], [30957, 0.6436445603639643], [30967, 0.6559145017839461], [30974, 0.6407040257094406], [30978, 0.6501468883532845], [30987, 0.6950767538235261], [30988, 0.7445356081552125], [30994, 0.7348597137887946], [30997, 0.7182919131580036], [31009, 0.7524432578126182], [31019, 0.7919452414703676], [31031, 0.720763487630303], [31039, 0.7136681589147796], [31040, 0.7175439436761293], [31041, 0.8165730845656137], [32218, 0.729711458573955], [32220, 0.7265675478919424], [32224, 0.7366414595556144], [32241, 0.7213544552857597], [32249, 0.7185940138208129], [32252, 0.6971807858191664], [32256, 0.7061573278142939], [32259, 0.6950702015198814], [33213, 0.8803064851184284], [33259, 0.8821084831839892], [33296, 0.8583313038150681], [33302, 0.8720915886192258], [33309, 0.8660069257605115], [33310, 0.8862879618278011], [33311, 0.8715423801958357], [33315, 0.8866582233161322], [33323, 0.8640872364021378], [33332, 0.8762189426357689], [33333, 0.8707213418081459], [33337, 0.909276113677693], [33338, 0.8949029787886731], [33341, 0.9365836874064226], [33346, 0.8975857049391185], [33351, 0.9161146493957396], [33358, 0.9087668358136597], [33359, 0.8746417429549008], [33361, 0.893114218557973], [33370, 0.8976467149811846], [33373, 0.8673642408332886], [33380, 0.8661055589981947], [33386, 0.8790263056255527], [33393, 0.8915589159788706], [33400, 0.8787639243732728], [33414, 0.8971069414901426], [33424, 0.9067176880860129], [33428, 0.902538174123705], [33437, 0.9016918424164887], [33444, 0.8874271870761075], [33453, 0.9400539321402723], [33516, 0.9039717362791704], [33517, 0.8695003379373198], [33518, 0.8853979473977008], [33520, 0.8854012585822685], [33524, 0.9220791107967138], [33533, 0.8918679298793099], [33536, 0.8932950889764406], [33537, 0.8809639981363171], [33543, 0.9149766591137487], [33546, 0.8910324982584641], [33648, 0.9243810660649225], [33704, 0.8889031573165536], [33707, 0.9307889410015118], [33708, 0.9059926285176506], [33712, 0.980167187438088], [33715, 0.9160550770037768], [33722, 0.8989790266044754], [33733, 0.8674379079584553], [33734, 0.8557419958337109], [33756, 0.875667407162526], [33766, 0.8622622032239892], [33802, 0.8557484685810197], [33808, 0.8781901528991796], [33813, 0.8706360332067605], [33818, 0.8562354238072932], [33820, 0.861428104164772], [33826, 0.8799905433332141], [33833, 0.8590625490876018], [34031, 0.8879694262260878], [34034, 0.8902255484405703], [34046, 0.8562503434203027], [34049, 0.8747622637598156], [34052, 0.9378763940561258], [34058, 0.9021968190073616], [34065, 0.8979305129431238], [34068, 0.9080523891470353], [34075, 0.9114233931655474], [34079, 0.8992897494743587], [34113, 0.8713811635548312], [34115, 0.8623594780543284], [34120, 0.8714277016146138], [34126, 0.8728586131528632], [34139, 0.8607858876530878], [34140, 0.8781966308265042], [34141, 0.8876829744148214], [34155, 0.8746903913479119], [34158, 0.8893178504364835], [34160, 0.8947085094358459], [34162, 0.8740213491735034], [34164, 0.8476986978430019]] \ No newline at end of file diff --git a/graphs/summary/linear_model.RidgeBenchmark.time_predict.json b/graphs/summary/linear_model.RidgeBenchmark.time_predict.json index 260f6f4bc6..917a900eb2 100644 --- a/graphs/summary/linear_model.RidgeBenchmark.time_predict.json +++ b/graphs/summary/linear_model.RidgeBenchmark.time_predict.json @@ -1 +1 @@ -[[28497, 0.02038330378280017], [29215, 0.02403147054029701], [29225, 0.02377992684048238], [29227, 0.024380279048216533], [29228, 0.02317080188843028], [29229, 0.024713988653960923], [29235, 0.024123069840295247], [29240, 0.02044308317476556], [29245, 0.0200465260251597], [29246, 0.020045233285356335], [29258, 0.020544571280068803], [29262, 0.019739129619271652], [29279, 0.01993021684970164], [29286, 0.023502418301754452], [29293, 0.020111357460165742], [29294, 0.020394435741273746], [29295, 0.020070484739715025], [29296, 0.02213049402657172], [29313, 0.021538924053048577], [29318, 0.02021604747603172], [29319, 0.020165303324918823], [29322, 0.02022794722186189], [29325, 0.019838088328024594], [29327, 0.019584336559478062], [29328, 0.020713247119764466], [29340, 0.02373130439130299], [29344, 0.020079477921797626], [29349, 0.020119090355860333], [29364, 0.02023727798788738], [29371, 0.020182823714055397], [29376, 0.020600460813203273], [29381, 0.0201837017171718], [29383, 0.02343395334316052], [29387, 0.020300073166453693], [29401, 0.020318030509919215], [29404, 0.019999701169277177], [29409, 0.01961025606574197], [29414, 0.020096437784449826], [29415, 0.02004366933712566], [29420, 0.020342226133893467], [29421, 0.020767808016871874], [29425, 0.019630945648500066], [29429, 0.020089727119691973], [29435, 0.028207248256726013], [29443, 0.02767106597841287], [29446, 0.024333589341663197], [29453, 0.02541553586079722], [29454, 0.02543889146978896], [29455, 0.023903746512403994], [29457, 0.02428371438637849], [29458, 0.024713839848185617], [29469, 0.026374289169990132], [29541, 0.02527400537371933], [29548, 0.024566843282220176], [29550, 0.024825121179594473], [29551, 0.022232552514604754], [29572, 0.022287708397501525], [29591, 0.022345628089964733], [29598, 0.022833350202902065], [29609, 0.022606971117630065], [29611, 0.021664485390977022], [29621, 0.021366220894683152], [29638, 0.021663919303552666], [29644, 0.021820306822480613], [29648, 0.022356158854542823], [29652, 0.021700178838141904], [29656, 0.02232668180547799], [29657, 0.021667424736259978], [29662, 0.022390889827124963], [29665, 0.022655639090904747], [29667, 0.021773522116080156], [29735, 0.02188488758585486], [29742, 0.02194956071796949], [29750, 0.0246561706392589], [29753, 0.021675564718117758], [29757, 0.022078194759702487], [29761, 0.02300444135902556], [29765, 0.022357244027127084], [29766, 0.02252339747440075], [29768, 0.02165328086238801], [29776, 0.027425117141318876], [29783, 0.023527613385108025], [29788, 0.022863582989820726], [29789, 0.023616194564793875], [29790, 0.02375491525662121], [29795, 0.024136759799797115], [29798, 0.023124325152328807], [29805, 0.022775392633795487], [29806, 0.02308861869217674], [29807, 0.024221699080156475], [29808, 0.022412449639754122], [29813, 0.023579778738468324], [29815, 0.02304999889200686], [29828, 0.021995146779889205], [29839, 0.024800712768349536], [29844, 0.02314665466799021], [29858, 0.023984800420930034], [29865, 0.02397812869045574], [29999, 0.0235463153331296], [30002, 0.02375478242398664], [30010, 0.023930355759932916], [30013, 0.023207795471431897], [30023, 0.02393411321217501], [30028, 0.023366275732104116], [30035, 0.023907770490392218], [30046, 0.023875509305139167], [30053, 0.022561094503763524], [30066, 0.023691258520435594], [30068, 0.022712647174300302], [30070, 0.023339833374564092], [30074, 0.02445378036823682], [30076, 0.023020729215179756], [30077, 0.0234600650064785], [30078, 0.023834093331041133], [30085, 0.0238004941613946], [30086, 0.02357427939010487], [30096, 0.023622029163596084], [30104, 0.023508321534045234], [30106, 0.021737016216930367], [30112, 0.022345122555534738], [30116, 0.022611850993854984], [30118, 0.023428148485608417], [30123, 0.022356534319237568], [30128, 0.02505119685643596], [30135, 0.02446589633929628], [30145, 0.02324470713491343], [30155, 0.02212710461116327], [30156, 0.0243564854725585], [30157, 0.02299928284644161], [30165, 0.022767532149578405], [30174, 0.02416996395872944], [30179, 0.023550708593097127], [30185, 0.022940295978729996], [30189, 0.022892496703842816], [30190, 0.02364230499720234], [30198, 0.024288479790094214], [30202, 0.023949541803047435], [30203, 0.022507438407854508], [30208, 0.023444863936304936], [30212, 0.02380587523461572], [30213, 0.02460411550907237], [30215, 0.0237245475925767], [30218, 0.024252885882001432], [30225, 0.02287979440078877], [30227, 0.02329902458460948], [30233, 0.02208688984183105], [30235, 0.022310779080797153], [30238, 0.022959750234944388], [30244, 0.022966447397375436], [30248, 0.02319135427615718], [30254, 0.024294750802758797], [30259, 0.022959053449377362], [30260, 0.022972964874344], [30501, 0.023552991452560956], [30502, 0.02433901709079953], [30506, 0.022235457448521307], [30507, 0.02275412750876604], [30510, 0.02295725153418342], [30515, 0.022887055518914227], [30519, 0.023149087105764438], [30520, 0.024241105373186356], [30524, 0.022980709311337697], [30525, 0.023322204619283568], [30529, 0.023578572548482623], [30533, 0.023325497676610074], [30538, 0.024414774012552074], [30542, 0.0229405548054315], [30543, 0.023745611051306768], [30544, 0.022950054250101364], [30545, 0.023711225513891234], [30550, 0.02251034096069197], [30552, 0.023543764035478486], [30556, 0.023804366966078253], [30561, 0.022929200484220705], [30564, 0.02370074098851968], [30565, 0.024005171675514782], [30577, 0.023786701404194255], [30581, 0.02440872930010223], [30586, 0.02488987710975558], [30593, 0.022772428282638552], [30615, 0.02292875883898455], [30621, 0.023337115401402046], [30622, 0.023411202722221944], [30629, 0.02293512470029632], [30635, 0.02418116782908172], [30639, 0.023133613733462857], [30640, 0.023073802373583984], [30643, 0.02408751026190094], [30646, 0.023507786592147493], [30647, 0.02530352785450394], [30650, 0.023779794096994256], [30657, 0.024210764511041948], [30665, 0.023139047566735675], [30670, 0.024627210290846344], [30675, 0.023211981403078], [30679, 0.02418570540163986], [30694, 0.023584460548344108], [30704, 0.023056338481907617], [30708, 0.02383351595454784], [30718, 0.02312951832918303], [30723, 0.022670591664013445], [30729, 0.022999229806855793], [30730, 0.022825791734939073], [30734, 0.02424136184748719], [30739, 0.022860896681544486], [30744, 0.023863423682432515], [30748, 0.023819417820386324], [30750, 0.02357363093836105], [30754, 0.02444518754624007], [30761, 0.02420041686903202], [30762, 0.022982842235889037], [30777, 0.02421855805155249], [30782, 0.02251655794322395], [30785, 0.023689760233512033], [30787, 0.02370002655490921], [30794, 0.02400067332850227], [30804, 0.023160548967738455], [30812, 0.023692712200649106], [30817, 0.024074454264568394], [30821, 0.022970582686993927], [30838, 0.02432788482605717], [30849, 0.022959472557754688], [30861, 0.022674598140133284], [30868, 0.023202371347645804], [30872, 0.02281043819216472], [30890, 0.023177585786646342], [30904, 0.022942356117083822], [30907, 0.024110267218432128], [30908, 0.023566534062866865], [30917, 0.02297772361607084], [30928, 0.02343188243121094], [30931, 0.02240786708131607], [30938, 0.0225726877838664], [30945, 0.02426363239634491], [30949, 0.02382969631967477], [30955, 0.023722378503380406], [30957, 0.023691133974088], [30967, 0.024167584179187757], [30974, 0.023862732439662495], [30978, 0.022281310363419352], [30987, 0.023329014937287538], [30988, 0.02397539965842261], [30994, 0.02251536773621269], [30997, 0.024222869799916308], [31009, 0.02219491690366157], [31019, 0.024258962850226704], [31031, 0.023342244998353367], [31039, 0.023902215217474137], [31040, 0.024159141997143453], [31041, 0.02329343038869212], [32218, 0.015589303348861815], [32220, 0.01530327982188378], [32224, 0.01550465441985876], [32241, 0.015072890191399997], [32249, 0.014825656964279735], [32252, 0.014776091112824076], [32256, 0.015230803985200336], [32259, 0.01456480785951458], [33213, 0.014205171450837141], [33259, 0.013917940420030821], [33296, 0.015292138524114957], [33302, 0.014077424373906118], [33309, 0.013718505202803755], [33310, 0.013850438968983504], [33311, 0.014405972809381249], [33315, 0.013603143820321842], [33323, 0.014056575316790009], [33332, 0.01401543015643314], [33333, 0.01417487426499454], [33337, 0.015015827267144871], [33338, 0.014016213269110709], [33341, 0.013983042159910778], [33346, 0.013856903241850582], [33351, 0.014605085486023269], [33358, 0.014605590247428982], [33359, 0.0140404708397851], [33361, 0.013764362208670444], [33370, 0.01428963540668104], [33373, 0.013383385209442576], [33380, 0.014055374825475473], [33386, 0.013815823672986298], [33393, 0.014616574549829847], [33400, 0.013766478986347414], [33414, 0.01441066327402652], [33424, 0.013491900558172922], [33428, 0.014475671392308551], [33437, 0.013739199007407391], [33444, 0.013629278837862129], [33453, 0.015058265416239919], [33516, 0.014080311216846657], [33517, 0.01318675232023405], [33518, 0.013446229971135688], [33520, 0.014421510864707828], [33524, 0.014593252891385938], [33533, 0.014871496911900891], [33536, 0.013300051601280557], [33537, 0.01434965514322078], [33543, 0.014057955558696267], [33546, 0.01516045195538313], [33648, 0.013669020385973786], [33704, 0.013894765017860751], [33707, 0.014476383690428384], [33708, 0.013695683477729766], [33712, 0.014395862534261802], [33715, 0.013666246272107541], [33722, 0.014973051372680584], [33733, 0.014228877246598028], [33734, 0.013688264123379066], [33756, 0.014044897523880667], [33766, 0.01382703528222701], [33802, 0.014494968826812005], [33808, 0.014871129325173064], [33813, 0.014117620816594945], [33818, 0.014980915864614735], [33820, 0.014462240522871433], [33826, 0.013990405482271906], [33833, 0.014143678064446575], [34031, 0.014308968949576251], [34034, 0.01411811377584114], [34046, 0.014380440276772183], [34049, 0.014528142348706493], [34052, 0.013968022821164551], [34058, 0.014295600988948276], [34065, 0.013904465324900268], [34068, 0.014502651990729086], [34075, 0.0146259717027325], [34079, 0.014122478650259342], [34113, 0.0149648099815749], [34115, 0.01369102765985351], [34120, 0.014129505418078864], [34126, 0.014426188331192552], [34139, 0.014784147998637958], [34140, 0.014323427391016424], [34141, 0.014565360448357703], [34155, 0.013253626814500846], [34158, 0.014714969319666819], [34160, 0.0144285428399125], [34162, 0.014087399240070997]] \ No newline at end of file +[[28497, 0.02038330378280017], [29215, 0.02403147054029701], [29225, 0.02377992684048238], [29227, 0.024380279048216533], [29228, 0.02317080188843028], [29229, 0.024713988653960923], [29235, 0.024123069840295247], [29240, 0.02044308317476556], [29245, 0.0200465260251597], [29246, 0.020045233285356335], [29258, 0.020544571280068803], [29262, 0.019739129619271652], [29279, 0.01993021684970164], [29286, 0.023502418301754452], [29293, 0.020111357460165742], [29294, 0.020394435741273746], [29295, 0.020070484739715025], [29296, 0.02213049402657172], [29313, 0.021538924053048577], [29318, 0.02021604747603172], [29319, 0.020165303324918823], [29322, 0.02022794722186189], [29325, 0.019838088328024594], [29327, 0.019584336559478062], [29328, 0.020713247119764466], [29340, 0.02373130439130299], [29344, 0.020079477921797626], [29349, 0.020119090355860333], [29364, 0.02023727798788738], [29371, 0.020182823714055397], [29376, 0.020600460813203273], [29381, 0.0201837017171718], [29383, 0.02343395334316052], [29387, 0.020300073166453693], [29401, 0.020318030509919215], [29404, 0.019999701169277177], [29409, 0.01961025606574197], [29414, 0.020096437784449826], [29415, 0.02004366933712566], [29420, 0.020342226133893467], [29421, 0.020767808016871874], [29425, 0.019630945648500066], [29429, 0.020089727119691973], [29435, 0.028207248256726013], [29443, 0.02767106597841287], [29446, 0.024333589341663197], [29453, 0.02541553586079722], [29454, 0.02543889146978896], [29455, 0.023903746512403994], [29457, 0.02428371438637849], [29458, 0.024713839848185617], [29469, 0.026374289169990132], [29541, 0.02527400537371933], [29548, 0.024566843282220176], [29550, 0.024825121179594473], [29551, 0.022232552514604754], [29572, 0.022287708397501525], [29591, 0.022345628089964733], [29598, 0.022833350202902065], [29609, 0.022606971117630065], [29611, 0.021664485390977022], [29621, 0.021366220894683152], [29638, 0.021663919303552666], [29644, 0.021820306822480613], [29648, 0.022356158854542823], [29652, 0.021700178838141904], [29656, 0.02232668180547799], [29657, 0.021667424736259978], [29662, 0.022390889827124963], [29665, 0.022655639090904747], [29667, 0.021773522116080156], [29735, 0.02188488758585486], [29742, 0.02194956071796949], [29750, 0.0246561706392589], [29753, 0.021675564718117758], [29757, 0.022078194759702487], [29761, 0.02300444135902556], [29765, 0.022357244027127084], [29766, 0.02252339747440075], [29768, 0.02165328086238801], [29776, 0.027425117141318876], [29783, 0.023527613385108025], [29788, 0.022863582989820726], [29789, 0.023616194564793875], [29790, 0.02375491525662121], [29795, 0.024136759799797115], [29798, 0.023124325152328807], [29805, 0.022775392633795487], [29806, 0.02308861869217674], [29807, 0.024221699080156475], [29808, 0.022412449639754122], [29813, 0.023579778738468324], [29815, 0.02304999889200686], [29828, 0.021995146779889205], [29839, 0.024800712768349536], [29844, 0.02314665466799021], [29858, 0.023984800420930034], [29865, 0.02397812869045574], [29999, 0.0235463153331296], [30002, 0.02375478242398664], [30010, 0.023930355759932916], [30013, 0.023207795471431897], [30023, 0.02393411321217501], [30028, 0.023366275732104116], [30035, 0.023907770490392218], [30046, 0.023875509305139167], [30053, 0.022561094503763524], [30066, 0.023691258520435594], [30068, 0.022712647174300302], [30070, 0.023339833374564092], [30074, 0.02445378036823682], [30076, 0.023020729215179756], [30077, 0.0234600650064785], [30078, 0.023834093331041133], [30085, 0.0238004941613946], [30086, 0.02357427939010487], [30096, 0.023622029163596084], [30104, 0.023508321534045234], [30106, 0.021737016216930367], [30112, 0.022345122555534738], [30116, 0.022611850993854984], [30118, 0.023428148485608417], [30123, 0.022356534319237568], [30128, 0.02505119685643596], [30135, 0.02446589633929628], [30145, 0.02324470713491343], [30155, 0.02212710461116327], [30156, 0.0243564854725585], [30157, 0.02299928284644161], [30165, 0.022767532149578405], [30174, 0.02416996395872944], [30179, 0.023550708593097127], [30185, 0.022940295978729996], [30189, 0.022892496703842816], [30190, 0.02364230499720234], [30198, 0.024288479790094214], [30202, 0.023949541803047435], [30203, 0.022507438407854508], [30208, 0.023444863936304936], [30212, 0.02380587523461572], [30213, 0.02460411550907237], [30215, 0.0237245475925767], [30218, 0.024252885882001432], [30225, 0.02287979440078877], [30227, 0.02329902458460948], [30233, 0.02208688984183105], [30235, 0.022310779080797153], [30238, 0.022959750234944388], [30244, 0.022966447397375436], [30248, 0.02319135427615718], [30254, 0.024294750802758797], [30259, 0.022959053449377362], [30260, 0.022972964874344], [30501, 0.023552991452560956], [30502, 0.02433901709079953], [30506, 0.022235457448521307], [30507, 0.02275412750876604], [30510, 0.02295725153418342], [30515, 0.022887055518914227], [30519, 0.023149087105764438], [30520, 0.024241105373186356], [30524, 0.022980709311337697], [30525, 0.023322204619283568], [30529, 0.023578572548482623], [30533, 0.023325497676610074], [30538, 0.024414774012552074], [30542, 0.0229405548054315], [30543, 0.023745611051306768], [30544, 0.022950054250101364], [30545, 0.023711225513891234], [30550, 0.02251034096069197], [30552, 0.023543764035478486], [30556, 0.023804366966078253], [30561, 0.022929200484220705], [30564, 0.02370074098851968], [30565, 0.024005171675514782], [30577, 0.023786701404194255], [30581, 0.02440872930010223], [30586, 0.02488987710975558], [30593, 0.022772428282638552], [30615, 0.02292875883898455], [30621, 0.023337115401402046], [30622, 0.023411202722221944], [30629, 0.02293512470029632], [30635, 0.02418116782908172], [30639, 0.023133613733462857], [30640, 0.023073802373583984], [30643, 0.02408751026190094], [30646, 0.023507786592147493], [30647, 0.02530352785450394], [30650, 0.023779794096994256], [30657, 0.024210764511041948], [30665, 0.023139047566735675], [30670, 0.024627210290846344], [30675, 0.023211981403078], [30679, 0.02418570540163986], [30694, 0.023584460548344108], [30704, 0.023056338481907617], [30708, 0.02383351595454784], [30718, 0.02312951832918303], [30723, 0.022670591664013445], [30729, 0.022999229806855793], [30730, 0.022825791734939073], [30734, 0.02424136184748719], [30739, 0.022860896681544486], [30744, 0.023863423682432515], [30748, 0.023819417820386324], [30750, 0.02357363093836105], [30754, 0.02444518754624007], [30761, 0.02420041686903202], [30762, 0.022982842235889037], [30777, 0.02421855805155249], [30782, 0.02251655794322395], [30785, 0.023689760233512033], [30787, 0.02370002655490921], [30794, 0.02400067332850227], [30804, 0.023160548967738455], [30812, 0.023692712200649106], [30817, 0.024074454264568394], [30821, 0.022970582686993927], [30838, 0.02432788482605717], [30849, 0.022959472557754688], [30861, 0.022674598140133284], [30868, 0.023202371347645804], [30872, 0.02281043819216472], [30890, 0.023177585786646342], [30904, 0.022942356117083822], [30907, 0.024110267218432128], [30908, 0.023566534062866865], [30917, 0.02297772361607084], [30928, 0.02343188243121094], [30931, 0.02240786708131607], [30938, 0.0225726877838664], [30945, 0.02426363239634491], [30949, 0.02382969631967477], [30955, 0.023722378503380406], [30957, 0.023691133974088], [30967, 0.024167584179187757], [30974, 0.023862732439662495], [30978, 0.022281310363419352], [30987, 0.023329014937287538], [30988, 0.02397539965842261], [30994, 0.02251536773621269], [30997, 0.024222869799916308], [31009, 0.02219491690366157], [31019, 0.024258962850226704], [31031, 0.023342244998353367], [31039, 0.023902215217474137], [31040, 0.024159141997143453], [31041, 0.02329343038869212], [32218, 0.015589303348861815], [32220, 0.01530327982188378], [32224, 0.01550465441985876], [32241, 0.015072890191399997], [32249, 0.014825656964279735], [32252, 0.014776091112824076], [32256, 0.015230803985200336], [32259, 0.01456480785951458], [33213, 0.014205171450837141], [33259, 0.013917940420030821], [33296, 0.015292138524114957], [33302, 0.014077424373906118], [33309, 0.013718505202803755], [33310, 0.013850438968983504], [33311, 0.014405972809381249], [33315, 0.013603143820321842], [33323, 0.014056575316790009], [33332, 0.01401543015643314], [33333, 0.01417487426499454], [33337, 0.015015827267144871], [33338, 0.014016213269110709], [33341, 0.013983042159910778], [33346, 0.013856903241850582], [33351, 0.014605085486023269], [33358, 0.014605590247428982], [33359, 0.0140404708397851], [33361, 0.013764362208670444], [33370, 0.01428963540668104], [33373, 0.013383385209442576], [33380, 0.014055374825475473], [33386, 0.013815823672986298], [33393, 0.014616574549829847], [33400, 0.013766478986347414], [33414, 0.01441066327402652], [33424, 0.013491900558172922], [33428, 0.014475671392308551], [33437, 0.013739199007407391], [33444, 0.013629278837862129], [33453, 0.015058265416239919], [33516, 0.014080311216846657], [33517, 0.01318675232023405], [33518, 0.013446229971135688], [33520, 0.014421510864707828], [33524, 0.014593252891385938], [33533, 0.014871496911900891], [33536, 0.013300051601280557], [33537, 0.01434965514322078], [33543, 0.014057955558696267], [33546, 0.01516045195538313], [33648, 0.013669020385973786], [33704, 0.013894765017860751], [33707, 0.014476383690428384], [33708, 0.013695683477729766], [33712, 0.014395862534261802], [33715, 0.013666246272107541], [33722, 0.014973051372680584], [33733, 0.014228877246598028], [33734, 0.013688264123379066], [33756, 0.014044897523880667], [33766, 0.01382703528222701], [33802, 0.014494968826812005], [33808, 0.014871129325173064], [33813, 0.014117620816594945], [33818, 0.014980915864614735], [33820, 0.014462240522871433], [33826, 0.013990405482271906], [33833, 0.014143678064446575], [34031, 0.014308968949576251], [34034, 0.01411811377584114], [34046, 0.014380440276772183], [34049, 0.014528142348706493], [34052, 0.013968022821164551], [34058, 0.014295600988948276], [34065, 0.013904465324900268], [34068, 0.014502651990729086], [34075, 0.0146259717027325], [34079, 0.014122478650259342], [34113, 0.0149648099815749], [34115, 0.01369102765985351], [34120, 0.014129505418078864], [34126, 0.014426188331192552], [34139, 0.014784147998637958], [34140, 0.014323427391016424], [34141, 0.014565360448357703], [34155, 0.013253626814500846], [34158, 0.014714969319666819], [34160, 0.0144285428399125], [34162, 0.014087399240070997], [34164, 0.013559850413884468]] \ No newline at end of file diff --git a/graphs/summary/linear_model.RidgeBenchmark.track_test_score.json b/graphs/summary/linear_model.RidgeBenchmark.track_test_score.json index 79d656b73c..2c275d0bcd 100644 --- a/graphs/summary/linear_model.RidgeBenchmark.track_test_score.json +++ b/graphs/summary/linear_model.RidgeBenchmark.track_test_score.json @@ -1 +1 @@ -[[28497, 0.9496812391690304], [29215, 0.949289818901943], [29225, 0.9494072484443746], [29227, 0.9494088611363202], [29228, 0.9492839014029104], [29229, 0.9492562076385457], [29235, 0.9492869416640946], [29240, 0.9491824801440009], [29245, 0.949310496699852], [29246, 0.9496940307011758], [29258, 0.9493679201722516], [29262, 0.948974462555284], [29279, 0.9487226539931273], [29286, 0.9493478457248852], [29293, 0.9488800997793047], [29294, 0.9490366945626578], [29295, 0.9492967855458314], [29296, 0.949185207636688], [29313, 0.94923644933987], [29318, 0.9494136523347155], [29319, 0.9493365204068129], [29322, 0.9489993941357894], [29325, 0.949229266853427], [29327, 0.9492031270362713], [29328, 0.949437370155923], [29340, 0.9488216310622783], [29344, 0.9489343768015551], [29349, 0.9498234031892471], [29364, 0.9491502030328625], [29371, 0.9490323861411628], [29376, 0.9492681753314838], [29381, 0.9494464631855956], [29383, 0.9493927997402581], [29387, 0.94933907708995], [29401, 0.9495514060730782], [29404, 0.9491939867314789], [29409, 0.9490606970287806], [29414, 0.9492697276101151], [29415, 0.9493469256193539], [29420, 0.9494774228963467], [29421, 0.9492389925604889], [29425, 0.9491047242877901], [29429, 0.9491313258705343], [29435, 0.9494383347523667], [29443, 0.9496881852312009], [29446, 0.9491907326990252], [29453, 0.949030087343655], [29454, 0.9488918340215943], [29455, 0.9488357024041241], [29457, 0.9494295158763124], [29458, 0.9495119037986752], [29469, 0.9488218873243907], [29541, 0.9491640600477996], [29548, 0.9495763134816368], [29550, 0.9493849492151302], [29551, 0.9494080354525298], [29572, 0.9493642537390924], [29591, 0.9492614615332994], [29598, 0.9495380159211585], [29609, 0.949596207327726], [29611, 0.9495633141678975], [29621, 0.9494250647479154], [29638, 0.9493816698482247], [29644, 0.9494454688254143], [29648, 0.9497096415493681], [29652, 0.9485828511611676], [29656, 0.9489152735249703], [29657, 0.9493522255340742], [29662, 0.9492614573811808], [29665, 0.9484458668421202], [29667, 0.9494975679968833], [29735, 0.9484757040326346], [29742, 0.9494670649660717], [29750, 0.949101685298991], [29753, 0.9495765290776433], [29757, 0.9493863732236419], [29761, 0.9495267429874179], [29765, 0.9493118573245838], [29766, 0.9490070091482279], [29768, 0.9495905602538242], [29776, 0.9490253801555757], [29783, 0.9496597862214322], [29788, 0.9492013533879792], [29789, 0.9487854796492758], [29790, 0.9497474439114737], [29795, 0.9494219802290337], [29798, 0.9496657287503396], [29805, 0.9486939333495725], [29806, 0.9492580653059195], [29807, 0.9492229335876886], [29808, 0.949523716030994], [29813, 0.9496094670165347], [29815, 0.9490480516570834], [29828, 0.9492610107547662], [29839, 0.9490884275567548], [29844, 0.9490267256282128], [29858, 0.9492606745908052], [29865, 0.9498758192238754], [29999, 0.9493939186593926], [30002, 0.9491382451143866], [30010, 0.9491617309098223], [30013, 0.9493940381042204], [30023, 0.9491841993890018], [30028, 0.9492721648401061], [30035, 0.9487323638290581], [30046, 0.9493769445350765], [30053, 0.9493653005557398], [30066, 0.9495998410297245], [30068, 0.9495461021273731], [30070, 0.9493913542860766], [30074, 0.9487807603555326], [30076, 0.9490402327923223], [30077, 0.9498669275657755], [30078, 0.9490053171868018], [30085, 0.9494328688846724], [30086, 0.9491941352911689], [30096, 0.9494250697650862], [30104, 0.9490984857375337], [30106, 0.9492008067734812], [30112, 0.9492375368298325], [30116, 0.949109813382886], [30118, 0.9491473565198465], [30123, 0.9490851009514459], [30128, 0.9493392319420652], [30135, 0.9490210348045045], [30145, 0.9490508917068645], [30155, 0.9494298094415413], [30156, 0.9493076444446653], [30157, 0.9488533047591571], [30165, 0.9486213630485366], [30174, 0.9497514419054364], [30179, 0.9492363501416797], [30185, 0.9494938074007866], [30189, 0.9489761652491318], [30190, 0.949045442438076], [30198, 0.9491294758420823], [30202, 0.9495943866276], [30203, 0.949418431512859], [30208, 0.9493215843938927], [30212, 0.9495048930253985], [30213, 0.9489753656334876], [30215, 0.9495952807950556], [30218, 0.949414440768517], [30225, 0.9493915986991329], [30227, 0.9490300797389857], [30233, 0.9493559968260314], [30235, 0.9488183382215799], [30238, 0.9495737411806277], [30244, 0.9493646121763273], [30248, 0.9492041395511921], [30254, 0.9492049144177783], [30259, 0.9494260864790702], [30260, 0.9491470813465589], [30501, 0.949187090783212], [30502, 0.9496374128589998], [30506, 0.9496262668652302], [30507, 0.9490453182537923], [30510, 0.94913413933213], [30515, 0.9489308519594464], [30519, 0.9494192327264727], [30520, 0.9494455737934114], [30524, 0.9485693108164488], [30525, 0.9489989555941335], [30529, 0.9492190644185173], [30533, 0.9487845240147946], [30538, 0.9491490176202986], [30542, 0.9491515078145121], [30543, 0.9492266670641089], [30544, 0.9489509636146871], [30545, 0.9491341504012633], [30550, 0.9489927382479721], [30552, 0.9497254484886748], [30556, 0.9495763958851585], [30561, 0.9491985540844412], [30564, 0.949293976983775], [30565, 0.9494175965031091], [30577, 0.9492179693023344], [30581, 0.9490337721254899], [30586, 0.9491665923342885], [30593, 0.9490297588213223], [30615, 0.948986209883768], [30621, 0.948671782615986], [30622, 0.9493209105893496], [30629, 0.949318507428452], [30635, 0.9489079676669392], [30639, 0.9493131212444292], [30640, 0.9491273129393697], [30643, 0.9492794965931994], [30646, 0.9488298943931032], [30647, 0.9490903858203578], [30650, 0.9487828973102849], [30657, 0.9492614270142304], [30665, 0.9496083720408919], [30670, 0.9489170841937721], [30675, 0.9485780105755182], [30679, 0.9490747164572861], [30694, 0.9488559609147807], [30704, 0.9490533921190544], [30708, 0.9489607226989647], [30718, 0.9495057554961038], [30723, 0.9488804678866466], [30729, 0.9493101247438916], [30730, 0.9496408210912837], [30734, 0.949256510310315], [30739, 0.9498341933984116], [30744, 0.9494082068193799], [30748, 0.9495643079186247], [30750, 0.949580613803401], [30754, 0.9493341175562159], [30761, 0.9489234871262433], [30762, 0.9492634668136427], [30777, 0.9495383858758734], [30782, 0.9490601901152839], [30785, 0.9494429008275979], [30787, 0.9494631998836041], [30794, 0.9488565582027845], [30804, 0.9490021436544785], [30812, 0.9489738436877041], [30817, 0.9492439407219129], [30821, 0.9492442169498907], [30838, 0.9492877924634299], [30849, 0.9493095507678998], [30861, 0.9492751747624577], [30868, 0.9494224389391029], [30872, 0.9493634753815796], [30890, 0.9492021918879539], [30904, 0.9495314570129172], [30907, 0.9493401353775637], [30908, 0.9496139598053337], [30917, 0.9496032059649376], [30928, 0.9488143421977788], [30931, 0.9495162365356116], [30938, 0.9495663428060128], [30945, 0.9490342788839696], [30949, 0.9494592414686698], [30955, 0.9488692573385492], [30957, 0.9495443968666818], [30967, 0.949558903620055], [30974, 0.9490914872236322], [30978, 0.9494430750556927], [30987, 0.9496693538596728], [30988, 0.9493168754447111], [30994, 0.9492434574203014], [30997, 0.9487433473368617], [31009, 0.9494762028856538], [31019, 0.948675588364969], [31031, 0.9489503481003031], [31039, 0.9492640525470329], [31040, 0.9494087542388009], [31041, 0.9496533392846398], [32218, 0.9496420637803128], [32220, 0.94976747135745], [32224, 0.9490156109654808], [32241, 0.9492040843765606], [32249, 0.9494403666063548], [32252, 0.9494872933025053], [32256, 0.94933769147982], [32259, 0.9497981868551141], [33213, 0.9489432514029298], [33259, 0.9491567624883966], [33296, 0.9491211493370174], [33302, 0.9493378521763116], [33309, 0.9490687450809406], [33310, 0.9489523031623103], [33311, 0.9493566023535911], [33315, 0.9497811940481811], [33323, 0.9494057637629196], [33332, 0.9489629314508572], [33333, 0.9493309059220171], [33337, 0.9493332316873935], [33338, 0.9494635231231291], [33341, 0.9488122588881185], [33346, 0.9493692836065154], [33351, 0.9492452406365007], [33358, 0.949556044651534], [33359, 0.9486806378724809], [33361, 0.9495094774931312], [33370, 0.949442740694171], [33373, 0.9497424957760818], [33380, 0.9495566818251576], [33386, 0.9490624069692312], [33393, 0.9490321749799937], [33400, 0.9496902525221382], [33414, 0.9489820710648562], [33424, 0.9490149598327923], [33428, 0.9495331549201204], [33437, 0.94958307239815], [33444, 0.9491993276136375], [33453, 0.9488004726948344], [33516, 0.94901904399825], [33517, 0.9496021601241941], [33518, 0.949262421925893], [33520, 0.94949153064751], [33524, 0.9495735642905176], [33533, 0.9493545125557793], [33536, 0.9494251201375223], [33537, 0.9491480771254651], [33543, 0.9493026112545744], [33546, 0.9490199787562744], [33648, 0.9491667874493087], [33704, 0.9489930629060414], [33707, 0.9494294119351844], [33708, 0.9495334711830784], [33712, 0.9492108984824643], [33715, 0.9492089683291463], [33722, 0.9488337058644081], [33733, 0.9483482990669251], [33734, 0.9490490915511592], [33756, 0.9495141080690113], [33766, 0.9493551415629777], [33802, 0.9493817272666784], [33808, 0.9491188519454208], [33813, 0.949232870528335], [33818, 0.9491819424548059], [33820, 0.9492773684118239], [33826, 0.949745648152415], [33833, 0.9489209318171092], [34031, 0.9489450411885428], [34034, 0.9491539571251792], [34046, 0.9494421911277732], [34049, 0.9497616409636123], [34052, 0.949050208744822], [34058, 0.9491827533351889], [34065, 0.9487628170719324], [34068, 0.949215088494552], [34075, 0.9494009065385718], [34079, 0.949806737550645], [34113, 0.9494217270387941], [34115, 0.949364770017755], [34120, 0.9491035137025112], [34126, 0.9488856692428476], [34139, 0.9491868040078965], [34140, 0.949671922512336], [34141, 0.9493913624258294], [34155, 0.94906283229951], [34158, 0.9494319635097784], [34160, 0.9494040794416674], [34162, 0.9497864970624093]] \ No newline at end of file +[[28497, 0.9496812391690304], [29215, 0.949289818901943], [29225, 0.9494072484443746], [29227, 0.9494088611363202], [29228, 0.9492839014029104], [29229, 0.9492562076385457], [29235, 0.9492869416640946], [29240, 0.9491824801440009], [29245, 0.949310496699852], [29246, 0.9496940307011758], [29258, 0.9493679201722516], [29262, 0.948974462555284], [29279, 0.9487226539931273], [29286, 0.9493478457248852], [29293, 0.9488800997793047], [29294, 0.9490366945626578], [29295, 0.9492967855458314], [29296, 0.949185207636688], [29313, 0.94923644933987], [29318, 0.9494136523347155], [29319, 0.9493365204068129], [29322, 0.9489993941357894], [29325, 0.949229266853427], [29327, 0.9492031270362713], [29328, 0.949437370155923], [29340, 0.9488216310622783], [29344, 0.9489343768015551], [29349, 0.9498234031892471], [29364, 0.9491502030328625], [29371, 0.9490323861411628], [29376, 0.9492681753314838], [29381, 0.9494464631855956], [29383, 0.9493927997402581], [29387, 0.94933907708995], [29401, 0.9495514060730782], [29404, 0.9491939867314789], [29409, 0.9490606970287806], [29414, 0.9492697276101151], [29415, 0.9493469256193539], [29420, 0.9494774228963467], [29421, 0.9492389925604889], [29425, 0.9491047242877901], [29429, 0.9491313258705343], [29435, 0.9494383347523667], [29443, 0.9496881852312009], [29446, 0.9491907326990252], [29453, 0.949030087343655], [29454, 0.9488918340215943], [29455, 0.9488357024041241], [29457, 0.9494295158763124], [29458, 0.9495119037986752], [29469, 0.9488218873243907], [29541, 0.9491640600477996], [29548, 0.9495763134816368], [29550, 0.9493849492151302], [29551, 0.9494080354525298], [29572, 0.9493642537390924], [29591, 0.9492614615332994], [29598, 0.9495380159211585], [29609, 0.949596207327726], [29611, 0.9495633141678975], [29621, 0.9494250647479154], [29638, 0.9493816698482247], [29644, 0.9494454688254143], [29648, 0.9497096415493681], [29652, 0.9485828511611676], [29656, 0.9489152735249703], [29657, 0.9493522255340742], [29662, 0.9492614573811808], [29665, 0.9484458668421202], [29667, 0.9494975679968833], [29735, 0.9484757040326346], [29742, 0.9494670649660717], [29750, 0.949101685298991], [29753, 0.9495765290776433], [29757, 0.9493863732236419], [29761, 0.9495267429874179], [29765, 0.9493118573245838], [29766, 0.9490070091482279], [29768, 0.9495905602538242], [29776, 0.9490253801555757], [29783, 0.9496597862214322], [29788, 0.9492013533879792], [29789, 0.9487854796492758], [29790, 0.9497474439114737], [29795, 0.9494219802290337], [29798, 0.9496657287503396], [29805, 0.9486939333495725], [29806, 0.9492580653059195], [29807, 0.9492229335876886], [29808, 0.949523716030994], [29813, 0.9496094670165347], [29815, 0.9490480516570834], [29828, 0.9492610107547662], [29839, 0.9490884275567548], [29844, 0.9490267256282128], [29858, 0.9492606745908052], [29865, 0.9498758192238754], [29999, 0.9493939186593926], [30002, 0.9491382451143866], [30010, 0.9491617309098223], [30013, 0.9493940381042204], [30023, 0.9491841993890018], [30028, 0.9492721648401061], [30035, 0.9487323638290581], [30046, 0.9493769445350765], [30053, 0.9493653005557398], [30066, 0.9495998410297245], [30068, 0.9495461021273731], [30070, 0.9493913542860766], [30074, 0.9487807603555326], [30076, 0.9490402327923223], [30077, 0.9498669275657755], [30078, 0.9490053171868018], [30085, 0.9494328688846724], [30086, 0.9491941352911689], [30096, 0.9494250697650862], [30104, 0.9490984857375337], [30106, 0.9492008067734812], [30112, 0.9492375368298325], [30116, 0.949109813382886], [30118, 0.9491473565198465], [30123, 0.9490851009514459], [30128, 0.9493392319420652], [30135, 0.9490210348045045], [30145, 0.9490508917068645], [30155, 0.9494298094415413], [30156, 0.9493076444446653], [30157, 0.9488533047591571], [30165, 0.9486213630485366], [30174, 0.9497514419054364], [30179, 0.9492363501416797], [30185, 0.9494938074007866], [30189, 0.9489761652491318], [30190, 0.949045442438076], [30198, 0.9491294758420823], [30202, 0.9495943866276], [30203, 0.949418431512859], [30208, 0.9493215843938927], [30212, 0.9495048930253985], [30213, 0.9489753656334876], [30215, 0.9495952807950556], [30218, 0.949414440768517], [30225, 0.9493915986991329], [30227, 0.9490300797389857], [30233, 0.9493559968260314], [30235, 0.9488183382215799], [30238, 0.9495737411806277], [30244, 0.9493646121763273], [30248, 0.9492041395511921], [30254, 0.9492049144177783], [30259, 0.9494260864790702], [30260, 0.9491470813465589], [30501, 0.949187090783212], [30502, 0.9496374128589998], [30506, 0.9496262668652302], [30507, 0.9490453182537923], [30510, 0.94913413933213], [30515, 0.9489308519594464], [30519, 0.9494192327264727], [30520, 0.9494455737934114], [30524, 0.9485693108164488], [30525, 0.9489989555941335], [30529, 0.9492190644185173], [30533, 0.9487845240147946], [30538, 0.9491490176202986], [30542, 0.9491515078145121], [30543, 0.9492266670641089], [30544, 0.9489509636146871], [30545, 0.9491341504012633], [30550, 0.9489927382479721], [30552, 0.9497254484886748], [30556, 0.9495763958851585], [30561, 0.9491985540844412], [30564, 0.949293976983775], [30565, 0.9494175965031091], [30577, 0.9492179693023344], [30581, 0.9490337721254899], [30586, 0.9491665923342885], [30593, 0.9490297588213223], [30615, 0.948986209883768], [30621, 0.948671782615986], [30622, 0.9493209105893496], [30629, 0.949318507428452], [30635, 0.9489079676669392], [30639, 0.9493131212444292], [30640, 0.9491273129393697], [30643, 0.9492794965931994], [30646, 0.9488298943931032], [30647, 0.9490903858203578], [30650, 0.9487828973102849], [30657, 0.9492614270142304], [30665, 0.9496083720408919], [30670, 0.9489170841937721], [30675, 0.9485780105755182], [30679, 0.9490747164572861], [30694, 0.9488559609147807], [30704, 0.9490533921190544], [30708, 0.9489607226989647], [30718, 0.9495057554961038], [30723, 0.9488804678866466], [30729, 0.9493101247438916], [30730, 0.9496408210912837], [30734, 0.949256510310315], [30739, 0.9498341933984116], [30744, 0.9494082068193799], [30748, 0.9495643079186247], [30750, 0.949580613803401], [30754, 0.9493341175562159], [30761, 0.9489234871262433], [30762, 0.9492634668136427], [30777, 0.9495383858758734], [30782, 0.9490601901152839], [30785, 0.9494429008275979], [30787, 0.9494631998836041], [30794, 0.9488565582027845], [30804, 0.9490021436544785], [30812, 0.9489738436877041], [30817, 0.9492439407219129], [30821, 0.9492442169498907], [30838, 0.9492877924634299], [30849, 0.9493095507678998], [30861, 0.9492751747624577], [30868, 0.9494224389391029], [30872, 0.9493634753815796], [30890, 0.9492021918879539], [30904, 0.9495314570129172], [30907, 0.9493401353775637], [30908, 0.9496139598053337], [30917, 0.9496032059649376], [30928, 0.9488143421977788], [30931, 0.9495162365356116], [30938, 0.9495663428060128], [30945, 0.9490342788839696], [30949, 0.9494592414686698], [30955, 0.9488692573385492], [30957, 0.9495443968666818], [30967, 0.949558903620055], [30974, 0.9490914872236322], [30978, 0.9494430750556927], [30987, 0.9496693538596728], [30988, 0.9493168754447111], [30994, 0.9492434574203014], [30997, 0.9487433473368617], [31009, 0.9494762028856538], [31019, 0.948675588364969], [31031, 0.9489503481003031], [31039, 0.9492640525470329], [31040, 0.9494087542388009], [31041, 0.9496533392846398], [32218, 0.9496420637803128], [32220, 0.94976747135745], [32224, 0.9490156109654808], [32241, 0.9492040843765606], [32249, 0.9494403666063548], [32252, 0.9494872933025053], [32256, 0.94933769147982], [32259, 0.9497981868551141], [33213, 0.9489432514029298], [33259, 0.9491567624883966], [33296, 0.9491211493370174], [33302, 0.9493378521763116], [33309, 0.9490687450809406], [33310, 0.9489523031623103], [33311, 0.9493566023535911], [33315, 0.9497811940481811], [33323, 0.9494057637629196], [33332, 0.9489629314508572], [33333, 0.9493309059220171], [33337, 0.9493332316873935], [33338, 0.9494635231231291], [33341, 0.9488122588881185], [33346, 0.9493692836065154], [33351, 0.9492452406365007], [33358, 0.949556044651534], [33359, 0.9486806378724809], [33361, 0.9495094774931312], [33370, 0.949442740694171], [33373, 0.9497424957760818], [33380, 0.9495566818251576], [33386, 0.9490624069692312], [33393, 0.9490321749799937], [33400, 0.9496902525221382], [33414, 0.9489820710648562], [33424, 0.9490149598327923], [33428, 0.9495331549201204], [33437, 0.94958307239815], [33444, 0.9491993276136375], [33453, 0.9488004726948344], [33516, 0.94901904399825], [33517, 0.9496021601241941], [33518, 0.949262421925893], [33520, 0.94949153064751], [33524, 0.9495735642905176], [33533, 0.9493545125557793], [33536, 0.9494251201375223], [33537, 0.9491480771254651], [33543, 0.9493026112545744], [33546, 0.9490199787562744], [33648, 0.9491667874493087], [33704, 0.9489930629060414], [33707, 0.9494294119351844], [33708, 0.9495334711830784], [33712, 0.9492108984824643], [33715, 0.9492089683291463], [33722, 0.9488337058644081], [33733, 0.9483482990669251], [33734, 0.9490490915511592], [33756, 0.9495141080690113], [33766, 0.9493551415629777], [33802, 0.9493817272666784], [33808, 0.9491188519454208], [33813, 0.949232870528335], [33818, 0.9491819424548059], [33820, 0.9492773684118239], [33826, 0.949745648152415], [33833, 0.9489209318171092], [34031, 0.9489450411885428], [34034, 0.9491539571251792], [34046, 0.9494421911277732], [34049, 0.9497616409636123], [34052, 0.949050208744822], [34058, 0.9491827533351889], [34065, 0.9487628170719324], [34068, 0.949215088494552], [34075, 0.9494009065385718], [34079, 0.949806737550645], [34113, 0.9494217270387941], [34115, 0.949364770017755], [34120, 0.9491035137025112], [34126, 0.9488856692428476], [34139, 0.9491868040078965], [34140, 0.949671922512336], [34141, 0.9493913624258294], [34155, 0.94906283229951], [34158, 0.9494319635097784], [34160, 0.9494040794416674], [34162, 0.9497864970624093], [34164, 0.9494832721536]] \ No newline at end of file diff --git a/graphs/summary/linear_model.RidgeBenchmark.track_train_score.json b/graphs/summary/linear_model.RidgeBenchmark.track_train_score.json index baac3cf0ac..d1d3261c6f 100644 --- a/graphs/summary/linear_model.RidgeBenchmark.track_train_score.json +++ b/graphs/summary/linear_model.RidgeBenchmark.track_train_score.json @@ -1 +1 @@ -[[28497, 0.9543432680487894], [29215, 0.9541463532312772], [29225, 0.9542516320049069], [29227, 0.9540845912545358], [29228, 0.9542502657057432], [29229, 0.9541702541973347], [29235, 0.9541268276694588], [29240, 0.9542716755207268], [29245, 0.9542190095635779], [29246, 0.9543572447014691], [29258, 0.9543088924992226], [29262, 0.9542351387488005], [29279, 0.9544122662527542], [29286, 0.9542996088231349], [29293, 0.9541692636104436], [29294, 0.9543519860181559], [29295, 0.954175341206208], [29296, 0.9542959708349356], [29313, 0.9543133069715899], [29318, 0.9543089769145192], [29319, 0.954221961630101], [29322, 0.954220941102113], [29325, 0.9543049540811185], [29327, 0.9543261611707586], [29328, 0.9541824827801612], [29340, 0.9542172919620749], [29344, 0.9541511256339268], [29349, 0.9542523423602742], [29364, 0.9542371213257216], [29371, 0.9542468687489235], [29376, 0.9541923990098291], [29381, 0.954171917712017], [29383, 0.9542419635410812], [29387, 0.9542700219912785], [29401, 0.9543138097719641], [29404, 0.9542728411627475], [29409, 0.9542816072931835], [29414, 0.9543635386438314], [29415, 0.9541990728549339], [29420, 0.9542080746465762], [29421, 0.9542539832282217], [29425, 0.9541894953792706], [29429, 0.95425514576832], [29435, 0.9541096089808611], [29443, 0.9543600768185059], [29446, 0.9542879230185439], [29453, 0.954115477157314], [29454, 0.95431639175589], [29455, 0.9541086956509864], [29457, 0.9544271478030424], [29458, 0.9543462494746755], [29469, 0.9542600676627133], [29541, 0.954247941248279], [29548, 0.9543552452866166], [29550, 0.9542880090369483], [29551, 0.9541288194405717], [29572, 0.9540747766394501], [29591, 0.9542035773765807], [29598, 0.9542087977657613], [29609, 0.954247785514231], [29611, 0.9541771496300157], [29621, 0.9542320922929753], [29638, 0.954283143219789], [29644, 0.9542190892237306], [29648, 0.9543157873710569], [29652, 0.9542114338023236], [29656, 0.9542117953126125], [29657, 0.954311344737566], [29662, 0.9541295103941562], [29665, 0.9542319577505548], [29667, 0.9542428664207584], [29735, 0.9544112308827514], [29742, 0.9543257730760358], [29750, 0.9541942059913426], [29753, 0.9543110663660694], [29757, 0.9542128731785264], [29761, 0.9542779323478262], [29765, 0.9542970957260699], [29766, 0.9542723240847406], [29768, 0.9542398364512207], [29776, 0.9541801922580763], [29783, 0.9542350328375958], [29788, 0.9541678940965299], [29789, 0.9542062172336631], [29790, 0.9542314727409492], [29795, 0.954318597702606], [29798, 0.9543228934542825], [29805, 0.9542605351967804], [29806, 0.954216274978042], [29807, 0.9542440130027038], [29808, 0.9543429482628497], [29813, 0.9541051600310886], [29815, 0.9542500379259007], [29828, 0.9542179876345762], [29839, 0.9543278098130263], [29844, 0.9543395809540092], [29858, 0.9543341160021107], [29865, 0.9542244918978748], [29999, 0.9543624169666719], [30002, 0.9542382958930006], [30010, 0.9540872948143563], [30013, 0.9541904130817441], [30023, 0.9541933419196433], [30028, 0.9541894428916907], [30035, 0.9542978773398065], [30046, 0.9542288744714839], [30053, 0.9542477394237577], [30066, 0.9541912018585588], [30068, 0.9543167999035768], [30070, 0.9541172758466435], [30074, 0.9542735136672764], [30076, 0.9542722785963471], [30077, 0.9543036739323796], [30078, 0.9540728710970127], [30085, 0.9541952830920369], [30086, 0.954120869700687], [30096, 0.9542810213438795], [30104, 0.9542305308756096], [30106, 0.9542922688160985], [30112, 0.9544214289904426], [30116, 0.9542147385099596], [30118, 0.9542867613965598], [30123, 0.9542572088138958], [30128, 0.9543333081642991], [30135, 0.9542202341676744], [30145, 0.9542894593505864], [30155, 0.954343875482806], [30156, 0.9543181900343671], [30157, 0.9542248204717516], [30165, 0.9541811658858], [30174, 0.954162134040069], [30179, 0.9542328310292896], [30185, 0.9542331413088843], [30189, 0.9543242425480286], [30190, 0.9541854130792704], [30198, 0.9540779465923102], [30202, 0.9540731568732127], [30203, 0.9542900906344652], [30208, 0.9542006452624865], [30212, 0.9542778622041448], [30213, 0.9542219398773819], [30215, 0.9542699906704233], [30218, 0.9542474988158133], [30225, 0.9542457131679927], [30227, 0.9542684865922243], [30233, 0.9541717554664305], [30235, 0.9541889500384086], [30238, 0.9542755186913596], [30244, 0.9542150901265187], [30248, 0.9542772575625916], [30254, 0.9543680064748525], [30259, 0.9543346371224442], [30260, 0.9542772019043653], [30501, 0.9543133270177007], [30502, 0.9543894482614949], [30506, 0.954273859563085], [30507, 0.9542197520950519], [30510, 0.9542437505815516], [30515, 0.9541322507693689], [30519, 0.9541572386363532], [30520, 0.9543239609180306], [30524, 0.95416680246553], [30525, 0.9543549316091399], [30529, 0.9540389728775284], [30533, 0.9543410587203547], [30538, 0.9543200339454826], [30542, 0.9542558139097018], [30543, 0.9542760575365694], [30544, 0.9542462565280585], [30545, 0.9541111895418347], [30550, 0.9541351973206342], [30552, 0.9541960132964854], [30556, 0.9542844912265288], [30561, 0.9542223548494965], [30564, 0.9542616543386367], [30565, 0.9543083842277569], [30577, 0.9541549650313584], [30581, 0.954240830317093], [30586, 0.9542815439621234], [30593, 0.9543307705238855], [30615, 0.954198663105092], [30621, 0.9541116225594939], [30622, 0.9542694542969083], [30629, 0.9541924057377488], [30635, 0.9540631325666962], [30639, 0.9542219647890609], [30640, 0.9542796584170532], [30643, 0.9541270778613512], [30646, 0.9541376569176714], [30647, 0.9543123187499335], [30650, 0.9542731450979683], [30657, 0.9541298513160053], [30665, 0.954305578765182], [30670, 0.9542600953607369], [30675, 0.95437102928934], [30679, 0.9541967006009738], [30694, 0.9542172979352276], [30704, 0.9542094455109001], [30708, 0.954264037993962], [30718, 0.9542866306112902], [30723, 0.9542677749560224], [30729, 0.9542188501156419], [30730, 0.9542908119377829], [30734, 0.9541755854008158], [30739, 0.9541277547647738], [30744, 0.9541725994582001], [30748, 0.9541998005225685], [30750, 0.9542947533492532], [30754, 0.9541957352960655], [30761, 0.9542980413412943], [30762, 0.9540764799012049], [30777, 0.9541175134380535], [30782, 0.9542026500399665], [30785, 0.9542843333826571], [30787, 0.9542441339002629], [30794, 0.9542695701214207], [30804, 0.954204226285311], [30812, 0.9542669227840851], [30817, 0.9542253909715611], [30821, 0.9542271257362009], [30838, 0.9542583452867531], [30849, 0.954199229136017], [30861, 0.9543354946014961], [30868, 0.9542656286865683], [30872, 0.9543121913977782], [30890, 0.9542353271984415], [30904, 0.9544421797058346], [30907, 0.9541437078355525], [30908, 0.9542588397980608], [30917, 0.9543151845969233], [30928, 0.9541588710135177], [30931, 0.9541886038534289], [30938, 0.9543765458108788], [30945, 0.9543309169219342], [30949, 0.9544587106914596], [30955, 0.9543794063358445], [30957, 0.9543085785588705], [30967, 0.9541734383900232], [30974, 0.9542584208635505], [30978, 0.9542595367052548], [30987, 0.9543056665808324], [30988, 0.9542583429978106], [30994, 0.9541748927352813], [30997, 0.9541387215674005], [31009, 0.9543129566745889], [31019, 0.9542728179784762], [31031, 0.9542128571657535], [31039, 0.954333299405418], [31040, 0.9542741766100649], [31041, 0.9542063519564034], [32218, 0.9543705227902535], [32220, 0.9542986129592897], [32224, 0.9543228676379453], [32241, 0.9542600084485727], [32249, 0.9542054092407722], [32252, 0.9542319587319554], [32256, 0.954215090927176], [32259, 0.9543846280783111], [33213, 0.9541691267094689], [33259, 0.9542013047994529], [33296, 0.9542400039058427], [33302, 0.9542075835392949], [33309, 0.9542053377905337], [33310, 0.9543335574841384], [33311, 0.9542802796819833], [33315, 0.9541904572859667], [33323, 0.9541465278647511], [33332, 0.9541549315311263], [33333, 0.9543628982508834], [33337, 0.9542283986407459], [33338, 0.9543781738780598], [33341, 0.9541373517308888], [33346, 0.9540494080118588], [33351, 0.9541182586122814], [33358, 0.9544340027120358], [33359, 0.9542241436071507], [33361, 0.9544691056181591], [33370, 0.9542190696801451], [33373, 0.954212859160604], [33380, 0.954228793047812], [33386, 0.9541446509294421], [33393, 0.9542835637333212], [33400, 0.9543054728354964], [33414, 0.954244683761829], [33424, 0.954110660364287], [33428, 0.9542190379362213], [33437, 0.9543395618031273], [33444, 0.9541925493590454], [33453, 0.9543861876509054], [33516, 0.9542993241729021], [33517, 0.954279131121773], [33518, 0.9540195444273649], [33520, 0.9543986931236128], [33524, 0.9542389162467344], [33533, 0.9541786679642997], [33536, 0.9542352090414772], [33537, 0.954159276040902], [33543, 0.9543130357466441], [33546, 0.9542061650857183], [33648, 0.9542327584871708], [33704, 0.954260858465295], [33707, 0.9542521898381022], [33708, 0.954139346933933], [33712, 0.954343000099586], [33715, 0.9542030013166519], [33722, 0.9542464200177356], [33733, 0.9543508696841758], [33734, 0.9542715520252563], [33756, 0.954289142384169], [33766, 0.9542483869683638], [33802, 0.9541502939442695], [33808, 0.9542872288042322], [33813, 0.9542947545944443], [33818, 0.9541905989619955], [33820, 0.9543902199090697], [33826, 0.9543624927435148], [33833, 0.9542307371208056], [34031, 0.9541909716683081], [34034, 0.954132189280399], [34046, 0.9543262527797505], [34049, 0.9542770850717891], [34052, 0.954220468246894], [34058, 0.9542214547448459], [34065, 0.9541799570706495], [34068, 0.9542445567109519], [34075, 0.9542802628820654], [34079, 0.9542081049078075], [34113, 0.9541842144264373], [34115, 0.9542292954285166], [34120, 0.9542661372089678], [34126, 0.9543089868215036], [34139, 0.9543984519899187], [34140, 0.9543188644255436], [34141, 0.9541694716651534], [34155, 0.9542031251246174], [34158, 0.9541942768451483], [34160, 0.954215843225613], [34162, 0.9542488396475588]] \ No newline at end of file +[[28497, 0.9543432680487894], [29215, 0.9541463532312772], [29225, 0.9542516320049069], [29227, 0.9540845912545358], [29228, 0.9542502657057432], [29229, 0.9541702541973347], [29235, 0.9541268276694588], [29240, 0.9542716755207268], [29245, 0.9542190095635779], [29246, 0.9543572447014691], [29258, 0.9543088924992226], [29262, 0.9542351387488005], [29279, 0.9544122662527542], [29286, 0.9542996088231349], [29293, 0.9541692636104436], [29294, 0.9543519860181559], [29295, 0.954175341206208], [29296, 0.9542959708349356], [29313, 0.9543133069715899], [29318, 0.9543089769145192], [29319, 0.954221961630101], [29322, 0.954220941102113], [29325, 0.9543049540811185], [29327, 0.9543261611707586], [29328, 0.9541824827801612], [29340, 0.9542172919620749], [29344, 0.9541511256339268], [29349, 0.9542523423602742], [29364, 0.9542371213257216], [29371, 0.9542468687489235], [29376, 0.9541923990098291], [29381, 0.954171917712017], [29383, 0.9542419635410812], [29387, 0.9542700219912785], [29401, 0.9543138097719641], [29404, 0.9542728411627475], [29409, 0.9542816072931835], [29414, 0.9543635386438314], [29415, 0.9541990728549339], [29420, 0.9542080746465762], [29421, 0.9542539832282217], [29425, 0.9541894953792706], [29429, 0.95425514576832], [29435, 0.9541096089808611], [29443, 0.9543600768185059], [29446, 0.9542879230185439], [29453, 0.954115477157314], [29454, 0.95431639175589], [29455, 0.9541086956509864], [29457, 0.9544271478030424], [29458, 0.9543462494746755], [29469, 0.9542600676627133], [29541, 0.954247941248279], [29548, 0.9543552452866166], [29550, 0.9542880090369483], [29551, 0.9541288194405717], [29572, 0.9540747766394501], [29591, 0.9542035773765807], [29598, 0.9542087977657613], [29609, 0.954247785514231], [29611, 0.9541771496300157], [29621, 0.9542320922929753], [29638, 0.954283143219789], [29644, 0.9542190892237306], [29648, 0.9543157873710569], [29652, 0.9542114338023236], [29656, 0.9542117953126125], [29657, 0.954311344737566], [29662, 0.9541295103941562], [29665, 0.9542319577505548], [29667, 0.9542428664207584], [29735, 0.9544112308827514], [29742, 0.9543257730760358], [29750, 0.9541942059913426], [29753, 0.9543110663660694], [29757, 0.9542128731785264], [29761, 0.9542779323478262], [29765, 0.9542970957260699], [29766, 0.9542723240847406], [29768, 0.9542398364512207], [29776, 0.9541801922580763], [29783, 0.9542350328375958], [29788, 0.9541678940965299], [29789, 0.9542062172336631], [29790, 0.9542314727409492], [29795, 0.954318597702606], [29798, 0.9543228934542825], [29805, 0.9542605351967804], [29806, 0.954216274978042], [29807, 0.9542440130027038], [29808, 0.9543429482628497], [29813, 0.9541051600310886], [29815, 0.9542500379259007], [29828, 0.9542179876345762], [29839, 0.9543278098130263], [29844, 0.9543395809540092], [29858, 0.9543341160021107], [29865, 0.9542244918978748], [29999, 0.9543624169666719], [30002, 0.9542382958930006], [30010, 0.9540872948143563], [30013, 0.9541904130817441], [30023, 0.9541933419196433], [30028, 0.9541894428916907], [30035, 0.9542978773398065], [30046, 0.9542288744714839], [30053, 0.9542477394237577], [30066, 0.9541912018585588], [30068, 0.9543167999035768], [30070, 0.9541172758466435], [30074, 0.9542735136672764], [30076, 0.9542722785963471], [30077, 0.9543036739323796], [30078, 0.9540728710970127], [30085, 0.9541952830920369], [30086, 0.954120869700687], [30096, 0.9542810213438795], [30104, 0.9542305308756096], [30106, 0.9542922688160985], [30112, 0.9544214289904426], [30116, 0.9542147385099596], [30118, 0.9542867613965598], [30123, 0.9542572088138958], [30128, 0.9543333081642991], [30135, 0.9542202341676744], [30145, 0.9542894593505864], [30155, 0.954343875482806], [30156, 0.9543181900343671], [30157, 0.9542248204717516], [30165, 0.9541811658858], [30174, 0.954162134040069], [30179, 0.9542328310292896], [30185, 0.9542331413088843], [30189, 0.9543242425480286], [30190, 0.9541854130792704], [30198, 0.9540779465923102], [30202, 0.9540731568732127], [30203, 0.9542900906344652], [30208, 0.9542006452624865], [30212, 0.9542778622041448], [30213, 0.9542219398773819], [30215, 0.9542699906704233], [30218, 0.9542474988158133], [30225, 0.9542457131679927], [30227, 0.9542684865922243], [30233, 0.9541717554664305], [30235, 0.9541889500384086], [30238, 0.9542755186913596], [30244, 0.9542150901265187], [30248, 0.9542772575625916], [30254, 0.9543680064748525], [30259, 0.9543346371224442], [30260, 0.9542772019043653], [30501, 0.9543133270177007], [30502, 0.9543894482614949], [30506, 0.954273859563085], [30507, 0.9542197520950519], [30510, 0.9542437505815516], [30515, 0.9541322507693689], [30519, 0.9541572386363532], [30520, 0.9543239609180306], [30524, 0.95416680246553], [30525, 0.9543549316091399], [30529, 0.9540389728775284], [30533, 0.9543410587203547], [30538, 0.9543200339454826], [30542, 0.9542558139097018], [30543, 0.9542760575365694], [30544, 0.9542462565280585], [30545, 0.9541111895418347], [30550, 0.9541351973206342], [30552, 0.9541960132964854], [30556, 0.9542844912265288], [30561, 0.9542223548494965], [30564, 0.9542616543386367], [30565, 0.9543083842277569], [30577, 0.9541549650313584], [30581, 0.954240830317093], [30586, 0.9542815439621234], [30593, 0.9543307705238855], [30615, 0.954198663105092], [30621, 0.9541116225594939], [30622, 0.9542694542969083], [30629, 0.9541924057377488], [30635, 0.9540631325666962], [30639, 0.9542219647890609], [30640, 0.9542796584170532], [30643, 0.9541270778613512], [30646, 0.9541376569176714], [30647, 0.9543123187499335], [30650, 0.9542731450979683], [30657, 0.9541298513160053], [30665, 0.954305578765182], [30670, 0.9542600953607369], [30675, 0.95437102928934], [30679, 0.9541967006009738], [30694, 0.9542172979352276], [30704, 0.9542094455109001], [30708, 0.954264037993962], [30718, 0.9542866306112902], [30723, 0.9542677749560224], [30729, 0.9542188501156419], [30730, 0.9542908119377829], [30734, 0.9541755854008158], [30739, 0.9541277547647738], [30744, 0.9541725994582001], [30748, 0.9541998005225685], [30750, 0.9542947533492532], [30754, 0.9541957352960655], [30761, 0.9542980413412943], [30762, 0.9540764799012049], [30777, 0.9541175134380535], [30782, 0.9542026500399665], [30785, 0.9542843333826571], [30787, 0.9542441339002629], [30794, 0.9542695701214207], [30804, 0.954204226285311], [30812, 0.9542669227840851], [30817, 0.9542253909715611], [30821, 0.9542271257362009], [30838, 0.9542583452867531], [30849, 0.954199229136017], [30861, 0.9543354946014961], [30868, 0.9542656286865683], [30872, 0.9543121913977782], [30890, 0.9542353271984415], [30904, 0.9544421797058346], [30907, 0.9541437078355525], [30908, 0.9542588397980608], [30917, 0.9543151845969233], [30928, 0.9541588710135177], [30931, 0.9541886038534289], [30938, 0.9543765458108788], [30945, 0.9543309169219342], [30949, 0.9544587106914596], [30955, 0.9543794063358445], [30957, 0.9543085785588705], [30967, 0.9541734383900232], [30974, 0.9542584208635505], [30978, 0.9542595367052548], [30987, 0.9543056665808324], [30988, 0.9542583429978106], [30994, 0.9541748927352813], [30997, 0.9541387215674005], [31009, 0.9543129566745889], [31019, 0.9542728179784762], [31031, 0.9542128571657535], [31039, 0.954333299405418], [31040, 0.9542741766100649], [31041, 0.9542063519564034], [32218, 0.9543705227902535], [32220, 0.9542986129592897], [32224, 0.9543228676379453], [32241, 0.9542600084485727], [32249, 0.9542054092407722], [32252, 0.9542319587319554], [32256, 0.954215090927176], [32259, 0.9543846280783111], [33213, 0.9541691267094689], [33259, 0.9542013047994529], [33296, 0.9542400039058427], [33302, 0.9542075835392949], [33309, 0.9542053377905337], [33310, 0.9543335574841384], [33311, 0.9542802796819833], [33315, 0.9541904572859667], [33323, 0.9541465278647511], [33332, 0.9541549315311263], [33333, 0.9543628982508834], [33337, 0.9542283986407459], [33338, 0.9543781738780598], [33341, 0.9541373517308888], [33346, 0.9540494080118588], [33351, 0.9541182586122814], [33358, 0.9544340027120358], [33359, 0.9542241436071507], [33361, 0.9544691056181591], [33370, 0.9542190696801451], [33373, 0.954212859160604], [33380, 0.954228793047812], [33386, 0.9541446509294421], [33393, 0.9542835637333212], [33400, 0.9543054728354964], [33414, 0.954244683761829], [33424, 0.954110660364287], [33428, 0.9542190379362213], [33437, 0.9543395618031273], [33444, 0.9541925493590454], [33453, 0.9543861876509054], [33516, 0.9542993241729021], [33517, 0.954279131121773], [33518, 0.9540195444273649], [33520, 0.9543986931236128], [33524, 0.9542389162467344], [33533, 0.9541786679642997], [33536, 0.9542352090414772], [33537, 0.954159276040902], [33543, 0.9543130357466441], [33546, 0.9542061650857183], [33648, 0.9542327584871708], [33704, 0.954260858465295], [33707, 0.9542521898381022], [33708, 0.954139346933933], [33712, 0.954343000099586], [33715, 0.9542030013166519], [33722, 0.9542464200177356], [33733, 0.9543508696841758], [33734, 0.9542715520252563], [33756, 0.954289142384169], [33766, 0.9542483869683638], [33802, 0.9541502939442695], [33808, 0.9542872288042322], [33813, 0.9542947545944443], [33818, 0.9541905989619955], [33820, 0.9543902199090697], [33826, 0.9543624927435148], [33833, 0.9542307371208056], [34031, 0.9541909716683081], [34034, 0.954132189280399], [34046, 0.9543262527797505], [34049, 0.9542770850717891], [34052, 0.954220468246894], [34058, 0.9542214547448459], [34065, 0.9541799570706495], [34068, 0.9542445567109519], [34075, 0.9542802628820654], [34079, 0.9542081049078075], [34113, 0.9541842144264373], [34115, 0.9542292954285166], [34120, 0.9542661372089678], [34126, 0.9543089868215036], [34139, 0.9543984519899187], [34140, 0.9543188644255436], [34141, 0.9541694716651534], [34155, 0.9542031251246174], [34158, 0.9541942768451483], [34160, 0.954215843225613], [34162, 0.9542488396475588], [34164, 0.9541892561249788]] \ No newline at end of file diff --git a/graphs/summary/linear_model.SGDRegressorBenchmark.peakmem_fit.json b/graphs/summary/linear_model.SGDRegressorBenchmark.peakmem_fit.json index 69fe46f665..cbde1677d4 100644 --- a/graphs/summary/linear_model.SGDRegressorBenchmark.peakmem_fit.json +++ b/graphs/summary/linear_model.SGDRegressorBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 168148430.06122607], [29225, 163930779.89369714], [29239, 163636018.3847816], [29253, 166409911.28923395], [29267, 166483718.9297629], [29281, 164129996.76728988], [29295, 166434465.2343134], [29309, 166292344.94810736], [29323, 165491929.50146627], [29337, 165514168.86481696], [29351, 164344261.52740493], [29365, 164392328.32588246], [29379, 164749232.0055446], [29393, 163917001.2661132], [29407, 165250048.4432234], [29421, 163888076.346043], [29435, 164621403.5042052], [29449, 165319552.62671813], [29463, 164787259.72934777], [29477, 164844009.13770142], [29547, 166554914.17746517], [29561, 166232681.74404335], [29575, 164089861.47005805], [29603, 166995479.186015], [29617, 165739493.96613485], [29631, 166430425.2303795], [29645, 166446831.60632744], [29659, 166854408.84663332], [29673, 166721182.06087533], [29743, 167121390.76261508], [29757, 166936280.23305112], [29771, 166361654.80195528], [29785, 166533048.84891146], [29799, 166443664.7489579], [29813, 166496565.49491656], [29827, 166421290.59066778], [29841, 166263304.73421657], [29855, 166305360.57872224], [29869, 166099546.20690376], [30009, 166399445.2478425], [30023, 166953766.59392577], [30037, 166268986.26051712], [30051, 166592056.09379002], [30065, 166012427.84217966], [30079, 166816549.43596444], [30093, 167454825.6956876], [30107, 166183968.34357294], [30121, 166799249.2040367], [30135, 167296276.08295384], [30149, 167055017.22782105], [30163, 167025834.00835714], [30177, 166693753.89442775], [30191, 167973489.66447127], [30205, 167375022.05845138], [30219, 166511198.07095996], [30233, 167588291.4972765], [30247, 167890282.27731198], [30261, 167846027.20239353], [30513, 167322531.5453007], [30527, 167729610.89827472], [30541, 168060063.56182495], [30555, 167416223.5960255], [30569, 167372310.28042936], [30583, 166466032.02386385], [30597, 166957923.14109945], [30625, 167623472.0724716], [30639, 165958115.68033364], [30653, 167008332.1204619], [30667, 168027136.8971982], [30681, 167023476.74948344], [30695, 165726438.49822706], [30709, 167839318.5995614], [30723, 169095859.49561876], [30737, 166432796.976339], [30751, 166945834.46600533], [30765, 168052742.53496024], [30779, 166113883.31430325], [30793, 166223230.21985185], [30807, 168530585.88818628], [30821, 167934760.9143412], [30835, 168424442.19444653], [30849, 166442465.18625417], [30863, 166352628.18480933], [30877, 168481575.48723778], [30891, 168850961.56750783], [30905, 166070267.44125584], [30919, 167114976.17613888], [30933, 167643159.8162789], [30947, 167162588.74807864], [30961, 167391027.23267373], [30975, 167118090.51067325], [30989, 166136429.58406782], [31003, 167053337.09033787], [31017, 167265950.72194642], [31031, 167708476.21329653], [31045, 167437504.9000269], [32095, 180488013.0970757], [32109, 181431419.67880446], [32123, 180757910.8031803], [32137, 181756513.98828888], [32151, 180632595.6292113], [32165, 181616711.771358], [32179, 181603617.13526124], [32193, 181313865.65602565], [32207, 182923346.0132444], [32221, 185434490.38066038], [32235, 185983112.44006798], [32249, 185102282.02535117], [32263, 185031091.18058202], [32277, 184705865.72298107], [32305, 185716920.5645899], [32319, 188761450.89278126], [32333, 189232700.80289072], [32347, 189103231.2498505], [32361, 189453088.34641442], [32375, 189001938.4233057], [32389, 188874416.41719455], [32403, 188088853.22851247], [32417, 189326337.687883], [32431, 188760004.38328993], [32445, 188764853.7901105], [32585, 188974032.04808047], [32599, 188491615.1959699], [32613, 189099069.4110422], [32627, 188623814.7386438], [32641, 189432213.99227107], [32655, 189030082.08588073], [32851, 190066644.84480357], [32865, 190513790.50537726], [32879, 189786056.74446383], [32893, 133906524.67528915], [32907, 134354334.33224314], [32921, 133300381.33621386], [32991, 132172310.25220132], [33005, 134135549.34187838], [33019, 133210393.23603545], [33033, 133884398.7815144], [33047, 133130751.81786086], [33061, 134067813.29925033], [33075, 133709645.95111291], [33089, 149342375.812918], [33103, 164512215.02830246], [33117, 164150549.53032023], [33131, 163895779.6799182], [33145, 164448618.36631435], [33159, 163411740.52556512], [33187, 133919557.3628508], [33201, 133808803.97010492], [33215, 132343099.578536], [33229, 128080906.69596593], [33243, 128407788.54534623], [33271, 122471970.44290768], [33299, 123266528.1758427], [33313, 122363263.1085162], [33327, 123150675.44750193], [33341, 122764714.45395078], [33355, 123266831.99900441], [33369, 123223357.23656642], [33383, 124116336.16511346], [33397, 124602239.8576439], [33411, 124600160.44171244], [33425, 124701619.47707975], [33439, 125762483.4209657], [33453, 120737958.05206208], [33467, 120058364.94204842], [33523, 120358392.60132015], [33537, 120379000.87335695], [33551, 120184063.29887597], [33649, 118853287.64302047], [33705, 119082100.61553654], [33719, 119307381.77051014], [33733, 118558932.6182236], [33747, 118694490.64251578], [33761, 118712237.30620773], [33775, 118525733.23600091], [33803, 118832180.09253728], [33817, 118848408.40551993], [33831, 118669927.6939667], [33845, 118641914.46924649], [34041, 118934642.56692047], [34055, 118878746.48563898], [34069, 118474213.18773587], [34083, 118575818.31634916], [34125, 118438839.11875117], [34139, 118022920.36671142], [34153, 118540764.39146225], [34167, 118408974.81439734]] \ No newline at end of file +[[28511, 168148430.06122607], [29225, 163930779.89369714], [29239, 163636018.3847816], [29253, 166409911.28923395], [29267, 166483718.9297629], [29281, 164129996.76728988], [29295, 166434465.2343134], [29309, 166292344.94810736], [29323, 165491929.50146627], [29337, 165514168.86481696], [29351, 164344261.52740493], [29365, 164392328.32588246], [29379, 164749232.0055446], [29393, 163917001.2661132], [29407, 165250048.4432234], [29421, 163888076.346043], [29435, 164621403.5042052], [29449, 165319552.62671813], [29463, 164787259.72934777], [29477, 164844009.13770142], [29547, 166554914.17746517], [29561, 166232681.74404335], [29575, 164089861.47005805], [29603, 166995479.186015], [29617, 165739493.96613485], [29631, 166430425.2303795], [29645, 166446831.60632744], [29659, 166854408.84663332], [29673, 166721182.06087533], [29743, 167121390.76261508], [29757, 166936280.23305112], [29771, 166361654.80195528], [29785, 166533048.84891146], [29799, 166443664.7489579], [29813, 166496565.49491656], [29827, 166421290.59066778], [29841, 166263304.73421657], [29855, 166305360.57872224], [29869, 166099546.20690376], [30009, 166399445.2478425], [30023, 166953766.59392577], [30037, 166268986.26051712], [30051, 166592056.09379002], [30065, 166012427.84217966], [30079, 166816549.43596444], [30093, 167454825.6956876], [30107, 166183968.34357294], [30121, 166799249.2040367], [30135, 167296276.08295384], [30149, 167055017.22782105], [30163, 167025834.00835714], [30177, 166693753.89442775], [30191, 167973489.66447127], [30205, 167375022.05845138], [30219, 166511198.07095996], [30233, 167588291.4972765], [30247, 167890282.27731198], [30261, 167846027.20239353], [30513, 167322531.5453007], [30527, 167729610.89827472], [30541, 168060063.56182495], [30555, 167416223.5960255], [30569, 167372310.28042936], [30583, 166466032.02386385], [30597, 166957923.14109945], [30625, 167623472.0724716], [30639, 165958115.68033364], [30653, 167008332.1204619], [30667, 168027136.8971982], [30681, 167023476.74948344], [30695, 165726438.49822706], [30709, 167839318.5995614], [30723, 169095859.49561876], [30737, 166432796.976339], [30751, 166945834.46600533], [30765, 168052742.53496024], [30779, 166113883.31430325], [30793, 166223230.21985185], [30807, 168530585.88818628], [30821, 167934760.9143412], [30835, 168424442.19444653], [30849, 166442465.18625417], [30863, 166352628.18480933], [30877, 168481575.48723778], [30891, 168850961.56750783], [30905, 166070267.44125584], [30919, 167114976.17613888], [30933, 167643159.8162789], [30947, 167162588.74807864], [30961, 167391027.23267373], [30975, 167118090.51067325], [30989, 166136429.58406782], [31003, 167053337.09033787], [31017, 167265950.72194642], [31031, 167708476.21329653], [31045, 167437504.9000269], [32095, 180488013.0970757], [32109, 181431419.67880446], [32123, 180757910.8031803], [32137, 181756513.98828888], [32151, 180632595.6292113], [32165, 181616711.771358], [32179, 181603617.13526124], [32193, 181313865.65602565], [32207, 182923346.0132444], [32221, 185434490.38066038], [32235, 185983112.44006798], [32249, 185102282.02535117], [32263, 185031091.18058202], [32277, 184705865.72298107], [32305, 185716920.5645899], [32319, 188761450.89278126], [32333, 189232700.80289072], [32347, 189103231.2498505], [32361, 189453088.34641442], [32375, 189001938.4233057], [32389, 188874416.41719455], [32403, 188088853.22851247], [32417, 189326337.687883], [32431, 188760004.38328993], [32445, 188764853.7901105], [32585, 188974032.04808047], [32599, 188491615.1959699], [32613, 189099069.4110422], [32627, 188623814.7386438], [32641, 189432213.99227107], [32655, 189030082.08588073], [32851, 190066644.84480357], [32865, 190513790.50537726], [32879, 189786056.74446383], [32893, 133906524.67528915], [32907, 134354334.33224314], [32921, 133300381.33621386], [32991, 132172310.25220132], [33005, 134135549.34187838], [33019, 133210393.23603545], [33033, 133884398.7815144], [33047, 133130751.81786086], [33061, 134067813.29925033], [33075, 133709645.95111291], [33089, 149342375.812918], [33103, 164512215.02830246], [33117, 164150549.53032023], [33131, 163895779.6799182], [33145, 164448618.36631435], [33159, 163411740.52556512], [33187, 133919557.3628508], [33201, 133808803.97010492], [33215, 132343099.578536], [33229, 128080906.69596593], [33243, 128407788.54534623], [33271, 122471970.44290768], [33299, 123266528.1758427], [33313, 122363263.1085162], [33327, 123150675.44750193], [33341, 122764714.45395078], [33355, 123266831.99900441], [33369, 123223357.23656642], [33383, 124116336.16511346], [33397, 124602239.8576439], [33411, 124600160.44171244], [33425, 124701619.47707975], [33439, 125762483.4209657], [33453, 120737958.05206208], [33467, 120058364.94204842], [33523, 120358392.60132015], [33537, 120379000.87335695], [33551, 120184063.29887597], [33649, 118853287.64302047], [33705, 119082100.61553654], [33719, 119307381.77051014], [33733, 118558932.6182236], [33747, 118694490.64251578], [33761, 118712237.30620773], [33775, 118525733.23600091], [33803, 118832180.09253728], [33817, 118848408.40551993], [33831, 118669927.6939667], [33845, 118641914.46924649], [34041, 118934642.56692047], [34055, 118878746.48563898], [34069, 118474213.18773587], [34083, 118575818.31634916], [34125, 118438839.11875117], [34139, 118022920.36671142], [34153, 118540764.39146225], [34167, 118437977.20308247]] \ No newline at end of file diff --git a/graphs/summary/linear_model.SGDRegressorBenchmark.peakmem_predict.json b/graphs/summary/linear_model.SGDRegressorBenchmark.peakmem_predict.json index 33950bf582..2c8ec9fdeb 100644 --- a/graphs/summary/linear_model.SGDRegressorBenchmark.peakmem_predict.json +++ b/graphs/summary/linear_model.SGDRegressorBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28511, 160557069.78011855], [29225, 158136095.9173702], [29239, 157977380.829533], [29253, 157532142.26183194], [29267, 157590686.38072914], [29281, 157778909.06605878], [29295, 157619813.78434667], [29309, 157468111.73155057], [29323, 157481318.15496892], [29337, 157673121.2532827], [29351, 156880444.71973768], [29365, 156956351.4744049], [29379, 157059330.0630651], [29393, 157073487.9042204], [29407, 156926748.3295727], [29421, 156946953.56347752], [29435, 157384207.00093815], [29449, 158149671.25202182], [29463, 158097709.12368217], [29477, 158359792.068516], [29547, 158498959.1101277], [29561, 158477933.3127917], [29575, 157651046.1099724], [29603, 159050819.84904385], [29617, 159164183.65878445], [29631, 159389419.3656869], [29645, 159380760.52195275], [29659, 159227647.59440768], [29673, 159166989.4873997], [29743, 159135867.55974376], [29757, 159246382.9491256], [29771, 159209099.6187836], [29785, 159290350.45460337], [29799, 159286795.9167121], [29813, 159464625.99849737], [29827, 159373036.97840852], [29841, 159415121.85559556], [29855, 159510975.9582853], [29869, 159579794.22032705], [30009, 159325149.1276523], [30023, 159343955.43432194], [30037, 159366507.5481813], [30051, 159290090.49211797], [30065, 159474297.43008736], [30079, 159401502.08156952], [30093, 159346349.70750713], [30107, 159264938.89712664], [30121, 159575600.80771312], [30135, 159470668.12115395], [30149, 159689259.02541453], [30163, 159870612.0911289], [30177, 159986652.90921196], [30191, 160004687.54277357], [30205, 159952596.4321554], [30219, 159860170.60268086], [30233, 159686029.3250211], [30247, 160068222.7322427], [30261, 159840940.31075633], [30513, 160068993.79079217], [30527, 159872820.53719336], [30541, 159737480.5938963], [30555, 159730539.9301944], [30569, 159695779.62127042], [30583, 159920936.82712704], [30597, 159714249.22373757], [30625, 159901351.5642883], [30639, 159920638.26867795], [30653, 159768565.53619203], [30667, 159792763.40878826], [30681, 159816328.9078678], [30695, 159864159.38489538], [30709, 159804742.26454583], [30723, 159749078.95925885], [30737, 159829789.22721726], [30751, 159953365.00093353], [30765, 160283762.9011357], [30779, 159919872.33419615], [30793, 159897826.2495019], [30807, 159886138.62619048], [30821, 160038792.21045482], [30835, 160324494.56118926], [30849, 160097570.5375086], [30863, 160034459.5852334], [30877, 160212567.57520404], [30891, 160294049.96627754], [30905, 160125464.24160075], [30919, 159847151.81063667], [30933, 159926024.0724614], [30947, 159989363.63904193], [30961, 159898987.92600778], [30975, 160084565.11153293], [30989, 160163030.82898378], [31003, 160337380.49182922], [31017, 160298328.2057362], [31031, 159873051.1665683], [31045, 160054068.17730242], [32095, 173977440.6440706], [32109, 173539755.4089564], [32123, 173651243.69836843], [32137, 173637490.64810365], [32151, 173613309.93879965], [32165, 173591689.19737077], [32179, 173448106.15126902], [32193, 173777362.08752444], [32207, 175265127.80831352], [32221, 177564515.47546172], [32235, 177710022.36108434], [32249, 177801910.8494664], [32263, 177598520.38400072], [32277, 176548339.9836928], [32305, 178036847.05675092], [32319, 181119740.3867506], [32333, 181167857.5793417], [32347, 181170784.33687323], [32361, 181213491.7802196], [32375, 181375716.64734396], [32389, 180999339.57741767], [32403, 181029042.6696255], [32417, 181081841.3823421], [32431, 181236451.004843], [32445, 181314333.15724102], [32585, 181436886.44916198], [32599, 181455892.86661696], [32613, 181487386.26206383], [32627, 181529378.670879], [32641, 181401018.9104327], [32655, 181470358.95379165], [32851, 182515057.55310288], [32865, 182565471.70387605], [32879, 182586875.39671338], [32893, 131469319.50258216], [32907, 131492616.44096778], [32921, 131573971.3850376], [32991, 131582132.52950306], [33005, 131423271.88910359], [33019, 131028964.71104296], [33033, 131557658.70381442], [33047, 131640379.80069429], [33061, 131680444.30960706], [33075, 131642018.63581447], [33089, 147310005.39676332], [33103, 162902431.97082436], [33117, 163068927.93319947], [33131, 162607559.30173898], [33145, 163142105.7627287], [33159, 163180101.43728736], [33187, 131996574.57129288], [33201, 131708931.6432894], [33215, 130257387.55141969], [33229, 125970354.5227356], [33243, 126159367.89615688], [33271, 120748619.99225889], [33299, 120211402.3201066], [33313, 120790687.43013169], [33327, 121248107.04896691], [33341, 121320418.84239265], [33355, 121565458.41543925], [33369, 121563674.15177554], [33383, 122305555.65594618], [33397, 122538908.7935193], [33411, 122561652.00833352], [33425, 122571156.16212206], [33439, 123694029.78055993], [33453, 118586672.80688243], [33467, 118677936.58566844], [33523, 118770305.5115962], [33537, 118906214.05119486], [33551, 118182512.0228702], [33649, 117400415.15501545], [33705, 117121855.68817106], [33719, 117227482.74327742], [33733, 117387602.36721532], [33747, 117214503.52109587], [33761, 117381804.18329784], [33775, 117044509.78094788], [33803, 117340708.16355075], [33817, 116952958.00687557], [33831, 117067530.85660185], [33845, 116958800.06840344], [34041, 116741390.09199838], [34055, 116975310.21908192], [34069, 116943218.50732803], [34083, 116731093.59742197], [34125, 116828413.75039749], [34139, 116777252.22215278], [34153, 116841110.3453966], [34167, 116821222.89330876]] \ No newline at end of file +[[28511, 160557069.78011855], [29225, 158136095.9173702], [29239, 157977380.829533], [29253, 157532142.26183194], [29267, 157590686.38072914], [29281, 157778909.06605878], [29295, 157619813.78434667], [29309, 157468111.73155057], [29323, 157481318.15496892], [29337, 157673121.2532827], [29351, 156880444.71973768], [29365, 156956351.4744049], [29379, 157059330.0630651], [29393, 157073487.9042204], [29407, 156926748.3295727], [29421, 156946953.56347752], [29435, 157384207.00093815], [29449, 158149671.25202182], [29463, 158097709.12368217], [29477, 158359792.068516], [29547, 158498959.1101277], [29561, 158477933.3127917], [29575, 157651046.1099724], [29603, 159050819.84904385], [29617, 159164183.65878445], [29631, 159389419.3656869], [29645, 159380760.52195275], [29659, 159227647.59440768], [29673, 159166989.4873997], [29743, 159135867.55974376], [29757, 159246382.9491256], [29771, 159209099.6187836], [29785, 159290350.45460337], [29799, 159286795.9167121], [29813, 159464625.99849737], [29827, 159373036.97840852], [29841, 159415121.85559556], [29855, 159510975.9582853], [29869, 159579794.22032705], [30009, 159325149.1276523], [30023, 159343955.43432194], [30037, 159366507.5481813], [30051, 159290090.49211797], [30065, 159474297.43008736], [30079, 159401502.08156952], [30093, 159346349.70750713], [30107, 159264938.89712664], [30121, 159575600.80771312], [30135, 159470668.12115395], [30149, 159689259.02541453], [30163, 159870612.0911289], [30177, 159986652.90921196], [30191, 160004687.54277357], [30205, 159952596.4321554], [30219, 159860170.60268086], [30233, 159686029.3250211], [30247, 160068222.7322427], [30261, 159840940.31075633], [30513, 160068993.79079217], [30527, 159872820.53719336], [30541, 159737480.5938963], [30555, 159730539.9301944], [30569, 159695779.62127042], [30583, 159920936.82712704], [30597, 159714249.22373757], [30625, 159901351.5642883], [30639, 159920638.26867795], [30653, 159768565.53619203], [30667, 159792763.40878826], [30681, 159816328.9078678], [30695, 159864159.38489538], [30709, 159804742.26454583], [30723, 159749078.95925885], [30737, 159829789.22721726], [30751, 159953365.00093353], [30765, 160283762.9011357], [30779, 159919872.33419615], [30793, 159897826.2495019], [30807, 159886138.62619048], [30821, 160038792.21045482], [30835, 160324494.56118926], [30849, 160097570.5375086], [30863, 160034459.5852334], [30877, 160212567.57520404], [30891, 160294049.96627754], [30905, 160125464.24160075], [30919, 159847151.81063667], [30933, 159926024.0724614], [30947, 159989363.63904193], [30961, 159898987.92600778], [30975, 160084565.11153293], [30989, 160163030.82898378], [31003, 160337380.49182922], [31017, 160298328.2057362], [31031, 159873051.1665683], [31045, 160054068.17730242], [32095, 173977440.6440706], [32109, 173539755.4089564], [32123, 173651243.69836843], [32137, 173637490.64810365], [32151, 173613309.93879965], [32165, 173591689.19737077], [32179, 173448106.15126902], [32193, 173777362.08752444], [32207, 175265127.80831352], [32221, 177564515.47546172], [32235, 177710022.36108434], [32249, 177801910.8494664], [32263, 177598520.38400072], [32277, 176548339.9836928], [32305, 178036847.05675092], [32319, 181119740.3867506], [32333, 181167857.5793417], [32347, 181170784.33687323], [32361, 181213491.7802196], [32375, 181375716.64734396], [32389, 180999339.57741767], [32403, 181029042.6696255], [32417, 181081841.3823421], [32431, 181236451.004843], [32445, 181314333.15724102], [32585, 181436886.44916198], [32599, 181455892.86661696], [32613, 181487386.26206383], [32627, 181529378.670879], [32641, 181401018.9104327], [32655, 181470358.95379165], [32851, 182515057.55310288], [32865, 182565471.70387605], [32879, 182586875.39671338], [32893, 131469319.50258216], [32907, 131492616.44096778], [32921, 131573971.3850376], [32991, 131582132.52950306], [33005, 131423271.88910359], [33019, 131028964.71104296], [33033, 131557658.70381442], [33047, 131640379.80069429], [33061, 131680444.30960706], [33075, 131642018.63581447], [33089, 147310005.39676332], [33103, 162902431.97082436], [33117, 163068927.93319947], [33131, 162607559.30173898], [33145, 163142105.7627287], [33159, 163180101.43728736], [33187, 131996574.57129288], [33201, 131708931.6432894], [33215, 130257387.55141969], [33229, 125970354.5227356], [33243, 126159367.89615688], [33271, 120748619.99225889], [33299, 120211402.3201066], [33313, 120790687.43013169], [33327, 121248107.04896691], [33341, 121320418.84239265], [33355, 121565458.41543925], [33369, 121563674.15177554], [33383, 122305555.65594618], [33397, 122538908.7935193], [33411, 122561652.00833352], [33425, 122571156.16212206], [33439, 123694029.78055993], [33453, 118586672.80688243], [33467, 118677936.58566844], [33523, 118770305.5115962], [33537, 118906214.05119486], [33551, 118182512.0228702], [33649, 117400415.15501545], [33705, 117121855.68817106], [33719, 117227482.74327742], [33733, 117387602.36721532], [33747, 117214503.52109587], [33761, 117381804.18329784], [33775, 117044509.78094788], [33803, 117340708.16355075], [33817, 116952958.00687557], [33831, 117067530.85660185], [33845, 116958800.06840344], [34041, 116741390.09199838], [34055, 116975310.21908192], [34069, 116943218.50732803], [34083, 116731093.59742197], [34125, 116828413.75039749], [34139, 116777252.22215278], [34153, 116841110.3453966], [34167, 116765344.43759139]] \ No newline at end of file diff --git a/graphs/summary/linear_model.SGDRegressorBenchmark.time_fit.json b/graphs/summary/linear_model.SGDRegressorBenchmark.time_fit.json index 4bcefeffba..59a4fc87ec 100644 --- a/graphs/summary/linear_model.SGDRegressorBenchmark.time_fit.json +++ b/graphs/summary/linear_model.SGDRegressorBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 1.9011236347919747], [29225, 2.7334296494731034], [29239, 2.1697493230448504], [29253, 1.739732932849922], [29267, 1.8701373672186974], [29281, 1.6175047522501087], [29295, 1.7619086315354104], [29309, 1.6563193683577326], [29323, 1.8242837603656883], [29337, 1.8670174136320128], [29351, 1.8297409133232378], [29365, 1.4711940025743548], [29379, 1.8310410932183698], [29393, 1.8271161155696787], [29407, 1.9417784199879629], [29421, 1.7502103372349807], [29435, 1.8384366177878695], [29449, 3.2969196169050576], [29463, 3.533637422899536], [29477, 3.2817162620058657], [29547, 4.284354723476936], [29561, 3.0811071119648545], [29575, 2.547667427547992], [29603, 2.419864573871065], [29617, 2.015716274264474], [29631, 2.329604574821814], [29645, 2.4109011136380616], [29659, 2.2533937851265673], [29673, 2.5891586722406625], [29743, 2.249023623356117], [29757, 2.2249363099612105], [29771, 2.3879923267053758], [29785, 4.063631787363224], [29799, 2.5552980540400982], [29813, 2.1810712223746025], [29827, 2.636230565489152], [29841, 2.5107010212793552], [29855, 2.6358893286347578], [29869, 2.458057683531379], [30009, 2.5562472393649474], [30023, 2.394496942185479], [30037, 2.1812371739741896], [30051, 2.274159106969875], [30065, 2.2746040913819736], [30079, 2.4477212177030365], [30093, 2.497164875546209], [30107, 2.578904047887315], [30121, 2.2221113135193242], [30135, 2.5521511923384814], [30149, 2.4043105668904072], [30163, 2.3569077834669936], [30177, 2.7114348779630824], [30191, 2.541950242372311], [30205, 2.2908943070604337], [30219, 2.4322892278009087], [30233, 2.93377178366019], [30247, 2.4492350945483654], [30261, 2.3054536820252753], [30513, 2.2265523415955655], [30527, 2.329308984566629], [30541, 2.757596275062833], [30555, 2.5670435012067236], [30569, 2.320473807094447], [30583, 2.3924155991401865], [30597, 2.5457857685550267], [30625, 2.5258906989091687], [30639, 3.1676014721557655], [30653, 2.567893317728014], [30667, 2.3051151877943203], [30681, 2.4294074577505005], [30695, 2.2578121032185576], [30709, 2.3679975525812456], [30723, 2.380447366899099], [30737, 2.7499204070064165], [30751, 2.6325922471906837], [30765, 2.446578680096405], [30779, 2.8835982511217537], [30793, 2.5957554797424227], [30807, 2.533808447417003], [30821, 2.336056810454294], [30835, 2.24950782548076], [30849, 2.3003523107135924], [30863, 2.3884715860290604], [30877, 2.3557159595181316], [30891, 2.429812831345365], [30905, 2.016953137247895], [30919, 2.64851976516814], [30933, 2.3034697653638725], [30947, 2.498223095052262], [30961, 2.6225681909080554], [30975, 2.4319368513973494], [30989, 2.558715751285025], [31003, 2.375997711481226], [31017, 3.211183763324997], [31031, 2.5357832873310935], [31045, 2.2553676452978175], [32095, 2.105765401260793], [32109, 3.0066629240424207], [32123, 2.7207561611164426], [32137, 2.5945897828315876], [32151, 3.139031291872656], [32165, 2.6798378705052075], [32179, 2.5561445174135526], [32193, 2.4953712504002046], [32207, 2.8631210603825927], [32221, 2.753732635276321], [32235, 2.3659279880264092], [32249, 2.273958512619484], [32263, 2.3419462826136996], [32277, 2.8342672348930837], [32305, 2.4722881293686974], [32319, 2.5953436054637162], [32333, 2.4269238781365123], [32347, 2.4849818159518584], [32361, 2.3724252170204685], [32375, 2.754315051797679], [32389, 2.5180118245563134], [32403, 2.4101983557054893], [32417, 2.466558885457301], [32431, 2.435866943167581], [32445, 2.605192361181052], [32585, 2.5763248301091655], [32599, 2.3207847590695354], [32613, 2.2370220395840303], [32627, 2.442515575357639], [32641, 2.5053611729737586], [32655, 2.800173011783741], [32851, 2.4573171332001986], [32865, 2.6354301907325657], [32879, 2.3887587589826116], [32893, 5.575452752666539], [32907, 8.220588178172944], [32921, 8.392722388331975], [32991, 8.718841477618998], [33005, 7.6729934562428435], [33019, 10.001383658936604], [33033, 8.5528957659475], [33047, 8.730141636477915], [33061, 7.97353339885168], [33075, 9.19015911915157], [33089, 7.6747161388755885], [33103, 9.127578732669077], [33117, 7.935847250591458], [33131, 8.745363116046008], [33145, 8.716257781942286], [33159, 8.135352137353252], [33187, 6.923160557440212], [33201, 8.329410778311274], [33215, 5.5176989985463045], [33229, 5.149260176283619], [33243, 5.2256639795721735], [33271, 5.1624964106699744], [33299, 5.651542854305683], [33313, 4.834622835231713], [33327, 4.785463662286208], [33341, 4.817292652333652], [33355, 4.874452079318673], [33369, 4.723349283078306], [33383, 4.934297759878623], [33397, 4.863224237274421], [33411, 4.757434481237228], [33425, 4.7165942568142984], [33439, 4.805081491916171], [33453, 4.6116062189026525], [33467, 4.753094230951204], [33523, 4.68563425629071], [33537, 4.75524279912576], [33551, 4.631797584086799], [33649, 4.60285574728962], [33705, 4.664252275562338], [33719, 4.910451749641215], [33733, 4.965505592387046], [33747, 4.878986201574621], [33761, 4.7744244619018215], [33775, 4.713502614304249], [33803, 5.016407971013026], [33817, 5.293540772436552], [33831, 4.996183042978979], [33845, 5.190150853975678], [34041, 4.920264417149793], [34055, 4.888842635991644], [34069, 5.0229130448516175], [34083, 5.180642116160331], [34125, 5.063629751059964], [34139, 4.883411127832198], [34153, 5.001348962354325], [34167, 4.945160168640401]] \ No newline at end of file +[[28511, 1.9011236347919747], [29225, 2.7334296494731034], [29239, 2.1697493230448504], [29253, 1.739732932849922], [29267, 1.8701373672186974], [29281, 1.6175047522501087], [29295, 1.7619086315354104], [29309, 1.6563193683577326], [29323, 1.8242837603656883], [29337, 1.8670174136320128], [29351, 1.8297409133232378], [29365, 1.4711940025743548], [29379, 1.8310410932183698], [29393, 1.8271161155696787], [29407, 1.9417784199879629], [29421, 1.7502103372349807], [29435, 1.8384366177878695], [29449, 3.2969196169050576], [29463, 3.533637422899536], [29477, 3.2817162620058657], [29547, 4.284354723476936], [29561, 3.0811071119648545], [29575, 2.547667427547992], [29603, 2.419864573871065], [29617, 2.015716274264474], [29631, 2.329604574821814], [29645, 2.4109011136380616], [29659, 2.2533937851265673], [29673, 2.5891586722406625], [29743, 2.249023623356117], [29757, 2.2249363099612105], [29771, 2.3879923267053758], [29785, 4.063631787363224], [29799, 2.5552980540400982], [29813, 2.1810712223746025], [29827, 2.636230565489152], [29841, 2.5107010212793552], [29855, 2.6358893286347578], [29869, 2.458057683531379], [30009, 2.5562472393649474], [30023, 2.394496942185479], [30037, 2.1812371739741896], [30051, 2.274159106969875], [30065, 2.2746040913819736], [30079, 2.4477212177030365], [30093, 2.497164875546209], [30107, 2.578904047887315], [30121, 2.2221113135193242], [30135, 2.5521511923384814], [30149, 2.4043105668904072], [30163, 2.3569077834669936], [30177, 2.7114348779630824], [30191, 2.541950242372311], [30205, 2.2908943070604337], [30219, 2.4322892278009087], [30233, 2.93377178366019], [30247, 2.4492350945483654], [30261, 2.3054536820252753], [30513, 2.2265523415955655], [30527, 2.329308984566629], [30541, 2.757596275062833], [30555, 2.5670435012067236], [30569, 2.320473807094447], [30583, 2.3924155991401865], [30597, 2.5457857685550267], [30625, 2.5258906989091687], [30639, 3.1676014721557655], [30653, 2.567893317728014], [30667, 2.3051151877943203], [30681, 2.4294074577505005], [30695, 2.2578121032185576], [30709, 2.3679975525812456], [30723, 2.380447366899099], [30737, 2.7499204070064165], [30751, 2.6325922471906837], [30765, 2.446578680096405], [30779, 2.8835982511217537], [30793, 2.5957554797424227], [30807, 2.533808447417003], [30821, 2.336056810454294], [30835, 2.24950782548076], [30849, 2.3003523107135924], [30863, 2.3884715860290604], [30877, 2.3557159595181316], [30891, 2.429812831345365], [30905, 2.016953137247895], [30919, 2.64851976516814], [30933, 2.3034697653638725], [30947, 2.498223095052262], [30961, 2.6225681909080554], [30975, 2.4319368513973494], [30989, 2.558715751285025], [31003, 2.375997711481226], [31017, 3.211183763324997], [31031, 2.5357832873310935], [31045, 2.2553676452978175], [32095, 2.105765401260793], [32109, 3.0066629240424207], [32123, 2.7207561611164426], [32137, 2.5945897828315876], [32151, 3.139031291872656], [32165, 2.6798378705052075], [32179, 2.5561445174135526], [32193, 2.4953712504002046], [32207, 2.8631210603825927], [32221, 2.753732635276321], [32235, 2.3659279880264092], [32249, 2.273958512619484], [32263, 2.3419462826136996], [32277, 2.8342672348930837], [32305, 2.4722881293686974], [32319, 2.5953436054637162], [32333, 2.4269238781365123], [32347, 2.4849818159518584], [32361, 2.3724252170204685], [32375, 2.754315051797679], [32389, 2.5180118245563134], [32403, 2.4101983557054893], [32417, 2.466558885457301], [32431, 2.435866943167581], [32445, 2.605192361181052], [32585, 2.5763248301091655], [32599, 2.3207847590695354], [32613, 2.2370220395840303], [32627, 2.442515575357639], [32641, 2.5053611729737586], [32655, 2.800173011783741], [32851, 2.4573171332001986], [32865, 2.6354301907325657], [32879, 2.3887587589826116], [32893, 5.575452752666539], [32907, 8.220588178172944], [32921, 8.392722388331975], [32991, 8.718841477618998], [33005, 7.6729934562428435], [33019, 10.001383658936604], [33033, 8.5528957659475], [33047, 8.730141636477915], [33061, 7.97353339885168], [33075, 9.19015911915157], [33089, 7.6747161388755885], [33103, 9.127578732669077], [33117, 7.935847250591458], [33131, 8.745363116046008], [33145, 8.716257781942286], [33159, 8.135352137353252], [33187, 6.923160557440212], [33201, 8.329410778311274], [33215, 5.5176989985463045], [33229, 5.149260176283619], [33243, 5.2256639795721735], [33271, 5.1624964106699744], [33299, 5.651542854305683], [33313, 4.834622835231713], [33327, 4.785463662286208], [33341, 4.817292652333652], [33355, 4.874452079318673], [33369, 4.723349283078306], [33383, 4.934297759878623], [33397, 4.863224237274421], [33411, 4.757434481237228], [33425, 4.7165942568142984], [33439, 4.805081491916171], [33453, 4.6116062189026525], [33467, 4.753094230951204], [33523, 4.68563425629071], [33537, 4.75524279912576], [33551, 4.631797584086799], [33649, 4.60285574728962], [33705, 4.664252275562338], [33719, 4.910451749641215], [33733, 4.965505592387046], [33747, 4.878986201574621], [33761, 4.7744244619018215], [33775, 4.713502614304249], [33803, 5.016407971013026], [33817, 5.293540772436552], [33831, 4.996183042978979], [33845, 5.190150853975678], [34041, 4.920264417149793], [34055, 4.888842635991644], [34069, 5.0229130448516175], [34083, 5.180642116160331], [34125, 5.063629751059964], [34139, 4.883411127832198], [34153, 5.001348962354325], [34167, 4.998520735114708]] \ No newline at end of file diff --git a/graphs/summary/linear_model.SGDRegressorBenchmark.time_predict.json b/graphs/summary/linear_model.SGDRegressorBenchmark.time_predict.json index 1ca195e4bf..3877155d2c 100644 --- a/graphs/summary/linear_model.SGDRegressorBenchmark.time_predict.json +++ b/graphs/summary/linear_model.SGDRegressorBenchmark.time_predict.json @@ -1 +1 @@ -[[28511, 0.009068074833253727], [29225, 0.015712158861601037], [29239, 0.014080735325829787], [29253, 0.009126925111132228], [29267, 0.009159172224650649], [29281, 0.008981814371086258], [29295, 0.009523582238501934], [29309, 0.00921962099573859], [29323, 0.009185259296430277], [29337, 0.009187815108971431], [29351, 0.01043844514641317], [29365, 0.009222762445221638], [29379, 0.009313376020063461], [29393, 0.00941276814088956], [29407, 0.009231639598156247], [29421, 0.009162515893397923], [29435, 0.009114785257720205], [29449, 0.015637122967828033], [29463, 0.016516382129787108], [29477, 0.015158876230015555], [29547, 0.01614947338355869], [29561, 0.014279731276989345], [29575, 0.014023853780262567], [29603, 0.013578043340947504], [29617, 0.013403608451509882], [29631, 0.013685002066412051], [29645, 0.013395834932389926], [29659, 0.013375280964408721], [29673, 0.013436927643503668], [29743, 0.013679753720644486], [29757, 0.013657042075733209], [29771, 0.013729853265332919], [29785, 0.01560878688630017], [29799, 0.0136506564971218], [29813, 0.014251185382162506], [29827, 0.01501918558923196], [29841, 0.013805495965609925], [29855, 0.013650791117104865], [29869, 0.014350672146860415], [30009, 0.01398552324346412], [30023, 0.013740021272137557], [30037, 0.01465917580224785], [30051, 0.014480801183780685], [30065, 0.014328079155632481], [30079, 0.014356019910888163], [30093, 0.013937588749696759], [30107, 0.013943620979985909], [30121, 0.013597259535636714], [30135, 0.013506626045037384], [30149, 0.013686074205105227], [30163, 0.014155821025190063], [30177, 0.014580879864675676], [30191, 0.014336754220067617], [30205, 0.01414595261981127], [30219, 0.013920052236546474], [30233, 0.014050059091226657], [30247, 0.013843967393589006], [30261, 0.013814727561471212], [30513, 0.014124691409944068], [30527, 0.014473485528627988], [30541, 0.014295300374786053], [30555, 0.014471812033704935], [30569, 0.01412763707656734], [30583, 0.01399617598964727], [30597, 0.013433748994837375], [30625, 0.014132408120297762], [30639, 0.013605301613384323], [30653, 0.014185585073528269], [30667, 0.01413253026301674], [30681, 0.014699148553676331], [30695, 0.01475522967299451], [30709, 0.013958989557119736], [30723, 0.01357083896808854], [30737, 0.015315257972581726], [30751, 0.01402039539007747], [30765, 0.01449619935112736], [30779, 0.014394461945309354], [30793, 0.01450977077524142], [30807, 0.015100829712079574], [30821, 0.014329452899804118], [30835, 0.014177542219490743], [30849, 0.014474051339054652], [30863, 0.014117158501875504], [30877, 0.014892704933851676], [30891, 0.016268353839597394], [30905, 0.013516211617033331], [30919, 0.014506075908339624], [30933, 0.01364137530012733], [30947, 0.015218127244320182], [30961, 0.01451251261437086], [30975, 0.013923527011349083], [30989, 0.014417947455332722], [31003, 0.013416862029845475], [31017, 0.01378234830703794], [31031, 0.013762130790042562], [31045, 0.01352830624090547], [32095, 0.01211833243670923], [32109, 0.01277229319500121], [32123, 0.012608664987989434], [32137, 0.012689294399535632], [32151, 0.012627263933968421], [32165, 0.012594977171392793], [32179, 0.012739360051437163], [32193, 0.01234261135274333], [32207, 0.012714415140435786], [32221, 0.012944589691817603], [32235, 0.012349401044826645], [32249, 0.012753789519701197], [32263, 0.012605961462987533], [32277, 0.012743792773634207], [32305, 0.012357809499681384], [32319, 0.012405888722094138], [32333, 0.015407771741159596], [32347, 0.012520090975064315], [32361, 0.012735204640450148], [32375, 0.011810958500550814], [32389, 0.012986309519852132], [32403, 0.012026186553332601], [32417, 0.012879284180905802], [32431, 0.013442670734659032], [32445, 0.01204705369832093], [32585, 0.012221689719195331], [32599, 0.012502618041460621], [32613, 0.012911902328257589], [32627, 0.012384525445671373], [32641, 0.01318755297540689], [32655, 0.012793654702808924], [32851, 0.012850891952075812], [32865, 0.012505128845982415], [32879, 0.012665120529219295], [32893, 0.004971377947790269], [32907, 0.00468464056703556], [32921, 0.004705995462496771], [32991, 0.004918691745153845], [33005, 0.004964576065995353], [33019, 0.004814189789556507], [33033, 0.004565388869609771], [33047, 0.004743249036203791], [33061, 0.004690131362127787], [33075, 0.004672418685085803], [33089, 0.004794176231857777], [33103, 0.004890363100254693], [33117, 0.004825880144178278], [33131, 0.004555817291584683], [33145, 0.004727449275215414], [33159, 0.004641129282591164], [33187, 0.004831141347247861], [33201, 0.004898269127010098], [33215, 0.004951256834169466], [33229, 0.00486774175091687], [33243, 0.004858568016931463], [33271, 0.0047037269132934705], [33299, 0.004867162103276451], [33313, 0.0049901743081989455], [33327, 0.005029331097048213], [33341, 0.004827073610702922], [33355, 0.005012686388725167], [33369, 0.005180023076683113], [33383, 0.004961545551547482], [33397, 0.005141283457916233], [33411, 0.0051351746130031475], [33425, 0.0048379082721329465], [33439, 0.00493562705798725], [33453, 0.004749352440796965], [33467, 0.004726701649592501], [33523, 0.004763718859818586], [33537, 0.004784208428882609], [33551, 0.005051284587079933], [33649, 0.005615548038769298], [33705, 0.005134598561251491], [33719, 0.004817061599238514], [33733, 0.005096789094256943], [33747, 0.004898641927164417], [33761, 0.004746137553277379], [33775, 0.005528545687434299], [33803, 0.004664379575792286], [33817, 0.00516406266760543], [33831, 0.0049599191089375536], [33845, 0.00483671506755491], [34041, 0.0048950713704761315], [34055, 0.004959296732375637], [34069, 0.00484399953433517], [34083, 0.005018056274473669], [34125, 0.00488945841895952], [34139, 0.00468751244988149], [34153, 0.004944912573237747], [34167, 0.0050414973958999324]] \ No newline at end of file +[[28511, 0.009068074833253727], [29225, 0.015712158861601037], [29239, 0.014080735325829787], [29253, 0.009126925111132228], [29267, 0.009159172224650649], [29281, 0.008981814371086258], [29295, 0.009523582238501934], [29309, 0.00921962099573859], [29323, 0.009185259296430277], [29337, 0.009187815108971431], [29351, 0.01043844514641317], [29365, 0.009222762445221638], [29379, 0.009313376020063461], [29393, 0.00941276814088956], [29407, 0.009231639598156247], [29421, 0.009162515893397923], [29435, 0.009114785257720205], [29449, 0.015637122967828033], [29463, 0.016516382129787108], [29477, 0.015158876230015555], [29547, 0.01614947338355869], [29561, 0.014279731276989345], [29575, 0.014023853780262567], [29603, 0.013578043340947504], [29617, 0.013403608451509882], [29631, 0.013685002066412051], [29645, 0.013395834932389926], [29659, 0.013375280964408721], [29673, 0.013436927643503668], [29743, 0.013679753720644486], [29757, 0.013657042075733209], [29771, 0.013729853265332919], [29785, 0.01560878688630017], [29799, 0.0136506564971218], [29813, 0.014251185382162506], [29827, 0.01501918558923196], [29841, 0.013805495965609925], [29855, 0.013650791117104865], [29869, 0.014350672146860415], [30009, 0.01398552324346412], [30023, 0.013740021272137557], [30037, 0.01465917580224785], [30051, 0.014480801183780685], [30065, 0.014328079155632481], [30079, 0.014356019910888163], [30093, 0.013937588749696759], [30107, 0.013943620979985909], [30121, 0.013597259535636714], [30135, 0.013506626045037384], [30149, 0.013686074205105227], [30163, 0.014155821025190063], [30177, 0.014580879864675676], [30191, 0.014336754220067617], [30205, 0.01414595261981127], [30219, 0.013920052236546474], [30233, 0.014050059091226657], [30247, 0.013843967393589006], [30261, 0.013814727561471212], [30513, 0.014124691409944068], [30527, 0.014473485528627988], [30541, 0.014295300374786053], [30555, 0.014471812033704935], [30569, 0.01412763707656734], [30583, 0.01399617598964727], [30597, 0.013433748994837375], [30625, 0.014132408120297762], [30639, 0.013605301613384323], [30653, 0.014185585073528269], [30667, 0.01413253026301674], [30681, 0.014699148553676331], [30695, 0.01475522967299451], [30709, 0.013958989557119736], [30723, 0.01357083896808854], [30737, 0.015315257972581726], [30751, 0.01402039539007747], [30765, 0.01449619935112736], [30779, 0.014394461945309354], [30793, 0.01450977077524142], [30807, 0.015100829712079574], [30821, 0.014329452899804118], [30835, 0.014177542219490743], [30849, 0.014474051339054652], [30863, 0.014117158501875504], [30877, 0.014892704933851676], [30891, 0.016268353839597394], [30905, 0.013516211617033331], [30919, 0.014506075908339624], [30933, 0.01364137530012733], [30947, 0.015218127244320182], [30961, 0.01451251261437086], [30975, 0.013923527011349083], [30989, 0.014417947455332722], [31003, 0.013416862029845475], [31017, 0.01378234830703794], [31031, 0.013762130790042562], [31045, 0.01352830624090547], [32095, 0.01211833243670923], [32109, 0.01277229319500121], [32123, 0.012608664987989434], [32137, 0.012689294399535632], [32151, 0.012627263933968421], [32165, 0.012594977171392793], [32179, 0.012739360051437163], [32193, 0.01234261135274333], [32207, 0.012714415140435786], [32221, 0.012944589691817603], [32235, 0.012349401044826645], [32249, 0.012753789519701197], [32263, 0.012605961462987533], [32277, 0.012743792773634207], [32305, 0.012357809499681384], [32319, 0.012405888722094138], [32333, 0.015407771741159596], [32347, 0.012520090975064315], [32361, 0.012735204640450148], [32375, 0.011810958500550814], [32389, 0.012986309519852132], [32403, 0.012026186553332601], [32417, 0.012879284180905802], [32431, 0.013442670734659032], [32445, 0.01204705369832093], [32585, 0.012221689719195331], [32599, 0.012502618041460621], [32613, 0.012911902328257589], [32627, 0.012384525445671373], [32641, 0.01318755297540689], [32655, 0.012793654702808924], [32851, 0.012850891952075812], [32865, 0.012505128845982415], [32879, 0.012665120529219295], [32893, 0.004971377947790269], [32907, 0.00468464056703556], [32921, 0.004705995462496771], [32991, 0.004918691745153845], [33005, 0.004964576065995353], [33019, 0.004814189789556507], [33033, 0.004565388869609771], [33047, 0.004743249036203791], [33061, 0.004690131362127787], [33075, 0.004672418685085803], [33089, 0.004794176231857777], [33103, 0.004890363100254693], [33117, 0.004825880144178278], [33131, 0.004555817291584683], [33145, 0.004727449275215414], [33159, 0.004641129282591164], [33187, 0.004831141347247861], [33201, 0.004898269127010098], [33215, 0.004951256834169466], [33229, 0.00486774175091687], [33243, 0.004858568016931463], [33271, 0.0047037269132934705], [33299, 0.004867162103276451], [33313, 0.0049901743081989455], [33327, 0.005029331097048213], [33341, 0.004827073610702922], [33355, 0.005012686388725167], [33369, 0.005180023076683113], [33383, 0.004961545551547482], [33397, 0.005141283457916233], [33411, 0.0051351746130031475], [33425, 0.0048379082721329465], [33439, 0.00493562705798725], [33453, 0.004749352440796965], [33467, 0.004726701649592501], [33523, 0.004763718859818586], [33537, 0.004784208428882609], [33551, 0.005051284587079933], [33649, 0.005615548038769298], [33705, 0.005134598561251491], [33719, 0.004817061599238514], [33733, 0.005096789094256943], [33747, 0.004898641927164417], [33761, 0.004746137553277379], [33775, 0.005528545687434299], [33803, 0.004664379575792286], [33817, 0.00516406266760543], [33831, 0.0049599191089375536], [33845, 0.00483671506755491], [34041, 0.0048950713704761315], [34055, 0.004959296732375637], [34069, 0.00484399953433517], [34083, 0.005018056274473669], [34125, 0.00488945841895952], [34139, 0.00468751244988149], [34153, 0.004944912573237747], [34167, 0.005039424595074714]] \ No newline at end of file diff --git a/graphs/summary/linear_model.SGDRegressorBenchmark.track_test_score.json b/graphs/summary/linear_model.SGDRegressorBenchmark.track_test_score.json index 69c41045c0..7850d40e78 100644 --- a/graphs/summary/linear_model.SGDRegressorBenchmark.track_test_score.json +++ b/graphs/summary/linear_model.SGDRegressorBenchmark.track_test_score.json @@ -1 +1 @@ -[[28511, 0.9622459160255139], [29225, 0.9624828375897203], [29239, 0.962511052711059], [29253, 0.9625755910415524], [29267, 0.9623086171479092], [29281, 0.9624155482743327], [29295, 0.9621533182570786], [29309, 0.9626339647718797], [29323, 0.9623929833278689], [29337, 0.9626068626089709], [29351, 0.9624067450774344], [29365, 0.962614448258911], [29379, 0.9625018119792723], [29393, 0.9624513934735788], [29407, 0.962596803712981], [29421, 0.9625174166430844], [29435, 0.9626716490099049], [29449, 0.9624421148744419], [29463, 0.9626267219338013], [29477, 0.9623112431402681], [29547, 0.9627809356860699], [29561, 0.9622066726482448], [29575, 0.9628167700157864], [29603, 0.9625833715310439], [29617, 0.9622339053723825], [29631, 0.9623775617493874], [29645, 0.9626644361788856], [29659, 0.9626423422382848], [29673, 0.9624263288986178], [29743, 0.9625927357475483], [29757, 0.9623614331199204], [29771, 0.9625476662727251], [29785, 0.9623715684810581], [29799, 0.9621743367346488], [29813, 0.9626385779696116], [29827, 0.9622947947249454], [29841, 0.9624043816349808], [29855, 0.9622164612644978], [29869, 0.9621011430559612], [30009, 0.9626768580711851], [30023, 0.9629914063178622], [30037, 0.962694552948233], [30051, 0.9624072493702968], [30065, 0.9626352209061295], [30079, 0.9626438102494774], [30093, 0.9624276873530728], [30107, 0.9626552085881043], [30121, 0.9626593943753657], [30135, 0.9624561959543475], [30149, 0.9625050156328749], [30163, 0.9624463494007142], [30177, 0.9628082640123354], [30191, 0.9626798343770785], [30205, 0.9625229903425145], [30219, 0.9625087119293217], [30233, 0.962658873842418], [30247, 0.9624626544452973], [30261, 0.9625128973423762], [30513, 0.9627094456984698], [30527, 0.9625579589380313], [30541, 0.9626916121328373], [30555, 0.9625406097660223], [30569, 0.9623203030629678], [30583, 0.9625703128298664], [30597, 0.9624067263862262], [30625, 0.9625827571877265], [30639, 0.9625397972173868], [30653, 0.9625740418643597], [30667, 0.962574772774593], [30681, 0.9624984953429223], [30695, 0.9623959279560631], [30709, 0.9624555808683177], [30723, 0.9626925399789417], [30737, 0.9623740037355142], [30751, 0.9625285473745793], [30765, 0.9627858472958364], [30779, 0.9625979687465789], [30793, 0.962863307266554], [30807, 0.9622439252286786], [30821, 0.962338192142597], [30835, 0.9624590442500622], [30849, 0.9626470730318005], [30863, 0.9624316746543606], [30877, 0.9624534671239456], [30891, 0.9624044476077107], [30905, 0.9626905828418031], [30919, 0.9625708018910076], [30933, 0.9627585162191128], [30947, 0.9624075717271513], [30961, 0.962475214229113], [30975, 0.9627284049048855], [30989, 0.9624122882188034], [31003, 0.9626411564894914], [31017, 0.9625695959758311], [31031, 0.9624029758697736], [31045, 0.9624971766584479], [32095, 0.9620134792445316], [32109, 0.962373352768804], [32123, 0.9625409470727088], [32137, 0.9623809888431634], [32151, 0.9625527139250292], [32165, 0.9626628377202189], [32179, 0.9625433661513914], [32193, 0.9625799761623012], [32207, 0.9623688883181636], [32221, 0.962296231421304], [32235, 0.9617891984595817], [32249, 0.9624674900101221], [32263, 0.9626284631162699], [32277, 0.9624683271692076], [32305, 0.9624532104939746], [32319, 0.9625360426001399], [32333, 0.9624325077513735], [32347, 0.9626019773148857], [32361, 0.9625481107256872], [32375, 0.9627898601450351], [32389, 0.962572795235906], [32403, 0.9623216473851234], [32417, 0.962670007073709], [32431, 0.9626308750272676], [32445, 0.9626189922046616], [32585, 0.9624132315969165], [32599, 0.9623185698760167], [32613, 0.9625640021699097], [32627, 0.9617554980659453], [32641, 0.9625656789809585], [32655, 0.9627724021121863], [32851, 0.9625167883674887], [32865, 0.9625243516363775], [32879, 0.9621875956420886], [32893, 0.9629171887276176], [32907, 0.9625664430670088], [32921, 0.9628389284808533], [32991, 0.9625426120017634], [33005, 0.9622447713612888], [33019, 0.9627480780680285], [33033, 0.9626095332473292], [33047, 0.962370716085173], [33061, 0.9626406868962285], [33075, 0.9626097051387537], [33089, 0.9628752933099864], [33103, 0.9627916857131513], [33117, 0.962707490610385], [33131, 0.9624501233166344], [33145, 0.9623807357961452], [33159, 0.9623612296734569], [33187, 0.9622437013867516], [33201, 0.9626692529344352], [33215, 0.9625471435143687], [33229, 0.9626518706006236], [33243, 0.9629834733162839], [33271, 0.9632387540517059], [33299, 0.9626313315038968], [33313, 0.9625308858346865], [33327, 0.9625380502024974], [33341, 0.9627598760947885], [33355, 0.9629092764034278], [33369, 0.9623636625652195], [33383, 0.9625316596614408], [33397, 0.96256293335764], [33411, 0.9624422077321488], [33425, 0.9624227916069457], [33439, 0.9623813098639946], [33453, 0.9622636210543271], [33467, 0.9622135925991963], [33523, 0.9624327408981886], [33537, 0.9624970589479261], [33551, 0.9625514268071121], [33649, 0.9627932818560312], [33705, 0.9627537609068192], [33719, 0.9623100680995144], [33733, 0.9626233864789518], [33747, 0.9624632111865303], [33761, 0.9625382134302269], [33775, 0.9619075003799135], [33803, 0.962898442973949], [33817, 0.9625090966633822], [33831, 0.9626188603177117], [33845, 0.9626270557739389], [34041, 0.962381980493114], [34055, 0.9625275181877654], [34069, 0.9626931470765266], [34083, 0.962914794985417], [34125, 0.9629956139229451], [34139, 0.9623263153863747], [34153, 0.9624398948810692], [34167, 0.9626875043650744]] \ No newline at end of file +[[28511, 0.9622459160255139], [29225, 0.9624828375897203], [29239, 0.962511052711059], [29253, 0.9625755910415524], [29267, 0.9623086171479092], [29281, 0.9624155482743327], [29295, 0.9621533182570786], [29309, 0.9626339647718797], [29323, 0.9623929833278689], [29337, 0.9626068626089709], [29351, 0.9624067450774344], [29365, 0.962614448258911], [29379, 0.9625018119792723], [29393, 0.9624513934735788], [29407, 0.962596803712981], [29421, 0.9625174166430844], [29435, 0.9626716490099049], [29449, 0.9624421148744419], [29463, 0.9626267219338013], [29477, 0.9623112431402681], [29547, 0.9627809356860699], [29561, 0.9622066726482448], [29575, 0.9628167700157864], [29603, 0.9625833715310439], [29617, 0.9622339053723825], [29631, 0.9623775617493874], [29645, 0.9626644361788856], [29659, 0.9626423422382848], [29673, 0.9624263288986178], [29743, 0.9625927357475483], [29757, 0.9623614331199204], [29771, 0.9625476662727251], [29785, 0.9623715684810581], [29799, 0.9621743367346488], [29813, 0.9626385779696116], [29827, 0.9622947947249454], [29841, 0.9624043816349808], [29855, 0.9622164612644978], [29869, 0.9621011430559612], [30009, 0.9626768580711851], [30023, 0.9629914063178622], [30037, 0.962694552948233], [30051, 0.9624072493702968], [30065, 0.9626352209061295], [30079, 0.9626438102494774], [30093, 0.9624276873530728], [30107, 0.9626552085881043], [30121, 0.9626593943753657], [30135, 0.9624561959543475], [30149, 0.9625050156328749], [30163, 0.9624463494007142], [30177, 0.9628082640123354], [30191, 0.9626798343770785], [30205, 0.9625229903425145], [30219, 0.9625087119293217], [30233, 0.962658873842418], [30247, 0.9624626544452973], [30261, 0.9625128973423762], [30513, 0.9627094456984698], [30527, 0.9625579589380313], [30541, 0.9626916121328373], [30555, 0.9625406097660223], [30569, 0.9623203030629678], [30583, 0.9625703128298664], [30597, 0.9624067263862262], [30625, 0.9625827571877265], [30639, 0.9625397972173868], [30653, 0.9625740418643597], [30667, 0.962574772774593], [30681, 0.9624984953429223], [30695, 0.9623959279560631], [30709, 0.9624555808683177], [30723, 0.9626925399789417], [30737, 0.9623740037355142], [30751, 0.9625285473745793], [30765, 0.9627858472958364], [30779, 0.9625979687465789], [30793, 0.962863307266554], [30807, 0.9622439252286786], [30821, 0.962338192142597], [30835, 0.9624590442500622], [30849, 0.9626470730318005], [30863, 0.9624316746543606], [30877, 0.9624534671239456], [30891, 0.9624044476077107], [30905, 0.9626905828418031], [30919, 0.9625708018910076], [30933, 0.9627585162191128], [30947, 0.9624075717271513], [30961, 0.962475214229113], [30975, 0.9627284049048855], [30989, 0.9624122882188034], [31003, 0.9626411564894914], [31017, 0.9625695959758311], [31031, 0.9624029758697736], [31045, 0.9624971766584479], [32095, 0.9620134792445316], [32109, 0.962373352768804], [32123, 0.9625409470727088], [32137, 0.9623809888431634], [32151, 0.9625527139250292], [32165, 0.9626628377202189], [32179, 0.9625433661513914], [32193, 0.9625799761623012], [32207, 0.9623688883181636], [32221, 0.962296231421304], [32235, 0.9617891984595817], [32249, 0.9624674900101221], [32263, 0.9626284631162699], [32277, 0.9624683271692076], [32305, 0.9624532104939746], [32319, 0.9625360426001399], [32333, 0.9624325077513735], [32347, 0.9626019773148857], [32361, 0.9625481107256872], [32375, 0.9627898601450351], [32389, 0.962572795235906], [32403, 0.9623216473851234], [32417, 0.962670007073709], [32431, 0.9626308750272676], [32445, 0.9626189922046616], [32585, 0.9624132315969165], [32599, 0.9623185698760167], [32613, 0.9625640021699097], [32627, 0.9617554980659453], [32641, 0.9625656789809585], [32655, 0.9627724021121863], [32851, 0.9625167883674887], [32865, 0.9625243516363775], [32879, 0.9621875956420886], [32893, 0.9629171887276176], [32907, 0.9625664430670088], [32921, 0.9628389284808533], [32991, 0.9625426120017634], [33005, 0.9622447713612888], [33019, 0.9627480780680285], [33033, 0.9626095332473292], [33047, 0.962370716085173], [33061, 0.9626406868962285], [33075, 0.9626097051387537], [33089, 0.9628752933099864], [33103, 0.9627916857131513], [33117, 0.962707490610385], [33131, 0.9624501233166344], [33145, 0.9623807357961452], [33159, 0.9623612296734569], [33187, 0.9622437013867516], [33201, 0.9626692529344352], [33215, 0.9625471435143687], [33229, 0.9626518706006236], [33243, 0.9629834733162839], [33271, 0.9632387540517059], [33299, 0.9626313315038968], [33313, 0.9625308858346865], [33327, 0.9625380502024974], [33341, 0.9627598760947885], [33355, 0.9629092764034278], [33369, 0.9623636625652195], [33383, 0.9625316596614408], [33397, 0.96256293335764], [33411, 0.9624422077321488], [33425, 0.9624227916069457], [33439, 0.9623813098639946], [33453, 0.9622636210543271], [33467, 0.9622135925991963], [33523, 0.9624327408981886], [33537, 0.9624970589479261], [33551, 0.9625514268071121], [33649, 0.9627932818560312], [33705, 0.9627537609068192], [33719, 0.9623100680995144], [33733, 0.9626233864789518], [33747, 0.9624632111865303], [33761, 0.9625382134302269], [33775, 0.9619075003799135], [33803, 0.962898442973949], [33817, 0.9625090966633822], [33831, 0.9626188603177117], [33845, 0.9626270557739389], [34041, 0.962381980493114], [34055, 0.9625275181877654], [34069, 0.9626931470765266], [34083, 0.962914794985417], [34125, 0.9629956139229451], [34139, 0.9623263153863747], [34153, 0.9624398948810692], [34167, 0.9627397683660371]] \ No newline at end of file diff --git a/graphs/summary/linear_model.SGDRegressorBenchmark.track_train_score.json b/graphs/summary/linear_model.SGDRegressorBenchmark.track_train_score.json index d5762c8bd6..3fe511367d 100644 --- a/graphs/summary/linear_model.SGDRegressorBenchmark.track_train_score.json +++ b/graphs/summary/linear_model.SGDRegressorBenchmark.track_train_score.json @@ -1 +1 @@ -[[28511, 0.9630044415601858], [29225, 0.9629790864572761], [29239, 0.962998872840075], [29253, 0.962986250323764], [29267, 0.9629540995477683], [29281, 0.9627675416930732], [29295, 0.9629591176049521], [29309, 0.9630647841727149], [29323, 0.9629543627529241], [29337, 0.9629648364804538], [29351, 0.9630480322387434], [29365, 0.9630527318575374], [29379, 0.962981821068013], [29393, 0.9629662242698974], [29407, 0.9629436557495383], [29421, 0.9629807254232957], [29435, 0.9630320796084916], [29449, 0.9629451986539365], [29463, 0.9629770568458224], [29477, 0.9629839443375539], [29547, 0.962914328153237], [29561, 0.9630014235986857], [29575, 0.9629997711245767], [29603, 0.9629578147681286], [29617, 0.963000509846908], [29631, 0.9629773441055871], [29645, 0.9630840448564361], [29659, 0.9630489089749803], [29673, 0.9629736307208209], [29743, 0.9629923573815957], [29757, 0.9631742900466576], [29771, 0.9630841008044054], [29785, 0.9629987139048815], [29799, 0.9629941945394138], [29813, 0.9630311157630286], [29827, 0.9628850945447153], [29841, 0.9629161333031778], [29855, 0.9630245574674976], [29869, 0.9631501200245639], [30009, 0.9629810746177553], [30023, 0.9628979783487535], [30037, 0.9629420342194495], [30051, 0.9629991862245748], [30065, 0.9628589001718684], [30079, 0.9630279055034169], [30093, 0.9630330627664697], [30107, 0.9629871640886359], [30121, 0.9629528017208503], [30135, 0.963053982365704], [30149, 0.9630264764906367], [30163, 0.9630155612406691], [30177, 0.9629672245115792], [30191, 0.9629776276117731], [30205, 0.9629940987436391], [30219, 0.9629196587734855], [30233, 0.9629276389806962], [30247, 0.962952888140757], [30261, 0.9629350411572948], [30513, 0.9630399060479847], [30527, 0.9630134752740351], [30541, 0.9629670801681391], [30555, 0.9629641094290747], [30569, 0.9630240108957502], [30583, 0.9631531948919533], [30597, 0.9630429068072904], [30625, 0.9630264583454894], [30639, 0.9630498405196978], [30653, 0.9629609538768742], [30667, 0.9628220071588762], [30681, 0.9629072031977377], [30695, 0.963001993878299], [30709, 0.96304091880166], [30723, 0.9628155726508282], [30737, 0.9629782795418146], [30751, 0.9630048357958356], [30765, 0.9630613697693319], [30779, 0.9628968333661104], [30793, 0.9630658818638448], [30807, 0.9629111227506736], [30821, 0.963076189144368], [30835, 0.9629862843156868], [30849, 0.9630714455693504], [30863, 0.9629284643625773], [30877, 0.9629886498686933], [30891, 0.963002745673242], [30905, 0.9629596178962446], [30919, 0.9630052263210837], [30933, 0.963024661018868], [30947, 0.9630481309860981], [30961, 0.9629625672582823], [30975, 0.9630516998375651], [30989, 0.9630362989661042], [31003, 0.963006260021236], [31017, 0.9629621033920576], [31031, 0.962948028145856], [31045, 0.9630471930217233], [32095, 0.9631328786238391], [32109, 0.9629283309262884], [32123, 0.9629895349820201], [32137, 0.9629210002805397], [32151, 0.9629261034008197], [32165, 0.9630630978658942], [32179, 0.9629614344330414], [32193, 0.9630143415914082], [32207, 0.9629942957188646], [32221, 0.9629764729504812], [32235, 0.9629486244091088], [32249, 0.9630228062541984], [32263, 0.9630176842630908], [32277, 0.963011314735375], [32305, 0.963051487577571], [32319, 0.9630600538135808], [32333, 0.9629954492502694], [32347, 0.9630539886136279], [32361, 0.9629938244341628], [32375, 0.9629836274120415], [32389, 0.9630053789622933], [32403, 0.9630669665191189], [32417, 0.9629478700716296], [32431, 0.9629773148339257], [32445, 0.9629479057498191], [32585, 0.9630672602453725], [32599, 0.9630042487885286], [32613, 0.9630388201942178], [32627, 0.9630183194000547], [32641, 0.9629883503948331], [32655, 0.9628758357358261], [32851, 0.9630932029623098], [32865, 0.9630079023376323], [32879, 0.962983547009797], [32893, 0.9630264310463781], [32907, 0.963037123900234], [32921, 0.9631316453646942], [32991, 0.9629576335202368], [33005, 0.9631518316949955], [33019, 0.9629816928762597], [33033, 0.9630987545645477], [33047, 0.96298813295032], [33061, 0.9630384455467892], [33075, 0.9632101287063646], [33089, 0.9629503230046429], [33103, 0.9630833221505237], [33117, 0.9630322562850135], [33131, 0.9629874883811356], [33145, 0.9631981326700361], [33159, 0.9630945463128993], [33187, 0.9630437005814275], [33201, 0.9629420677019538], [33215, 0.9630299103533361], [33229, 0.962986396824349], [33243, 0.9630431666568173], [33271, 0.9630090735178686], [33299, 0.9630823403118994], [33313, 0.9630290302352295], [33327, 0.9630603988886499], [33341, 0.9630424514461597], [33355, 0.9630238642807819], [33369, 0.9630878786470846], [33383, 0.9629577243541404], [33397, 0.9629623229968042], [33411, 0.9630988243265581], [33425, 0.9629743774011545], [33439, 0.9631360912489209], [33453, 0.9629225241326737], [33467, 0.9630752688628497], [33523, 0.9630462187789175], [33537, 0.9630200325789552], [33551, 0.9630989425123332], [33649, 0.9629768874848343], [33705, 0.9628765708741439], [33719, 0.9630115375242008], [33733, 0.9631138728965102], [33747, 0.9630259125441528], [33761, 0.9631922274730498], [33775, 0.9631256710900914], [33803, 0.9630989909147577], [33817, 0.963069278952102], [33831, 0.9630825898471231], [33845, 0.9630896739623475], [34041, 0.9630135401766877], [34055, 0.9630255751488832], [34069, 0.9630421658649361], [34083, 0.9630184850448067], [34125, 0.9631121730243272], [34139, 0.963106088182718], [34153, 0.9630434767167676], [34167, 0.9629817195918982]] \ No newline at end of file +[[28511, 0.9630044415601858], [29225, 0.9629790864572761], [29239, 0.962998872840075], [29253, 0.962986250323764], [29267, 0.9629540995477683], [29281, 0.9627675416930732], [29295, 0.9629591176049521], [29309, 0.9630647841727149], [29323, 0.9629543627529241], [29337, 0.9629648364804538], [29351, 0.9630480322387434], [29365, 0.9630527318575374], [29379, 0.962981821068013], [29393, 0.9629662242698974], [29407, 0.9629436557495383], [29421, 0.9629807254232957], [29435, 0.9630320796084916], [29449, 0.9629451986539365], [29463, 0.9629770568458224], [29477, 0.9629839443375539], [29547, 0.962914328153237], [29561, 0.9630014235986857], [29575, 0.9629997711245767], [29603, 0.9629578147681286], [29617, 0.963000509846908], [29631, 0.9629773441055871], [29645, 0.9630840448564361], [29659, 0.9630489089749803], [29673, 0.9629736307208209], [29743, 0.9629923573815957], [29757, 0.9631742900466576], [29771, 0.9630841008044054], [29785, 0.9629987139048815], [29799, 0.9629941945394138], [29813, 0.9630311157630286], [29827, 0.9628850945447153], [29841, 0.9629161333031778], [29855, 0.9630245574674976], [29869, 0.9631501200245639], [30009, 0.9629810746177553], [30023, 0.9628979783487535], [30037, 0.9629420342194495], [30051, 0.9629991862245748], [30065, 0.9628589001718684], [30079, 0.9630279055034169], [30093, 0.9630330627664697], [30107, 0.9629871640886359], [30121, 0.9629528017208503], [30135, 0.963053982365704], [30149, 0.9630264764906367], [30163, 0.9630155612406691], [30177, 0.9629672245115792], [30191, 0.9629776276117731], [30205, 0.9629940987436391], [30219, 0.9629196587734855], [30233, 0.9629276389806962], [30247, 0.962952888140757], [30261, 0.9629350411572948], [30513, 0.9630399060479847], [30527, 0.9630134752740351], [30541, 0.9629670801681391], [30555, 0.9629641094290747], [30569, 0.9630240108957502], [30583, 0.9631531948919533], [30597, 0.9630429068072904], [30625, 0.9630264583454894], [30639, 0.9630498405196978], [30653, 0.9629609538768742], [30667, 0.9628220071588762], [30681, 0.9629072031977377], [30695, 0.963001993878299], [30709, 0.96304091880166], [30723, 0.9628155726508282], [30737, 0.9629782795418146], [30751, 0.9630048357958356], [30765, 0.9630613697693319], [30779, 0.9628968333661104], [30793, 0.9630658818638448], [30807, 0.9629111227506736], [30821, 0.963076189144368], [30835, 0.9629862843156868], [30849, 0.9630714455693504], [30863, 0.9629284643625773], [30877, 0.9629886498686933], [30891, 0.963002745673242], [30905, 0.9629596178962446], [30919, 0.9630052263210837], [30933, 0.963024661018868], [30947, 0.9630481309860981], [30961, 0.9629625672582823], [30975, 0.9630516998375651], [30989, 0.9630362989661042], [31003, 0.963006260021236], [31017, 0.9629621033920576], [31031, 0.962948028145856], [31045, 0.9630471930217233], [32095, 0.9631328786238391], [32109, 0.9629283309262884], [32123, 0.9629895349820201], [32137, 0.9629210002805397], [32151, 0.9629261034008197], [32165, 0.9630630978658942], [32179, 0.9629614344330414], [32193, 0.9630143415914082], [32207, 0.9629942957188646], [32221, 0.9629764729504812], [32235, 0.9629486244091088], [32249, 0.9630228062541984], [32263, 0.9630176842630908], [32277, 0.963011314735375], [32305, 0.963051487577571], [32319, 0.9630600538135808], [32333, 0.9629954492502694], [32347, 0.9630539886136279], [32361, 0.9629938244341628], [32375, 0.9629836274120415], [32389, 0.9630053789622933], [32403, 0.9630669665191189], [32417, 0.9629478700716296], [32431, 0.9629773148339257], [32445, 0.9629479057498191], [32585, 0.9630672602453725], [32599, 0.9630042487885286], [32613, 0.9630388201942178], [32627, 0.9630183194000547], [32641, 0.9629883503948331], [32655, 0.9628758357358261], [32851, 0.9630932029623098], [32865, 0.9630079023376323], [32879, 0.962983547009797], [32893, 0.9630264310463781], [32907, 0.963037123900234], [32921, 0.9631316453646942], [32991, 0.9629576335202368], [33005, 0.9631518316949955], [33019, 0.9629816928762597], [33033, 0.9630987545645477], [33047, 0.96298813295032], [33061, 0.9630384455467892], [33075, 0.9632101287063646], [33089, 0.9629503230046429], [33103, 0.9630833221505237], [33117, 0.9630322562850135], [33131, 0.9629874883811356], [33145, 0.9631981326700361], [33159, 0.9630945463128993], [33187, 0.9630437005814275], [33201, 0.9629420677019538], [33215, 0.9630299103533361], [33229, 0.962986396824349], [33243, 0.9630431666568173], [33271, 0.9630090735178686], [33299, 0.9630823403118994], [33313, 0.9630290302352295], [33327, 0.9630603988886499], [33341, 0.9630424514461597], [33355, 0.9630238642807819], [33369, 0.9630878786470846], [33383, 0.9629577243541404], [33397, 0.9629623229968042], [33411, 0.9630988243265581], [33425, 0.9629743774011545], [33439, 0.9631360912489209], [33453, 0.9629225241326737], [33467, 0.9630752688628497], [33523, 0.9630462187789175], [33537, 0.9630200325789552], [33551, 0.9630989425123332], [33649, 0.9629768874848343], [33705, 0.9628765708741439], [33719, 0.9630115375242008], [33733, 0.9631138728965102], [33747, 0.9630259125441528], [33761, 0.9631922274730498], [33775, 0.9631256710900914], [33803, 0.9630989909147577], [33817, 0.963069278952102], [33831, 0.9630825898471231], [33845, 0.9630896739623475], [34041, 0.9630135401766877], [34055, 0.9630255751488832], [34069, 0.9630421658649361], [34083, 0.9630184850448067], [34125, 0.9631121730243272], [34139, 0.963106088182718], [34153, 0.9630434767167676], [34167, 0.9630213520132237]] \ No newline at end of file diff --git a/graphs/summary/manifold.TSNEBenchmark.peakmem_fit.json b/graphs/summary/manifold.TSNEBenchmark.peakmem_fit.json index abb711bead..425e3e8601 100644 --- a/graphs/summary/manifold.TSNEBenchmark.peakmem_fit.json +++ b/graphs/summary/manifold.TSNEBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 104739382.32000509], [29225, 100324504.88445376], [29239, 100252841.25824133], [29253, 102565164.83280827], [29267, 102364328.68075438], [29281, 102611138.30291165], [29295, 102664856.68484826], [29309, 102633856.99383703], [29323, 102506100.40773778], [29337, 102660421.29140563], [29351, 101486407.26955537], [29365, 101302445.73040254], [29379, 101701858.21672677], [29393, 101599525.8823257], [29407, 101793901.40678303], [29421, 101485164.6809084], [29435, 101892561.93251063], [29449, 100048512.55610597], [29463, 99932839.51920019], [29477, 99913419.95574206], [29547, 99842680.63847484], [29561, 100210955.7395395], [29575, 99365024.99315043], [29603, 100864186.44299299], [29617, 101010589.41643548], [29631, 101200203.15095374], [29645, 101358150.10826598], [29659, 100957630.37835556], [29673, 101054519.10580103], [29743, 100915275.47477168], [29757, 101120129.40396461], [29771, 101006972.65571599], [29785, 101297021.98635703], [29799, 100849745.98440191], [29813, 101082067.22066657], [29827, 101325687.74024802], [29841, 100957441.83064546], [29855, 100917812.24162418], [29869, 101233012.49846199], [30009, 101051493.30573079], [30023, 101220197.41576308], [30037, 101046277.00069146], [30051, 101052897.55403885], [30065, 101162490.23561727], [30079, 101209884.73225896], [30093, 101109237.36236662], [30107, 101048862.45223469], [30121, 101214175.84375], [30135, 101218700.7974832], [30149, 101752857.36773491], [30163, 101634670.76509267], [30177, 101680556.4387688], [30191, 101662336.58194673], [30205, 101668862.20639546], [30219, 101539147.7436362], [30233, 101480144.34006748], [30247, 101778430.98865396], [30261, 101587384.64678565], [30513, 101943344.03395635], [30527, 101566596.25997917], [30541, 101562581.16621442], [30555, 101548541.29155321], [30569, 101381984.39563417], [30583, 101663325.11560555], [30597, 101117571.95350271], [30625, 101412473.99741547], [30639, 101297778.83688572], [30653, 101408836.86237174], [30667, 101428588.47080216], [30681, 101336625.98403044], [30695, 101626741.77615668], [30709, 101436513.31210957], [30723, 101326824.48831484], [30737, 101652959.43248223], [30751, 101667219.9261734], [30765, 102068793.1974492], [30779, 101659087.58184318], [30793, 101627753.12838186], [30807, 101492999.86355026], [30821, 101553222.65217872], [30835, 102155002.86483398], [30849, 101649039.47919941], [30863, 101662320.74151589], [30877, 101910590.68811935], [30891, 101885588.47719024], [30905, 101553290.64409278], [30919, 101681216.87638699], [30933, 101399948.86602533], [30947, 101486791.7852909], [30961, 101605128.9444599], [30975, 101719285.74891272], [30989, 101657032.04313429], [31003, 102021402.49828155], [31017, 101634876.25922936], [31031, 101568118.70263006], [31045, 101866570.71189992], [32095, 102548663.55703779], [32109, 108238354.78642097], [32123, 108416244.0474096], [32137, 108287580.16919382], [32151, 108590502.50696087], [32165, 108329329.73508583], [32179, 107938654.34506768], [32193, 108171615.47371423], [32207, 109888490.99894375], [32221, 112072120.37591775], [32235, 113265080.94589151], [32249, 111833279.42554031], [32263, 112156614.84570742], [32277, 110971925.634448], [32305, 112272884.70244218], [32319, 115176876.86296295], [32333, 115694982.152197], [32347, 115491097.08892736], [32361, 115573344.42238113], [32375, 115265579.59304103], [32389, 115793104.55907577], [32403, 115396591.64391324], [32417, 115580068.3569209], [32431, 115489004.30002838], [32445, 115526120.66311583], [32585, 115835089.58767201], [32599, 116040872.66560298], [32613, 115860750.03138614], [32627, 115820982.60281566], [32641, 115988255.54761146], [32655, 116029550.17713432], [32851, 117181636.05242415], [32865, 116804263.70438819], [32879, 116840160.08651052], [32893, 116385966.18924479], [32907, 117030257.18566568], [32921, 116717010.1035541], [32991, 116982476.5826792], [33005, 116994023.4782035], [33019, 116649609.47838329], [33033, 116679017.87708536], [33047, 117025195.27966656], [33061, 117201622.42221591], [33075, 117402249.76706368], [33089, 131079613.05379799], [33103, 145190429.53593644], [33117, 145405916.7630841], [33131, 144219182.87597328], [33145, 145424750.86749578], [33159, 145353672.04490742], [33187, 117222213.11258306], [33201, 117099497.55727056], [33215, 114305661.81799397], [33229, 106120493.29300608], [33243, 106397905.95254824], [33271, 96497370.26076944], [33299, 95734554.90285026], [33313, 96567275.29005176], [33327, 96958190.05765286], [33341, 96685436.15632136], [33355, 96955301.52440731], [33369, 96764448.18608509], [33383, 97683664.1603893], [33397, 98020350.40275326], [33411, 98038553.69839568], [33425, 98084801.0684273], [33439, 99565157.72511703], [33453, 94807539.29062241], [33467, 94755525.27454081], [33523, 94394960.79545185], [33537, 94456513.25181182], [33551, 94127877.03354286], [33649, 93641555.72816506], [33705, 93151883.53584474], [33719, 93184779.78022912], [33733, 93121436.2280995], [33747, 93251169.31023517], [33761, 93027856.59043854], [33775, 93167509.03502168], [33803, 93252054.62995902], [33817, 92788581.33830866], [33831, 92976294.3879453], [33845, 93082179.9269063], [34041, 92760120.81518206], [34055, 92965659.51240623], [34069, 93017630.30439658], [34083, 92804954.28905267], [34125, 92888202.87316047], [34139, 92576694.50760852], [34153, 92827324.71662854], [34167, 92709411.52468275]] \ No newline at end of file +[[28511, 104739382.32000509], [29225, 100324504.88445376], [29239, 100252841.25824133], [29253, 102565164.83280827], [29267, 102364328.68075438], [29281, 102611138.30291165], [29295, 102664856.68484826], [29309, 102633856.99383703], [29323, 102506100.40773778], [29337, 102660421.29140563], [29351, 101486407.26955537], [29365, 101302445.73040254], [29379, 101701858.21672677], [29393, 101599525.8823257], [29407, 101793901.40678303], [29421, 101485164.6809084], [29435, 101892561.93251063], [29449, 100048512.55610597], [29463, 99932839.51920019], [29477, 99913419.95574206], [29547, 99842680.63847484], [29561, 100210955.7395395], [29575, 99365024.99315043], [29603, 100864186.44299299], [29617, 101010589.41643548], [29631, 101200203.15095374], [29645, 101358150.10826598], [29659, 100957630.37835556], [29673, 101054519.10580103], [29743, 100915275.47477168], [29757, 101120129.40396461], [29771, 101006972.65571599], [29785, 101297021.98635703], [29799, 100849745.98440191], [29813, 101082067.22066657], [29827, 101325687.74024802], [29841, 100957441.83064546], [29855, 100917812.24162418], [29869, 101233012.49846199], [30009, 101051493.30573079], [30023, 101220197.41576308], [30037, 101046277.00069146], [30051, 101052897.55403885], [30065, 101162490.23561727], [30079, 101209884.73225896], [30093, 101109237.36236662], [30107, 101048862.45223469], [30121, 101214175.84375], [30135, 101218700.7974832], [30149, 101752857.36773491], [30163, 101634670.76509267], [30177, 101680556.4387688], [30191, 101662336.58194673], [30205, 101668862.20639546], [30219, 101539147.7436362], [30233, 101480144.34006748], [30247, 101778430.98865396], [30261, 101587384.64678565], [30513, 101943344.03395635], [30527, 101566596.25997917], [30541, 101562581.16621442], [30555, 101548541.29155321], [30569, 101381984.39563417], [30583, 101663325.11560555], [30597, 101117571.95350271], [30625, 101412473.99741547], [30639, 101297778.83688572], [30653, 101408836.86237174], [30667, 101428588.47080216], [30681, 101336625.98403044], [30695, 101626741.77615668], [30709, 101436513.31210957], [30723, 101326824.48831484], [30737, 101652959.43248223], [30751, 101667219.9261734], [30765, 102068793.1974492], [30779, 101659087.58184318], [30793, 101627753.12838186], [30807, 101492999.86355026], [30821, 101553222.65217872], [30835, 102155002.86483398], [30849, 101649039.47919941], [30863, 101662320.74151589], [30877, 101910590.68811935], [30891, 101885588.47719024], [30905, 101553290.64409278], [30919, 101681216.87638699], [30933, 101399948.86602533], [30947, 101486791.7852909], [30961, 101605128.9444599], [30975, 101719285.74891272], [30989, 101657032.04313429], [31003, 102021402.49828155], [31017, 101634876.25922936], [31031, 101568118.70263006], [31045, 101866570.71189992], [32095, 102548663.55703779], [32109, 108238354.78642097], [32123, 108416244.0474096], [32137, 108287580.16919382], [32151, 108590502.50696087], [32165, 108329329.73508583], [32179, 107938654.34506768], [32193, 108171615.47371423], [32207, 109888490.99894375], [32221, 112072120.37591775], [32235, 113265080.94589151], [32249, 111833279.42554031], [32263, 112156614.84570742], [32277, 110971925.634448], [32305, 112272884.70244218], [32319, 115176876.86296295], [32333, 115694982.152197], [32347, 115491097.08892736], [32361, 115573344.42238113], [32375, 115265579.59304103], [32389, 115793104.55907577], [32403, 115396591.64391324], [32417, 115580068.3569209], [32431, 115489004.30002838], [32445, 115526120.66311583], [32585, 115835089.58767201], [32599, 116040872.66560298], [32613, 115860750.03138614], [32627, 115820982.60281566], [32641, 115988255.54761146], [32655, 116029550.17713432], [32851, 117181636.05242415], [32865, 116804263.70438819], [32879, 116840160.08651052], [32893, 116385966.18924479], [32907, 117030257.18566568], [32921, 116717010.1035541], [32991, 116982476.5826792], [33005, 116994023.4782035], [33019, 116649609.47838329], [33033, 116679017.87708536], [33047, 117025195.27966656], [33061, 117201622.42221591], [33075, 117402249.76706368], [33089, 131079613.05379799], [33103, 145190429.53593644], [33117, 145405916.7630841], [33131, 144219182.87597328], [33145, 145424750.86749578], [33159, 145353672.04490742], [33187, 117222213.11258306], [33201, 117099497.55727056], [33215, 114305661.81799397], [33229, 106120493.29300608], [33243, 106397905.95254824], [33271, 96497370.26076944], [33299, 95734554.90285026], [33313, 96567275.29005176], [33327, 96958190.05765286], [33341, 96685436.15632136], [33355, 96955301.52440731], [33369, 96764448.18608509], [33383, 97683664.1603893], [33397, 98020350.40275326], [33411, 98038553.69839568], [33425, 98084801.0684273], [33439, 99565157.72511703], [33453, 94807539.29062241], [33467, 94755525.27454081], [33523, 94394960.79545185], [33537, 94456513.25181182], [33551, 94127877.03354286], [33649, 93641555.72816506], [33705, 93151883.53584474], [33719, 93184779.78022912], [33733, 93121436.2280995], [33747, 93251169.31023517], [33761, 93027856.59043854], [33775, 93167509.03502168], [33803, 93252054.62995902], [33817, 92788581.33830866], [33831, 92976294.3879453], [33845, 93082179.9269063], [34041, 92760120.81518206], [34055, 92965659.51240623], [34069, 93017630.30439658], [34083, 92804954.28905267], [34125, 92888202.87316047], [34139, 92576694.50760852], [34153, 92827324.71662854], [34167, 92598119.50468178]] \ No newline at end of file diff --git a/graphs/summary/manifold.TSNEBenchmark.time_fit.json b/graphs/summary/manifold.TSNEBenchmark.time_fit.json index e1bc5ae6ef..83d37c327b 100644 --- a/graphs/summary/manifold.TSNEBenchmark.time_fit.json +++ b/graphs/summary/manifold.TSNEBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 4.285119638270411], [29225, 6.716879899802127], [29239, 7.202132647675649], [29253, 4.260957432587039], [29267, 4.24241068999279], [29281, 4.201747214492125], [29295, 4.26960189913556], [29309, 4.303531278045078], [29323, 4.228366699132311], [29337, 4.2192395478004165], [29351, 4.259996767946958], [29365, 4.178368046468679], [29379, 4.273061063401439], [29393, 4.242412848262536], [29407, 4.318497340160457], [29421, 4.210816660706605], [29435, 4.0850885375582635], [29449, 7.082125164060559], [29463, 7.225865257283078], [29477, 7.35672194845234], [29547, 7.386253824726119], [29561, 7.2025312498450775], [29575, 6.068704568170839], [29603, 6.070755327623203], [29617, 6.13241302499], [29631, 6.203945186061776], [29645, 6.300438936088889], [29659, 6.145240790090675], [29673, 6.176403973747939], [29743, 6.213143538873851], [29757, 6.037792359600178], [29771, 6.156417544164876], [29785, 7.334434345658645], [29799, 6.7712217234165335], [29813, 6.574112680085637], [29827, 6.478960670415651], [29841, 6.508374751432987], [29855, 6.605600397394751], [29869, 6.459465265856601], [30009, 6.543538476992899], [30023, 6.03356868582048], [30037, 6.525317998825183], [30051, 6.421873510072528], [30065, 6.288854362304587], [30079, 6.593543721035005], [30093, 6.747226005194234], [30107, 6.4141622075662665], [30121, 6.712733046344133], [30135, 6.128387761195837], [30149, 6.702425216372906], [30163, 6.558581800049983], [30177, 6.396924576689518], [30191, 6.356600667338133], [30205, 6.873147863409041], [30219, 6.354025332095872], [30233, 6.271347753681688], [30247, 6.6833641643223425], [30261, 6.703510807241625], [30513, 6.582662269951506], [30527, 6.639197393667442], [30541, 6.4485431631005], [30555, 6.467166741933345], [30569, 6.655779865944895], [30583, 6.894539217444941], [30597, 5.910481941666973], [30625, 6.663414920869459], [30639, 6.658504480116483], [30653, 6.2678443543967], [30667, 6.306326867847772], [30681, 6.776715532336094], [30695, 6.053198792146372], [30709, 6.6218292689132205], [30723, 6.36086699390596], [30737, 6.430510516180575], [30751, 6.487314619726304], [30765, 6.367004171695868], [30779, 7.138328303462861], [30793, 6.444183430673643], [30807, 5.957139753154352], [30821, 6.828501779434161], [30835, 6.624693030116392], [30849, 6.613098760933707], [30863, 7.174433023486831], [30877, 6.54668948989225], [30891, 6.48927475966895], [30905, 6.5385367048554], [30919, 6.222891236942136], [30933, 6.856147639862451], [30947, 6.431684720351901], [30961, 6.5346491426474005], [30975, 6.6695605146557835], [30989, 6.433518401797465], [31003, 6.237192603308961], [31017, 7.065761649454286], [31031, 6.661432059202994], [31045, 6.522195406180468], [32095, 5.967235618288347], [32109, 6.421659450492161], [32123, 6.25691502817487], [32137, 6.471737965812906], [32151, 6.14286813302754], [32165, 6.4159094535152335], [32179, 6.137136405529396], [32193, 6.121999669422391], [32207, 6.196098232453296], [32221, 6.193656563920676], [32235, 6.339392922279157], [32249, 5.953563401483854], [32263, 6.509584554562233], [32277, 6.3501945298500075], [32305, 6.3491439319483485], [32319, 6.314348287792778], [32333, 6.591864801295297], [32347, 6.679553516999191], [32361, 6.445633241625595], [32375, 6.205612719702542], [32389, 6.764867830529715], [32403, 6.401188938577197], [32417, 6.615983775131512], [32431, 6.266892306368067], [32445, 6.687414504541441], [32585, 6.358893158284371], [32599, 6.450353950941284], [32613, 6.352619829469215], [32627, 6.25661494723137], [32641, 6.418673571411627], [32655, 6.378371979255107], [32851, 5.82302236875248], [32865, 6.141059972005534], [32879, 5.897862446958015], [32893, 5.93943810935537], [32907, 6.837020004810673], [32921, 5.972723738841347], [32991, 6.041460403146379], [33005, 5.814708129761285], [33019, 6.10296902550315], [33033, 5.748305160328952], [33047, 5.627230881578814], [33061, 5.833793308465005], [33075, 5.797970617214275], [33089, 5.852632528778936], [33103, 5.914090129579821], [33117, 5.985516814412298], [33131, 5.699641239305719], [33145, 6.253484413398432], [33159, 5.578085814561098], [33187, 5.748114198069662], [33201, 5.981046250979453], [33215, 5.913798200556115], [33229, 5.474720616467511], [33243, 5.422856624624424], [33271, 4.8674054385704215], [33299, 7.297430288714451], [33313, 5.088301753394458], [33327, 5.138197838621745], [33341, 5.178910602797847], [33355, 5.533513421960412], [33369, 4.910760248728118], [33383, 4.90319163260344], [33397, 4.853334901657242], [33411, 4.781157291472394], [33425, 4.784586854826751], [33439, 4.671758410167287], [33453, 4.694603682748759], [33467, 4.64544149021348], [33523, 4.614550858948505], [33537, 4.773789199244022], [33551, 4.94752241207121], [33649, 5.157504503895991], [33705, 4.689210001170598], [33719, 5.407204760293551], [33733, 5.248385780891517], [33747, 4.835527650838202], [33761, 4.902112414122871], [33775, 4.805359059610634], [33803, 4.726475692269859], [33817, 4.687053981857693], [33831, 4.8440217217216], [33845, 4.884601134455797], [34041, 4.936534497296167], [34055, 5.070854530562401], [34069, 4.9262156547508305], [34083, 4.9399815581392], [34125, 4.588771210759588], [34139, 4.799529461552558], [34153, 4.54305913754263], [34167, 4.623619410293616]] \ No newline at end of file +[[28511, 4.285119638270411], [29225, 6.716879899802127], [29239, 7.202132647675649], [29253, 4.260957432587039], [29267, 4.24241068999279], [29281, 4.201747214492125], [29295, 4.26960189913556], [29309, 4.303531278045078], [29323, 4.228366699132311], [29337, 4.2192395478004165], [29351, 4.259996767946958], [29365, 4.178368046468679], [29379, 4.273061063401439], [29393, 4.242412848262536], [29407, 4.318497340160457], [29421, 4.210816660706605], [29435, 4.0850885375582635], [29449, 7.082125164060559], [29463, 7.225865257283078], [29477, 7.35672194845234], [29547, 7.386253824726119], [29561, 7.2025312498450775], [29575, 6.068704568170839], [29603, 6.070755327623203], [29617, 6.13241302499], [29631, 6.203945186061776], [29645, 6.300438936088889], [29659, 6.145240790090675], [29673, 6.176403973747939], [29743, 6.213143538873851], [29757, 6.037792359600178], [29771, 6.156417544164876], [29785, 7.334434345658645], [29799, 6.7712217234165335], [29813, 6.574112680085637], [29827, 6.478960670415651], [29841, 6.508374751432987], [29855, 6.605600397394751], [29869, 6.459465265856601], [30009, 6.543538476992899], [30023, 6.03356868582048], [30037, 6.525317998825183], [30051, 6.421873510072528], [30065, 6.288854362304587], [30079, 6.593543721035005], [30093, 6.747226005194234], [30107, 6.4141622075662665], [30121, 6.712733046344133], [30135, 6.128387761195837], [30149, 6.702425216372906], [30163, 6.558581800049983], [30177, 6.396924576689518], [30191, 6.356600667338133], [30205, 6.873147863409041], [30219, 6.354025332095872], [30233, 6.271347753681688], [30247, 6.6833641643223425], [30261, 6.703510807241625], [30513, 6.582662269951506], [30527, 6.639197393667442], [30541, 6.4485431631005], [30555, 6.467166741933345], [30569, 6.655779865944895], [30583, 6.894539217444941], [30597, 5.910481941666973], [30625, 6.663414920869459], [30639, 6.658504480116483], [30653, 6.2678443543967], [30667, 6.306326867847772], [30681, 6.776715532336094], [30695, 6.053198792146372], [30709, 6.6218292689132205], [30723, 6.36086699390596], [30737, 6.430510516180575], [30751, 6.487314619726304], [30765, 6.367004171695868], [30779, 7.138328303462861], [30793, 6.444183430673643], [30807, 5.957139753154352], [30821, 6.828501779434161], [30835, 6.624693030116392], [30849, 6.613098760933707], [30863, 7.174433023486831], [30877, 6.54668948989225], [30891, 6.48927475966895], [30905, 6.5385367048554], [30919, 6.222891236942136], [30933, 6.856147639862451], [30947, 6.431684720351901], [30961, 6.5346491426474005], [30975, 6.6695605146557835], [30989, 6.433518401797465], [31003, 6.237192603308961], [31017, 7.065761649454286], [31031, 6.661432059202994], [31045, 6.522195406180468], [32095, 5.967235618288347], [32109, 6.421659450492161], [32123, 6.25691502817487], [32137, 6.471737965812906], [32151, 6.14286813302754], [32165, 6.4159094535152335], [32179, 6.137136405529396], [32193, 6.121999669422391], [32207, 6.196098232453296], [32221, 6.193656563920676], [32235, 6.339392922279157], [32249, 5.953563401483854], [32263, 6.509584554562233], [32277, 6.3501945298500075], [32305, 6.3491439319483485], [32319, 6.314348287792778], [32333, 6.591864801295297], [32347, 6.679553516999191], [32361, 6.445633241625595], [32375, 6.205612719702542], [32389, 6.764867830529715], [32403, 6.401188938577197], [32417, 6.615983775131512], [32431, 6.266892306368067], [32445, 6.687414504541441], [32585, 6.358893158284371], [32599, 6.450353950941284], [32613, 6.352619829469215], [32627, 6.25661494723137], [32641, 6.418673571411627], [32655, 6.378371979255107], [32851, 5.82302236875248], [32865, 6.141059972005534], [32879, 5.897862446958015], [32893, 5.93943810935537], [32907, 6.837020004810673], [32921, 5.972723738841347], [32991, 6.041460403146379], [33005, 5.814708129761285], [33019, 6.10296902550315], [33033, 5.748305160328952], [33047, 5.627230881578814], [33061, 5.833793308465005], [33075, 5.797970617214275], [33089, 5.852632528778936], [33103, 5.914090129579821], [33117, 5.985516814412298], [33131, 5.699641239305719], [33145, 6.253484413398432], [33159, 5.578085814561098], [33187, 5.748114198069662], [33201, 5.981046250979453], [33215, 5.913798200556115], [33229, 5.474720616467511], [33243, 5.422856624624424], [33271, 4.8674054385704215], [33299, 7.297430288714451], [33313, 5.088301753394458], [33327, 5.138197838621745], [33341, 5.178910602797847], [33355, 5.533513421960412], [33369, 4.910760248728118], [33383, 4.90319163260344], [33397, 4.853334901657242], [33411, 4.781157291472394], [33425, 4.784586854826751], [33439, 4.671758410167287], [33453, 4.694603682748759], [33467, 4.64544149021348], [33523, 4.614550858948505], [33537, 4.773789199244022], [33551, 4.94752241207121], [33649, 5.157504503895991], [33705, 4.689210001170598], [33719, 5.407204760293551], [33733, 5.248385780891517], [33747, 4.835527650838202], [33761, 4.902112414122871], [33775, 4.805359059610634], [33803, 4.726475692269859], [33817, 4.687053981857693], [33831, 4.8440217217216], [33845, 4.884601134455797], [34041, 4.936534497296167], [34055, 5.070854530562401], [34069, 4.9262156547508305], [34083, 4.9399815581392], [34125, 4.588771210759588], [34139, 4.799529461552558], [34153, 4.54305913754263], [34167, 4.605854382911351]] \ No newline at end of file diff --git a/graphs/summary/manifold.TSNEBenchmark.track_test_score.json b/graphs/summary/manifold.TSNEBenchmark.track_test_score.json index bf2f94ac5a..5c05933818 100644 --- a/graphs/summary/manifold.TSNEBenchmark.track_test_score.json +++ b/graphs/summary/manifold.TSNEBenchmark.track_test_score.json @@ -1 +1 @@ -[[28511, 0.4843944130401759], [29225, 0.4861091162704062], [29239, 0.48610910009599306], [29253, 0.48610910279172853], [29267, 0.4861091061613979], [29281, 0.4861091162704061], [29295, 0.4861090960523897], [29309, 0.4861091162704061], [29323, 0.4861090960523897], [29337, 0.4861090960523897], [29351, 0.48610908931305064], [29365, 0.4861090960523897], [29379, 0.4861091061613979], [29393, 0.48610910279172853], [29407, 0.4861091061613979], [29421, 0.4861090909978854], [29435, 0.48610910279172853], [29449, 0.4861090893130508], [29463, 0.486109100095993], [29477, 0.48610909605238983], [29547, 0.48610909605238983], [29561, 0.4861091095310674], [29575, 0.48610909605238983], [29603, 0.486109106161398], [29617, 0.486109106161398], [29631, 0.4861091162704062], [29645, 0.48610909605238983], [29659, 0.486109101106894], [29673, 0.48610910279172836], [29743, 0.486109106161398], [29757, 0.48610909605238983], [29771, 0.48610910009599306], [29785, 0.486109106161398], [29799, 0.48610910009599306], [29813, 0.486109101106894], [29827, 0.486109106161398], [29841, 0.486109106161398], [29855, 0.48610909605238983], [29869, 0.4861090960523894], [30009, 0.4861090960523894], [30023, 0.486109106161398], [30037, 0.48610910279172864], [30051, 0.48610909605238983], [30065, 0.4861091162704062], [30079, 0.4861090960523898], [30093, 0.4861090859433812], [30107, 0.48610910279172864], [30121, 0.48610910279172864], [30135, 0.48610909605238983], [30149, 0.48610909605238983], [30163, 0.48610910279172864], [30177, 0.486109106161398], [30191, 0.48610911121590206], [30205, 0.4861090960523895], [30219, 0.4861091041395964], [30233, 0.48610909605238983], [30247, 0.486109101106894], [30261, 0.48610909605238983], [30513, 0.48610910009599306], [30527, 0.48610909605238983], [30541, 0.4861091095310674], [30555, 0.4861090994220591], [30569, 0.4861090909978856], [30583, 0.486109106161398], [30597, 0.4861090859433812], [30625, 0.48610910279172864], [30639, 0.48610909605238983], [30653, 0.48610910279172864], [30667, 0.486109106161398], [30681, 0.4861091095310674], [30695, 0.48610909605238983], [30709, 0.486109106161398], [30723, 0.4861091162704062], [30737, 0.48610909605238983], [30751, 0.486109101106894], [30765, 0.4861090893130508], [30779, 0.4861091162704062], [30793, 0.4861090893130508], [30807, 0.486109106161398], [30821, 0.4861090960523894], [30835, 0.4861091162704062], [30849, 0.48610909605238983], [30863, 0.48610909605238983], [30877, 0.4861090859433812], [30891, 0.48610909605238983], [30905, 0.48610909605238983], [30919, 0.4861090960523895], [30933, 0.48610909605238983], [30947, 0.4861091162704062], [30961, 0.48610910279172864], [30975, 0.486109106161398], [30989, 0.48610910279172864], [31003, 0.48610909605238983], [31017, 0.4861091162704062], [31031, 0.48610909605238983], [31045, 0.4861090859433812], [32095, 0.4864554690211633], [32109, 0.48427963341262315], [32123, 0.48427964336586937], [32137, 0.4842796300948744], [32151, 0.48427964336586937], [32165, 0.48427963838924626], [32179, 0.48427964336586937], [32193, 0.4842796367303719], [32207, 0.48427961350613014], [32221, 0.48427964336586937], [32235, 0.48427964336586937], [32249, 0.48427964336586937], [32263, 0.48427963938457086], [32277, 0.4842796367303719], [32305, 0.48427964336586937], [32319, 0.48427964336586937], [32333, 0.48427964336586937], [32347, 0.484279608529507], [32361, 0.48427963838924626], [32375, 0.48427960355288374], [32389, 0.48427964336586937], [32403, 0.48427960355288374], [32417, 0.4842796367303719], [32431, 0.48427964336586937], [32445, 0.4842796234593769], [32585, 0.48427964336586937], [32599, 0.48427964336586937], [32613, 0.4842796367303719], [32627, 0.48427964336586937], [32641, 0.48427964336586937], [32655, 0.4842796300948742], [32851, 0.48427964336586937], [32865, 0.48427964336586937], [32879, 0.48427964336586937], [32893, 0.48427964336586937], [32907, 0.48427964336586937], [32921, 0.48427964336586937], [32991, 0.48427960355288374], [33005, 0.48427960355288374], [33019, 0.4842796234593769], [33033, 0.48427963341262315], [33047, 0.48427964336586937], [33061, 0.4842796234593766], [33075, 0.48427964336586937], [33089, 0.48427963341262315], [33103, 0.4842796300948744], [33117, 0.48427964336586937], [33131, 0.4842796234593766], [33145, 0.48427964336586937], [33159, 0.48427964336586937], [33187, 0.4842796234593769], [33201, 0.48427961350613036], [33215, 0.4840919528757295], [33229, 0.4835289610312804], [33243, 0.4835289610312804], [33271, 0.48277944233009035], [33299, 0.48277944233009035], [33313, 0.48277945226510893], [33327, 0.48277945226510893], [33341, 0.48308359549685587], [33355, 0.48399605504527843], [33369, 0.48399605504527843], [33383, 0.48399606168466586], [33397, 0.4839960351271153], [33411, 0.48399607496344066], [33425, 0.48399606500435954], [33439, 0.48399605504527843], [33453, 0.48399605504527843], [33467, 0.4839960351271153], [33523, 0.4839960550452782], [33537, 0.48399606168466586], [33551, 0.48399605504527843], [33649, 0.48396733220246757], [33705, 0.48396733220246757], [33719, 0.48396732722263125], [33733, 0.4828452088058599], [33747, 0.48284519887221533], [33761, 0.4828452088058599], [33775, 0.48284518893857076], [33803, 0.4828452088058599], [33817, 0.48284519887221533], [33831, 0.4828451955610005], [33845, 0.48284518893857076], [34041, 0.48284519887221533], [34055, 0.4828452021834302], [34069, 0.4828452021834302], [34083, 0.48284519887221533], [34125, 0.4828452088058599], [34139, 0.48284518893857076], [34153, 0.4828452021834302], [34167, 0.4828452088058597]] \ No newline at end of file +[[28511, 0.4843944130401759], [29225, 0.4861091162704062], [29239, 0.48610910009599306], [29253, 0.48610910279172853], [29267, 0.4861091061613979], [29281, 0.4861091162704061], [29295, 0.4861090960523897], [29309, 0.4861091162704061], [29323, 0.4861090960523897], [29337, 0.4861090960523897], [29351, 0.48610908931305064], [29365, 0.4861090960523897], [29379, 0.4861091061613979], [29393, 0.48610910279172853], [29407, 0.4861091061613979], [29421, 0.4861090909978854], [29435, 0.48610910279172853], [29449, 0.4861090893130508], [29463, 0.486109100095993], [29477, 0.48610909605238983], [29547, 0.48610909605238983], [29561, 0.4861091095310674], [29575, 0.48610909605238983], [29603, 0.486109106161398], [29617, 0.486109106161398], [29631, 0.4861091162704062], [29645, 0.48610909605238983], [29659, 0.486109101106894], [29673, 0.48610910279172836], [29743, 0.486109106161398], [29757, 0.48610909605238983], [29771, 0.48610910009599306], [29785, 0.486109106161398], [29799, 0.48610910009599306], [29813, 0.486109101106894], [29827, 0.486109106161398], [29841, 0.486109106161398], [29855, 0.48610909605238983], [29869, 0.4861090960523894], [30009, 0.4861090960523894], [30023, 0.486109106161398], [30037, 0.48610910279172864], [30051, 0.48610909605238983], [30065, 0.4861091162704062], [30079, 0.4861090960523898], [30093, 0.4861090859433812], [30107, 0.48610910279172864], [30121, 0.48610910279172864], [30135, 0.48610909605238983], [30149, 0.48610909605238983], [30163, 0.48610910279172864], [30177, 0.486109106161398], [30191, 0.48610911121590206], [30205, 0.4861090960523895], [30219, 0.4861091041395964], [30233, 0.48610909605238983], [30247, 0.486109101106894], [30261, 0.48610909605238983], [30513, 0.48610910009599306], [30527, 0.48610909605238983], [30541, 0.4861091095310674], [30555, 0.4861090994220591], [30569, 0.4861090909978856], [30583, 0.486109106161398], [30597, 0.4861090859433812], [30625, 0.48610910279172864], [30639, 0.48610909605238983], [30653, 0.48610910279172864], [30667, 0.486109106161398], [30681, 0.4861091095310674], [30695, 0.48610909605238983], [30709, 0.486109106161398], [30723, 0.4861091162704062], [30737, 0.48610909605238983], [30751, 0.486109101106894], [30765, 0.4861090893130508], [30779, 0.4861091162704062], [30793, 0.4861090893130508], [30807, 0.486109106161398], [30821, 0.4861090960523894], [30835, 0.4861091162704062], [30849, 0.48610909605238983], [30863, 0.48610909605238983], [30877, 0.4861090859433812], [30891, 0.48610909605238983], [30905, 0.48610909605238983], [30919, 0.4861090960523895], [30933, 0.48610909605238983], [30947, 0.4861091162704062], [30961, 0.48610910279172864], [30975, 0.486109106161398], [30989, 0.48610910279172864], [31003, 0.48610909605238983], [31017, 0.4861091162704062], [31031, 0.48610909605238983], [31045, 0.4861090859433812], [32095, 0.4864554690211633], [32109, 0.48427963341262315], [32123, 0.48427964336586937], [32137, 0.4842796300948744], [32151, 0.48427964336586937], [32165, 0.48427963838924626], [32179, 0.48427964336586937], [32193, 0.4842796367303719], [32207, 0.48427961350613014], [32221, 0.48427964336586937], [32235, 0.48427964336586937], [32249, 0.48427964336586937], [32263, 0.48427963938457086], [32277, 0.4842796367303719], [32305, 0.48427964336586937], [32319, 0.48427964336586937], [32333, 0.48427964336586937], [32347, 0.484279608529507], [32361, 0.48427963838924626], [32375, 0.48427960355288374], [32389, 0.48427964336586937], [32403, 0.48427960355288374], [32417, 0.4842796367303719], [32431, 0.48427964336586937], [32445, 0.4842796234593769], [32585, 0.48427964336586937], [32599, 0.48427964336586937], [32613, 0.4842796367303719], [32627, 0.48427964336586937], [32641, 0.48427964336586937], [32655, 0.4842796300948742], [32851, 0.48427964336586937], [32865, 0.48427964336586937], [32879, 0.48427964336586937], [32893, 0.48427964336586937], [32907, 0.48427964336586937], [32921, 0.48427964336586937], [32991, 0.48427960355288374], [33005, 0.48427960355288374], [33019, 0.4842796234593769], [33033, 0.48427963341262315], [33047, 0.48427964336586937], [33061, 0.4842796234593766], [33075, 0.48427964336586937], [33089, 0.48427963341262315], [33103, 0.4842796300948744], [33117, 0.48427964336586937], [33131, 0.4842796234593766], [33145, 0.48427964336586937], [33159, 0.48427964336586937], [33187, 0.4842796234593769], [33201, 0.48427961350613036], [33215, 0.4840919528757295], [33229, 0.4835289610312804], [33243, 0.4835289610312804], [33271, 0.48277944233009035], [33299, 0.48277944233009035], [33313, 0.48277945226510893], [33327, 0.48277945226510893], [33341, 0.48308359549685587], [33355, 0.48399605504527843], [33369, 0.48399605504527843], [33383, 0.48399606168466586], [33397, 0.4839960351271153], [33411, 0.48399607496344066], [33425, 0.48399606500435954], [33439, 0.48399605504527843], [33453, 0.48399605504527843], [33467, 0.4839960351271153], [33523, 0.4839960550452782], [33537, 0.48399606168466586], [33551, 0.48399605504527843], [33649, 0.48396733220246757], [33705, 0.48396733220246757], [33719, 0.48396732722263125], [33733, 0.4828452088058599], [33747, 0.48284519887221533], [33761, 0.4828452088058599], [33775, 0.48284518893857076], [33803, 0.4828452088058599], [33817, 0.48284519887221533], [33831, 0.4828451955610005], [33845, 0.48284518893857076], [34041, 0.48284519887221533], [34055, 0.4828452021834302], [34069, 0.4828452021834302], [34083, 0.48284519887221533], [34125, 0.4828452088058599], [34139, 0.48284518893857076], [34153, 0.4828452021834302], [34167, 0.48284521277931736]] \ No newline at end of file diff --git a/graphs/summary/manifold.TSNEBenchmark.track_train_score.json b/graphs/summary/manifold.TSNEBenchmark.track_train_score.json index bf2f94ac5a..5c05933818 100644 --- a/graphs/summary/manifold.TSNEBenchmark.track_train_score.json +++ b/graphs/summary/manifold.TSNEBenchmark.track_train_score.json @@ -1 +1 @@ -[[28511, 0.4843944130401759], [29225, 0.4861091162704062], [29239, 0.48610910009599306], [29253, 0.48610910279172853], [29267, 0.4861091061613979], [29281, 0.4861091162704061], [29295, 0.4861090960523897], [29309, 0.4861091162704061], [29323, 0.4861090960523897], [29337, 0.4861090960523897], [29351, 0.48610908931305064], [29365, 0.4861090960523897], [29379, 0.4861091061613979], [29393, 0.48610910279172853], [29407, 0.4861091061613979], [29421, 0.4861090909978854], [29435, 0.48610910279172853], [29449, 0.4861090893130508], [29463, 0.486109100095993], [29477, 0.48610909605238983], [29547, 0.48610909605238983], [29561, 0.4861091095310674], [29575, 0.48610909605238983], [29603, 0.486109106161398], [29617, 0.486109106161398], [29631, 0.4861091162704062], [29645, 0.48610909605238983], [29659, 0.486109101106894], [29673, 0.48610910279172836], [29743, 0.486109106161398], [29757, 0.48610909605238983], [29771, 0.48610910009599306], [29785, 0.486109106161398], [29799, 0.48610910009599306], [29813, 0.486109101106894], [29827, 0.486109106161398], [29841, 0.486109106161398], [29855, 0.48610909605238983], [29869, 0.4861090960523894], [30009, 0.4861090960523894], [30023, 0.486109106161398], [30037, 0.48610910279172864], [30051, 0.48610909605238983], [30065, 0.4861091162704062], [30079, 0.4861090960523898], [30093, 0.4861090859433812], [30107, 0.48610910279172864], [30121, 0.48610910279172864], [30135, 0.48610909605238983], [30149, 0.48610909605238983], [30163, 0.48610910279172864], [30177, 0.486109106161398], [30191, 0.48610911121590206], [30205, 0.4861090960523895], [30219, 0.4861091041395964], [30233, 0.48610909605238983], [30247, 0.486109101106894], [30261, 0.48610909605238983], [30513, 0.48610910009599306], [30527, 0.48610909605238983], [30541, 0.4861091095310674], [30555, 0.4861090994220591], [30569, 0.4861090909978856], [30583, 0.486109106161398], [30597, 0.4861090859433812], [30625, 0.48610910279172864], [30639, 0.48610909605238983], [30653, 0.48610910279172864], [30667, 0.486109106161398], [30681, 0.4861091095310674], [30695, 0.48610909605238983], [30709, 0.486109106161398], [30723, 0.4861091162704062], [30737, 0.48610909605238983], [30751, 0.486109101106894], [30765, 0.4861090893130508], [30779, 0.4861091162704062], [30793, 0.4861090893130508], [30807, 0.486109106161398], [30821, 0.4861090960523894], [30835, 0.4861091162704062], [30849, 0.48610909605238983], [30863, 0.48610909605238983], [30877, 0.4861090859433812], [30891, 0.48610909605238983], [30905, 0.48610909605238983], [30919, 0.4861090960523895], [30933, 0.48610909605238983], [30947, 0.4861091162704062], [30961, 0.48610910279172864], [30975, 0.486109106161398], [30989, 0.48610910279172864], [31003, 0.48610909605238983], [31017, 0.4861091162704062], [31031, 0.48610909605238983], [31045, 0.4861090859433812], [32095, 0.4864554690211633], [32109, 0.48427963341262315], [32123, 0.48427964336586937], [32137, 0.4842796300948744], [32151, 0.48427964336586937], [32165, 0.48427963838924626], [32179, 0.48427964336586937], [32193, 0.4842796367303719], [32207, 0.48427961350613014], [32221, 0.48427964336586937], [32235, 0.48427964336586937], [32249, 0.48427964336586937], [32263, 0.48427963938457086], [32277, 0.4842796367303719], [32305, 0.48427964336586937], [32319, 0.48427964336586937], [32333, 0.48427964336586937], [32347, 0.484279608529507], [32361, 0.48427963838924626], [32375, 0.48427960355288374], [32389, 0.48427964336586937], [32403, 0.48427960355288374], [32417, 0.4842796367303719], [32431, 0.48427964336586937], [32445, 0.4842796234593769], [32585, 0.48427964336586937], [32599, 0.48427964336586937], [32613, 0.4842796367303719], [32627, 0.48427964336586937], [32641, 0.48427964336586937], [32655, 0.4842796300948742], [32851, 0.48427964336586937], [32865, 0.48427964336586937], [32879, 0.48427964336586937], [32893, 0.48427964336586937], [32907, 0.48427964336586937], [32921, 0.48427964336586937], [32991, 0.48427960355288374], [33005, 0.48427960355288374], [33019, 0.4842796234593769], [33033, 0.48427963341262315], [33047, 0.48427964336586937], [33061, 0.4842796234593766], [33075, 0.48427964336586937], [33089, 0.48427963341262315], [33103, 0.4842796300948744], [33117, 0.48427964336586937], [33131, 0.4842796234593766], [33145, 0.48427964336586937], [33159, 0.48427964336586937], [33187, 0.4842796234593769], [33201, 0.48427961350613036], [33215, 0.4840919528757295], [33229, 0.4835289610312804], [33243, 0.4835289610312804], [33271, 0.48277944233009035], [33299, 0.48277944233009035], [33313, 0.48277945226510893], [33327, 0.48277945226510893], [33341, 0.48308359549685587], [33355, 0.48399605504527843], [33369, 0.48399605504527843], [33383, 0.48399606168466586], [33397, 0.4839960351271153], [33411, 0.48399607496344066], [33425, 0.48399606500435954], [33439, 0.48399605504527843], [33453, 0.48399605504527843], [33467, 0.4839960351271153], [33523, 0.4839960550452782], [33537, 0.48399606168466586], [33551, 0.48399605504527843], [33649, 0.48396733220246757], [33705, 0.48396733220246757], [33719, 0.48396732722263125], [33733, 0.4828452088058599], [33747, 0.48284519887221533], [33761, 0.4828452088058599], [33775, 0.48284518893857076], [33803, 0.4828452088058599], [33817, 0.48284519887221533], [33831, 0.4828451955610005], [33845, 0.48284518893857076], [34041, 0.48284519887221533], [34055, 0.4828452021834302], [34069, 0.4828452021834302], [34083, 0.48284519887221533], [34125, 0.4828452088058599], [34139, 0.48284518893857076], [34153, 0.4828452021834302], [34167, 0.4828452088058597]] \ No newline at end of file +[[28511, 0.4843944130401759], [29225, 0.4861091162704062], [29239, 0.48610910009599306], [29253, 0.48610910279172853], [29267, 0.4861091061613979], [29281, 0.4861091162704061], [29295, 0.4861090960523897], [29309, 0.4861091162704061], [29323, 0.4861090960523897], [29337, 0.4861090960523897], [29351, 0.48610908931305064], [29365, 0.4861090960523897], [29379, 0.4861091061613979], [29393, 0.48610910279172853], [29407, 0.4861091061613979], [29421, 0.4861090909978854], [29435, 0.48610910279172853], [29449, 0.4861090893130508], [29463, 0.486109100095993], [29477, 0.48610909605238983], [29547, 0.48610909605238983], [29561, 0.4861091095310674], [29575, 0.48610909605238983], [29603, 0.486109106161398], [29617, 0.486109106161398], [29631, 0.4861091162704062], [29645, 0.48610909605238983], [29659, 0.486109101106894], [29673, 0.48610910279172836], [29743, 0.486109106161398], [29757, 0.48610909605238983], [29771, 0.48610910009599306], [29785, 0.486109106161398], [29799, 0.48610910009599306], [29813, 0.486109101106894], [29827, 0.486109106161398], [29841, 0.486109106161398], [29855, 0.48610909605238983], [29869, 0.4861090960523894], [30009, 0.4861090960523894], [30023, 0.486109106161398], [30037, 0.48610910279172864], [30051, 0.48610909605238983], [30065, 0.4861091162704062], [30079, 0.4861090960523898], [30093, 0.4861090859433812], [30107, 0.48610910279172864], [30121, 0.48610910279172864], [30135, 0.48610909605238983], [30149, 0.48610909605238983], [30163, 0.48610910279172864], [30177, 0.486109106161398], [30191, 0.48610911121590206], [30205, 0.4861090960523895], [30219, 0.4861091041395964], [30233, 0.48610909605238983], [30247, 0.486109101106894], [30261, 0.48610909605238983], [30513, 0.48610910009599306], [30527, 0.48610909605238983], [30541, 0.4861091095310674], [30555, 0.4861090994220591], [30569, 0.4861090909978856], [30583, 0.486109106161398], [30597, 0.4861090859433812], [30625, 0.48610910279172864], [30639, 0.48610909605238983], [30653, 0.48610910279172864], [30667, 0.486109106161398], [30681, 0.4861091095310674], [30695, 0.48610909605238983], [30709, 0.486109106161398], [30723, 0.4861091162704062], [30737, 0.48610909605238983], [30751, 0.486109101106894], [30765, 0.4861090893130508], [30779, 0.4861091162704062], [30793, 0.4861090893130508], [30807, 0.486109106161398], [30821, 0.4861090960523894], [30835, 0.4861091162704062], [30849, 0.48610909605238983], [30863, 0.48610909605238983], [30877, 0.4861090859433812], [30891, 0.48610909605238983], [30905, 0.48610909605238983], [30919, 0.4861090960523895], [30933, 0.48610909605238983], [30947, 0.4861091162704062], [30961, 0.48610910279172864], [30975, 0.486109106161398], [30989, 0.48610910279172864], [31003, 0.48610909605238983], [31017, 0.4861091162704062], [31031, 0.48610909605238983], [31045, 0.4861090859433812], [32095, 0.4864554690211633], [32109, 0.48427963341262315], [32123, 0.48427964336586937], [32137, 0.4842796300948744], [32151, 0.48427964336586937], [32165, 0.48427963838924626], [32179, 0.48427964336586937], [32193, 0.4842796367303719], [32207, 0.48427961350613014], [32221, 0.48427964336586937], [32235, 0.48427964336586937], [32249, 0.48427964336586937], [32263, 0.48427963938457086], [32277, 0.4842796367303719], [32305, 0.48427964336586937], [32319, 0.48427964336586937], [32333, 0.48427964336586937], [32347, 0.484279608529507], [32361, 0.48427963838924626], [32375, 0.48427960355288374], [32389, 0.48427964336586937], [32403, 0.48427960355288374], [32417, 0.4842796367303719], [32431, 0.48427964336586937], [32445, 0.4842796234593769], [32585, 0.48427964336586937], [32599, 0.48427964336586937], [32613, 0.4842796367303719], [32627, 0.48427964336586937], [32641, 0.48427964336586937], [32655, 0.4842796300948742], [32851, 0.48427964336586937], [32865, 0.48427964336586937], [32879, 0.48427964336586937], [32893, 0.48427964336586937], [32907, 0.48427964336586937], [32921, 0.48427964336586937], [32991, 0.48427960355288374], [33005, 0.48427960355288374], [33019, 0.4842796234593769], [33033, 0.48427963341262315], [33047, 0.48427964336586937], [33061, 0.4842796234593766], [33075, 0.48427964336586937], [33089, 0.48427963341262315], [33103, 0.4842796300948744], [33117, 0.48427964336586937], [33131, 0.4842796234593766], [33145, 0.48427964336586937], [33159, 0.48427964336586937], [33187, 0.4842796234593769], [33201, 0.48427961350613036], [33215, 0.4840919528757295], [33229, 0.4835289610312804], [33243, 0.4835289610312804], [33271, 0.48277944233009035], [33299, 0.48277944233009035], [33313, 0.48277945226510893], [33327, 0.48277945226510893], [33341, 0.48308359549685587], [33355, 0.48399605504527843], [33369, 0.48399605504527843], [33383, 0.48399606168466586], [33397, 0.4839960351271153], [33411, 0.48399607496344066], [33425, 0.48399606500435954], [33439, 0.48399605504527843], [33453, 0.48399605504527843], [33467, 0.4839960351271153], [33523, 0.4839960550452782], [33537, 0.48399606168466586], [33551, 0.48399605504527843], [33649, 0.48396733220246757], [33705, 0.48396733220246757], [33719, 0.48396732722263125], [33733, 0.4828452088058599], [33747, 0.48284519887221533], [33761, 0.4828452088058599], [33775, 0.48284518893857076], [33803, 0.4828452088058599], [33817, 0.48284519887221533], [33831, 0.4828451955610005], [33845, 0.48284518893857076], [34041, 0.48284519887221533], [34055, 0.4828452021834302], [34069, 0.4828452021834302], [34083, 0.48284519887221533], [34125, 0.4828452088058599], [34139, 0.48284518893857076], [34153, 0.4828452021834302], [34167, 0.48284521277931736]] \ No newline at end of file diff --git a/graphs/summary/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json b/graphs/summary/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json index f12dbd3121..1ebbf8d304 100644 --- a/graphs/summary/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json +++ b/graphs/summary/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json @@ -1 +1 @@ -[[28511, 534805124.2871156], [29225, 519169180.2863241], [29239, 525866104.0483775], [29253, 531466348.99949265], [29267, 536407766.70562565], [29281, 527767695.97886723], [29295, 529689801.30467767], [29309, 535597543.640881], [29323, 531230022.10425764], [29337, 525005504.66890603], [29351, 531555778.17268676], [29365, 530956894.6900093], [29379, 524600494.84898084], [29393, 536667071.70762414], [29407, 524644795.6241084], [29421, 533197237.6176509], [29435, 530011001.15429896], [29449, 523239481.6074681], [29463, 533610101.06855184], [29477, 528910415.2150152], [29547, 522164906.81769085], [29561, 536662144.13421726], [29575, 534385144.89358413], [29603, 539068141.7918619], [29617, 536102086.1564877], [29631, 539591906.3686812], [29645, 541789771.710632], [29659, 539456492.7279376], [29673, 543024224.2176133], [29743, 537903927.3167343], [29757, 542473528.0013175], [29771, 541205504.4625094], [29785, 528482660.550007], [29799, 535164053.0686137], [29813, 534620013.50340396], [29827, 533446408.04976183], [29841, 532259597.78635097], [29855, 534886012.84031254], [29869, 530639423.20223784], [30009, 531052632.00909746], [30023, 537997209.1462624], [30037, 537737876.1833385], [30051, 520704212.8922722], [30065, 538904411.0425974], [30079, 530678469.9603201], [30093, 535777099.25849134], [30107, 537361002.7158152], [30121, 531625075.56460667], [30135, 531705490.2730778], [30149, 528583941.08972085], [30163, 529458844.5663479], [30177, 530023180.6015725], [30191, 527259551.18176085], [30205, 531448693.841801], [30219, 533751377.4560237], [30233, 527856798.9231366], [30247, 530480508.8120515], [30261, 527769122.1453454], [30513, 535914080.216457], [30527, 526783470.7002738], [30541, 530687340.9080799], [30555, 531511817.1075661], [30569, 530324304.2898208], [30583, 531612574.88310057], [30597, 534097734.183866], [30625, 528037510.9071744], [30639, 532428601.7344182], [30653, 530513428.56194305], [30667, 538799111.2621957], [30681, 526786558.2760212], [30695, 527054212.4193215], [30709, 530599279.5248418], [30723, 531066000.4252934], [30737, 532639659.6648406], [30751, 535897757.1700534], [30765, 535061499.0749874], [30779, 539794603.9786421], [30793, 532531555.1068502], [30807, 533903167.73500204], [30821, 538678470.0907494], [30835, 528670128.1033404], [30849, 540921910.0790534], [30863, 533364011.18571585], [30877, 532136345.49577975], [30891, 535948593.06313497], [30905, 531887553.20082736], [30919, 528477646.5468586], [30933, 533813736.09616095], [30947, 526917141.6251385], [30961, 531469556.4893405], [30975, 536074609.0909621], [30989, 528734990.7882368], [31003, 533639968.4803101], [31017, 536094079.6634572], [31031, 528307981.035342], [31045, 532306053.32243216], [32095, 556470190.6937642], [32109, 550973044.7305622], [32123, 557241726.501437], [32137, 559709758.0287229], [32151, 559606428.9511005], [32165, 555090735.4332492], [32179, 563360800.3959386], [32193, 557362223.9299954], [32207, 557949161.6545774], [32221, 560557614.2799039], [32235, 553362810.7404605], [32249, 564135937.7151778], [32263, 553364522.8994482], [32277, 554648418.5611149], [32305, 556410842.1391969], [32319, 559386625.0807236], [32333, 551659941.2464823], [32347, 553771705.6895287], [32361, 560301025.7673316], [32375, 556430417.8878601], [32389, 554069033.6131538], [32403, 560948535.4555113], [32417, 554071898.5513455], [32431, 560585129.4636375], [32445, 564936630.7351999], [32585, 564449563.7315292], [32599, 555427388.0169452], [32613, 563430337.4624628], [32627, 556320286.71792], [32641, 550261068.5778444], [32655, 557739320.5472997], [32851, 563662620.9412107], [32865, 562238587.4499944], [32879, 565835338.6990641], [32893, 564026726.3971914], [32907, 560179007.0208036], [32921, 563565998.8395023], [32991, 559496875.2990494], [33005, 560757444.918234], [33019, 559345496.1822428], [33033, 563477720.0493603], [33047, 562193983.4974859], [33061, 565740135.2295156], [33075, 561261269.3302096], [33089, 577701461.0530447], [33103, 590223011.2229019], [33117, 593752423.4919816], [33131, 586950849.4160788], [33145, 590566834.0332495], [33159, 597140058.2536051], [33187, 567234435.7554508], [33201, 562609579.8517959], [33215, 558339193.0166472], [33229, 549679125.001198], [33243, 551294023.1136651], [33271, 535635321.01279825], [33299, 529316563.4933346], [33313, 540590399.4181929], [33327, 547219212.7892077], [33341, 541442343.7602106], [33355, 535208356.4146424], [33369, 545718341.6037747], [33383, 546976400.1805567], [33397, 541009068.6189926], [33411, 543395434.0684259], [33425, 533114123.0807047], [33439, 546840713.3710328], [33453, 538251489.3075095], [33467, 538238995.2728465], [33523, 539434794.0823911], [33537, 537096846.5093502], [33551, 535486939.20782214], [33649, 531472398.7603052], [33705, 531809436.63577926], [33719, 536945408.2149438], [33733, 542694729.0454292], [33747, 533126060.6690197], [33761, 533029898.8861707], [33775, 545090354.8553281], [33803, 535308535.1769645], [33817, 543498299.0274534], [33831, 539819827.8792509], [33845, 541476573.5843966], [34041, 532933564.1475505], [34055, 533709683.6688929], [34069, 540367294.3169155], [34083, 531665847.1295068], [34125, 532888181.41084146], [34139, 546052287.1778744], [34153, 538677595.3780216], [34167, 543227077.3607359]] \ No newline at end of file +[[28511, 534805124.2871156], [29225, 519169180.2863241], [29239, 525866104.0483775], [29253, 531466348.99949265], [29267, 536407766.70562565], [29281, 527767695.97886723], [29295, 529689801.30467767], [29309, 535597543.640881], [29323, 531230022.10425764], [29337, 525005504.66890603], [29351, 531555778.17268676], [29365, 530956894.6900093], [29379, 524600494.84898084], [29393, 536667071.70762414], [29407, 524644795.6241084], [29421, 533197237.6176509], [29435, 530011001.15429896], [29449, 523239481.6074681], [29463, 533610101.06855184], [29477, 528910415.2150152], [29547, 522164906.81769085], [29561, 536662144.13421726], [29575, 534385144.89358413], [29603, 539068141.7918619], [29617, 536102086.1564877], [29631, 539591906.3686812], [29645, 541789771.710632], [29659, 539456492.7279376], [29673, 543024224.2176133], [29743, 537903927.3167343], [29757, 542473528.0013175], [29771, 541205504.4625094], [29785, 528482660.550007], [29799, 535164053.0686137], [29813, 534620013.50340396], [29827, 533446408.04976183], [29841, 532259597.78635097], [29855, 534886012.84031254], [29869, 530639423.20223784], [30009, 531052632.00909746], [30023, 537997209.1462624], [30037, 537737876.1833385], [30051, 520704212.8922722], [30065, 538904411.0425974], [30079, 530678469.9603201], [30093, 535777099.25849134], [30107, 537361002.7158152], [30121, 531625075.56460667], [30135, 531705490.2730778], [30149, 528583941.08972085], [30163, 529458844.5663479], [30177, 530023180.6015725], [30191, 527259551.18176085], [30205, 531448693.841801], [30219, 533751377.4560237], [30233, 527856798.9231366], [30247, 530480508.8120515], [30261, 527769122.1453454], [30513, 535914080.216457], [30527, 526783470.7002738], [30541, 530687340.9080799], [30555, 531511817.1075661], [30569, 530324304.2898208], [30583, 531612574.88310057], [30597, 534097734.183866], [30625, 528037510.9071744], [30639, 532428601.7344182], [30653, 530513428.56194305], [30667, 538799111.2621957], [30681, 526786558.2760212], [30695, 527054212.4193215], [30709, 530599279.5248418], [30723, 531066000.4252934], [30737, 532639659.6648406], [30751, 535897757.1700534], [30765, 535061499.0749874], [30779, 539794603.9786421], [30793, 532531555.1068502], [30807, 533903167.73500204], [30821, 538678470.0907494], [30835, 528670128.1033404], [30849, 540921910.0790534], [30863, 533364011.18571585], [30877, 532136345.49577975], [30891, 535948593.06313497], [30905, 531887553.20082736], [30919, 528477646.5468586], [30933, 533813736.09616095], [30947, 526917141.6251385], [30961, 531469556.4893405], [30975, 536074609.0909621], [30989, 528734990.7882368], [31003, 533639968.4803101], [31017, 536094079.6634572], [31031, 528307981.035342], [31045, 532306053.32243216], [32095, 556470190.6937642], [32109, 550973044.7305622], [32123, 557241726.501437], [32137, 559709758.0287229], [32151, 559606428.9511005], [32165, 555090735.4332492], [32179, 563360800.3959386], [32193, 557362223.9299954], [32207, 557949161.6545774], [32221, 560557614.2799039], [32235, 553362810.7404605], [32249, 564135937.7151778], [32263, 553364522.8994482], [32277, 554648418.5611149], [32305, 556410842.1391969], [32319, 559386625.0807236], [32333, 551659941.2464823], [32347, 553771705.6895287], [32361, 560301025.7673316], [32375, 556430417.8878601], [32389, 554069033.6131538], [32403, 560948535.4555113], [32417, 554071898.5513455], [32431, 560585129.4636375], [32445, 564936630.7351999], [32585, 564449563.7315292], [32599, 555427388.0169452], [32613, 563430337.4624628], [32627, 556320286.71792], [32641, 550261068.5778444], [32655, 557739320.5472997], [32851, 563662620.9412107], [32865, 562238587.4499944], [32879, 565835338.6990641], [32893, 564026726.3971914], [32907, 560179007.0208036], [32921, 563565998.8395023], [32991, 559496875.2990494], [33005, 560757444.918234], [33019, 559345496.1822428], [33033, 563477720.0493603], [33047, 562193983.4974859], [33061, 565740135.2295156], [33075, 561261269.3302096], [33089, 577701461.0530447], [33103, 590223011.2229019], [33117, 593752423.4919816], [33131, 586950849.4160788], [33145, 590566834.0332495], [33159, 597140058.2536051], [33187, 567234435.7554508], [33201, 562609579.8517959], [33215, 558339193.0166472], [33229, 549679125.001198], [33243, 551294023.1136651], [33271, 535635321.01279825], [33299, 529316563.4933346], [33313, 540590399.4181929], [33327, 547219212.7892077], [33341, 541442343.7602106], [33355, 535208356.4146424], [33369, 545718341.6037747], [33383, 546976400.1805567], [33397, 541009068.6189926], [33411, 543395434.0684259], [33425, 533114123.0807047], [33439, 546840713.3710328], [33453, 538251489.3075095], [33467, 538238995.2728465], [33523, 539434794.0823911], [33537, 537096846.5093502], [33551, 535486939.20782214], [33649, 531472398.7603052], [33705, 531809436.63577926], [33719, 536945408.2149438], [33733, 542694729.0454292], [33747, 533126060.6690197], [33761, 533029898.8861707], [33775, 545090354.8553281], [33803, 535308535.1769645], [33817, 543498299.0274534], [33831, 539819827.8792509], [33845, 541476573.5843966], [34041, 532933564.1475505], [34055, 533709683.6688929], [34069, 540367294.3169155], [34083, 531665847.1295068], [34125, 532888181.41084146], [34139, 546052287.1778744], [34153, 538677595.3780216], [34167, 543985091.9253023]] \ No newline at end of file diff --git a/graphs/summary/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json b/graphs/summary/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json index eb1de58113..e05950f0d4 100644 --- a/graphs/summary/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json +++ b/graphs/summary/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json @@ -1 +1 @@ -[[28511, 1.68351744584663], [29225, 2.346582049131427], [29239, 2.2536957476965767], [29253, 1.6585710395236875], [29267, 1.688610289266403], [29281, 1.7284908015588145], [29295, 1.7146283703018204], [29309, 1.7066088350013233], [29323, 1.691064117429641], [29337, 1.7216663648927508], [29351, 1.6839285819571739], [29365, 1.6422740958130089], [29379, 1.6810657419096118], [29393, 1.6606966379227501], [29407, 1.6649481860568014], [29421, 1.6619447448740996], [29435, 1.6421596759494586], [29449, 2.481159115557852], [29463, 2.508024634745909], [29477, 2.5476170990662523], [29547, 2.5334988039600317], [29561, 2.3834230013074396], [29575, 2.181837575295464], [29603, 2.217138328761994], [29617, 2.2250688025886642], [29631, 2.191579051635938], [29645, 2.2055694622872766], [29659, 2.2347681457008908], [29673, 2.2168063556771958], [29743, 2.229086193224686], [29757, 2.234013386772018], [29771, 2.252482807005255], [29785, 2.6053577786303856], [29799, 2.3492975608019444], [29813, 2.336347283075362], [29827, 2.401678397270591], [29841, 2.353910594198157], [29855, 2.3245233880648866], [29869, 2.2918804128781076], [30009, 2.336538178746106], [30023, 2.3589564838128494], [30037, 2.390530455392739], [30051, 2.377795445741982], [30065, 2.425732265820918], [30079, 2.353507932733517], [30093, 2.3542123642425197], [30107, 2.3389842840510346], [30121, 2.394802285393343], [30135, 2.3820148395751044], [30149, 2.3550279340616225], [30163, 2.390470694127003], [30177, 2.3363907523028127], [30191, 2.3003612013061754], [30205, 2.3394303126664675], [30219, 2.363816960525984], [30233, 2.3818313286898127], [30247, 2.3689904263044537], [30261, 2.3759486699297288], [30513, 2.3686680825768462], [30527, 2.3877567777405075], [30541, 2.406202635912726], [30555, 2.3662486352621026], [30569, 2.3676061178988266], [30583, 2.33128248185381], [30597, 2.3408401462398514], [30625, 2.3570418206431056], [30639, 2.328238399812842], [30653, 2.3963259016195724], [30667, 2.3284033542044735], [30681, 2.4005394699628195], [30695, 2.3402926918855997], [30709, 2.411209477612136], [30723, 2.398959590493856], [30737, 2.3649611012666067], [30751, 2.348288517816856], [30765, 2.381140596425348], [30779, 2.341815195921634], [30793, 2.353492775366478], [30807, 2.415413789635259], [30821, 2.365419388658096], [30835, 2.446162721752828], [30849, 2.2910876269709344], [30863, 2.3873148752301585], [30877, 2.3631351583331797], [30891, 2.347497072794629], [30905, 2.2585904431844224], [30919, 2.3552997208969795], [30933, 2.3567665084137017], [30947, 2.3300926474664196], [30961, 2.3673765000004736], [30975, 2.450140604637588], [30989, 2.4391102460178335], [31003, 2.421584851096986], [31017, 2.4437881219960804], [31031, 2.4241368635712166], [31045, 2.4172865765779283], [32095, 2.178598909731901], [32109, 2.216012942075734], [32123, 2.2041774333503628], [32137, 2.2517116650149562], [32151, 2.175217050084551], [32165, 2.22212746033415], [32179, 2.170422422669505], [32193, 2.2125478271695243], [32207, 2.2165278373207635], [32221, 2.2472297651246134], [32235, 2.2593191005615347], [32249, 2.2161220883111747], [32263, 2.2522685400382993], [32277, 2.3116669257726983], [32305, 2.2883851151794072], [32319, 2.2785287045886817], [32333, 2.274760129772384], [32347, 2.349744220369046], [32361, 2.3136569401606377], [32375, 2.2902821595126697], [32389, 2.285164602546379], [32403, 2.2686365149738696], [32417, 2.358684544033008], [32431, 2.279125936150566], [32445, 2.2358126710251396], [32585, 2.2857751682299106], [32599, 2.3823297675194124], [32613, 2.3207109487914606], [32627, 2.3551302264005773], [32641, 2.325078097227779], [32655, 2.3295703794467078], [32851, 2.1716648841947777], [32865, 2.2196950832141438], [32879, 2.1952762308391374], [32893, 2.276537679298381], [32907, 2.395336048843755], [32921, 2.409141052823972], [32991, 2.3605682565809], [33005, 2.4195086069410294], [33019, 2.4021514889714526], [33033, 2.376135714981526], [33047, 2.400022568712412], [33061, 2.3902034293550285], [33075, 2.4302450606653165], [33089, 2.39699563732807], [33103, 2.374204553639372], [33117, 2.426437508178664], [33131, 2.4154540542016356], [33145, 2.4049929622742643], [33159, 2.3707256817441054], [33187, 2.4310852688449947], [33201, 2.3831567648852126], [33215, 2.3681553743068124], [33229, 2.3376719177065395], [33243, 2.3501691902524153], [33271, 2.2588325012050534], [33299, 2.3272550315278813], [33313, 2.289930090259902], [33327, 2.268631151404999], [33341, 2.327315042598321], [33355, 2.438583090704434], [33369, 2.3758271211366915], [33383, 2.40217849358207], [33397, 2.373926823475984], [33411, 2.3884158572488996], [33425, 2.394030755954849], [33439, 2.3666598883587615], [33453, 2.3386846700088415], [33467, 2.446650924995921], [33523, 2.3965802511007346], [33537, 2.4031626125289947], [33551, 2.3756919698197767], [33649, 2.396629893755654], [33705, 2.371114648476184], [33719, 2.4225713223521157], [33733, 2.3492934822958995], [33747, 2.2912027076807124], [33761, 2.2908328369028665], [33775, 2.263739670340948], [33803, 2.2347862463951165], [33817, 2.271973952329485], [33831, 2.2730440312516884], [33845, 2.250502822020164], [34041, 2.272554597466315], [34055, 2.300829794934255], [34069, 2.25904008242256], [34083, 2.2925168825051987], [34125, 2.277514277946549], [34139, 2.255021041008013], [34153, 2.271583868305388], [34167, 2.2753834305983016]] \ No newline at end of file +[[28511, 1.68351744584663], [29225, 2.346582049131427], [29239, 2.2536957476965767], [29253, 1.6585710395236875], [29267, 1.688610289266403], [29281, 1.7284908015588145], [29295, 1.7146283703018204], [29309, 1.7066088350013233], [29323, 1.691064117429641], [29337, 1.7216663648927508], [29351, 1.6839285819571739], [29365, 1.6422740958130089], [29379, 1.6810657419096118], [29393, 1.6606966379227501], [29407, 1.6649481860568014], [29421, 1.6619447448740996], [29435, 1.6421596759494586], [29449, 2.481159115557852], [29463, 2.508024634745909], [29477, 2.5476170990662523], [29547, 2.5334988039600317], [29561, 2.3834230013074396], [29575, 2.181837575295464], [29603, 2.217138328761994], [29617, 2.2250688025886642], [29631, 2.191579051635938], [29645, 2.2055694622872766], [29659, 2.2347681457008908], [29673, 2.2168063556771958], [29743, 2.229086193224686], [29757, 2.234013386772018], [29771, 2.252482807005255], [29785, 2.6053577786303856], [29799, 2.3492975608019444], [29813, 2.336347283075362], [29827, 2.401678397270591], [29841, 2.353910594198157], [29855, 2.3245233880648866], [29869, 2.2918804128781076], [30009, 2.336538178746106], [30023, 2.3589564838128494], [30037, 2.390530455392739], [30051, 2.377795445741982], [30065, 2.425732265820918], [30079, 2.353507932733517], [30093, 2.3542123642425197], [30107, 2.3389842840510346], [30121, 2.394802285393343], [30135, 2.3820148395751044], [30149, 2.3550279340616225], [30163, 2.390470694127003], [30177, 2.3363907523028127], [30191, 2.3003612013061754], [30205, 2.3394303126664675], [30219, 2.363816960525984], [30233, 2.3818313286898127], [30247, 2.3689904263044537], [30261, 2.3759486699297288], [30513, 2.3686680825768462], [30527, 2.3877567777405075], [30541, 2.406202635912726], [30555, 2.3662486352621026], [30569, 2.3676061178988266], [30583, 2.33128248185381], [30597, 2.3408401462398514], [30625, 2.3570418206431056], [30639, 2.328238399812842], [30653, 2.3963259016195724], [30667, 2.3284033542044735], [30681, 2.4005394699628195], [30695, 2.3402926918855997], [30709, 2.411209477612136], [30723, 2.398959590493856], [30737, 2.3649611012666067], [30751, 2.348288517816856], [30765, 2.381140596425348], [30779, 2.341815195921634], [30793, 2.353492775366478], [30807, 2.415413789635259], [30821, 2.365419388658096], [30835, 2.446162721752828], [30849, 2.2910876269709344], [30863, 2.3873148752301585], [30877, 2.3631351583331797], [30891, 2.347497072794629], [30905, 2.2585904431844224], [30919, 2.3552997208969795], [30933, 2.3567665084137017], [30947, 2.3300926474664196], [30961, 2.3673765000004736], [30975, 2.450140604637588], [30989, 2.4391102460178335], [31003, 2.421584851096986], [31017, 2.4437881219960804], [31031, 2.4241368635712166], [31045, 2.4172865765779283], [32095, 2.178598909731901], [32109, 2.216012942075734], [32123, 2.2041774333503628], [32137, 2.2517116650149562], [32151, 2.175217050084551], [32165, 2.22212746033415], [32179, 2.170422422669505], [32193, 2.2125478271695243], [32207, 2.2165278373207635], [32221, 2.2472297651246134], [32235, 2.2593191005615347], [32249, 2.2161220883111747], [32263, 2.2522685400382993], [32277, 2.3116669257726983], [32305, 2.2883851151794072], [32319, 2.2785287045886817], [32333, 2.274760129772384], [32347, 2.349744220369046], [32361, 2.3136569401606377], [32375, 2.2902821595126697], [32389, 2.285164602546379], [32403, 2.2686365149738696], [32417, 2.358684544033008], [32431, 2.279125936150566], [32445, 2.2358126710251396], [32585, 2.2857751682299106], [32599, 2.3823297675194124], [32613, 2.3207109487914606], [32627, 2.3551302264005773], [32641, 2.325078097227779], [32655, 2.3295703794467078], [32851, 2.1716648841947777], [32865, 2.2196950832141438], [32879, 2.1952762308391374], [32893, 2.276537679298381], [32907, 2.395336048843755], [32921, 2.409141052823972], [32991, 2.3605682565809], [33005, 2.4195086069410294], [33019, 2.4021514889714526], [33033, 2.376135714981526], [33047, 2.400022568712412], [33061, 2.3902034293550285], [33075, 2.4302450606653165], [33089, 2.39699563732807], [33103, 2.374204553639372], [33117, 2.426437508178664], [33131, 2.4154540542016356], [33145, 2.4049929622742643], [33159, 2.3707256817441054], [33187, 2.4310852688449947], [33201, 2.3831567648852126], [33215, 2.3681553743068124], [33229, 2.3376719177065395], [33243, 2.3501691902524153], [33271, 2.2588325012050534], [33299, 2.3272550315278813], [33313, 2.289930090259902], [33327, 2.268631151404999], [33341, 2.327315042598321], [33355, 2.438583090704434], [33369, 2.3758271211366915], [33383, 2.40217849358207], [33397, 2.373926823475984], [33411, 2.3884158572488996], [33425, 2.394030755954849], [33439, 2.3666598883587615], [33453, 2.3386846700088415], [33467, 2.446650924995921], [33523, 2.3965802511007346], [33537, 2.4031626125289947], [33551, 2.3756919698197767], [33649, 2.396629893755654], [33705, 2.371114648476184], [33719, 2.4225713223521157], [33733, 2.3492934822958995], [33747, 2.2912027076807124], [33761, 2.2908328369028665], [33775, 2.263739670340948], [33803, 2.2347862463951165], [33817, 2.271973952329485], [33831, 2.2730440312516884], [33845, 2.250502822020164], [34041, 2.272554597466315], [34055, 2.300829794934255], [34069, 2.25904008242256], [34083, 2.2925168825051987], [34125, 2.277514277946549], [34139, 2.255021041008013], [34153, 2.271583868305388], [34167, 2.276652758946118]] \ No newline at end of file diff --git a/graphs/summary/model_selection.CrossValidationBenchmark.peakmem_crossval.json b/graphs/summary/model_selection.CrossValidationBenchmark.peakmem_crossval.json index 507cadfc7b..6e45f57494 100644 --- a/graphs/summary/model_selection.CrossValidationBenchmark.peakmem_crossval.json +++ b/graphs/summary/model_selection.CrossValidationBenchmark.peakmem_crossval.json @@ -1 +1 @@ -[[28511, 157196335.01359454], [29225, 151198833.01063806], [29239, 151187879.646973], [29253, 154462637.2513421], [29267, 154487158.0719025], [29281, 154498394.70258096], [29295, 154634232.06529334], [29309, 154392875.3866372], [29323, 154378794.25634563], [29337, 154524653.08042392], [29351, 153866762.34589028], [29365, 153751719.55213717], [29379, 153838384.6837494], [29393, 153863492.10298932], [29407, 153814318.85543203], [29421, 153825656.67770627], [29435, 154154246.70789728], [29449, 151157690.10457993], [29463, 151099337.104477], [29477, 151142132.92724374], [29547, 151446264.17421594], [29561, 151285886.1126236], [29575, 150881679.5189661], [29603, 152012366.35932967], [29617, 152096934.31363177], [29631, 152223865.67641246], [29645, 152272373.68115175], [29659, 152231246.32914186], [29673, 152120520.63033378], [29743, 152173473.64473107], [29757, 152180275.91662288], [29771, 152248314.5086969], [29785, 152267295.25736713], [29799, 152164186.25144485], [29813, 152308712.07673085], [29827, 152389809.91393018], [29841, 152163920.43661392], [29855, 152180836.75042084], [29869, 152429157.0774693], [30009, 152365660.20977777], [30023, 152455847.13879955], [30037, 152204283.07134685], [30051, 152377682.77305996], [30065, 152256028.9793264], [30079, 152402810.4457368], [30093, 152330732.48979062], [30107, 152287559.67344108], [30121, 152445635.25141728], [30135, 152344150.12558436], [30149, 152597609.23124665], [30163, 152688394.69229135], [30177, 152587699.49813998], [30191, 152824746.6980148], [30205, 152795782.24593422], [30219, 152629818.76083094], [30233, 152525973.83435127], [30247, 152740795.92383698], [30261, 152647593.13353917], [30513, 152876285.10907298], [30527, 152710740.2280054], [30541, 152619567.86370337], [30555, 152482022.60979667], [30569, 152486649.8540756], [30583, 152718024.42375535], [30597, 152480933.96369097], [30625, 152553901.40350005], [30639, 152718202.43634892], [30653, 152541137.355937], [30667, 152549205.4991878], [30681, 152572441.00180283], [30695, 152605610.65690866], [30709, 152583493.37036073], [30723, 152501459.88266787], [30737, 152668879.75801566], [30751, 152683788.19917914], [30765, 153029313.46102566], [30779, 152580660.0772371], [30793, 152653980.63980612], [30807, 152796082.98816246], [30821, 152865087.17472926], [30835, 152963712.08606318], [30849, 152864583.602788], [30863, 152743444.07191348], [30877, 152630359.6111018], [30891, 152820624.12700358], [30905, 152822743.59672746], [30919, 152737634.94937333], [30933, 152695892.5649904], [30947, 152669656.96804535], [30961, 152751784.01668355], [30975, 152749090.88842875], [30989, 152799912.47364637], [31003, 152875016.72332728], [31017, 152929661.4428669], [31031, 152851654.69232544], [31045, 152806004.88528556], [32095, 165047014.55048934], [32109, 165247147.53136417], [32123, 165315533.57662877], [32137, 165374318.16823962], [32151, 165248678.70527685], [32165, 165273790.42545596], [32179, 165187986.55092412], [32193, 165392546.0825313], [32207, 166699904.34613016], [32221, 168468573.83551252], [32235, 168639620.21332264], [32249, 168555340.60938784], [32263, 168594113.14157653], [32277, 168067100.40870932], [32305, 170437986.76399374], [32319, 175234677.47643292], [32333, 175326352.1082478], [32347, 175249466.86806482], [32361, 175338018.27875897], [32375, 175248772.98745546], [32389, 175145761.41462755], [32403, 175420045.36754593], [32417, 175176310.34633902], [32431, 175288312.40033317], [32445, 175405901.9006072], [32585, 172156974.70733604], [32599, 172288111.03111863], [32613, 172152218.36812797], [32627, 172244358.7805349], [32641, 172152646.46045268], [32655, 172202188.37632418], [32851, 173216374.66908202], [32865, 173246034.79168135], [32879, 173255171.26954144], [32893, 173333142.96417198], [32907, 173273969.71520108], [32921, 173159625.76992655], [32991, 173393155.2124869], [33005, 173187342.7124321], [33019, 173008396.67245674], [33033, 173141040.03808194], [33047, 173210645.4030764], [33061, 173634191.63402423], [33075, 173494195.41212276], [33089, 182420404.27073658], [33103, 191206139.75865617], [33117, 191308925.6355124], [33131, 191078600.20225075], [33145, 191549064.90885973], [33159, 191678347.92701066], [33187, 173760934.32526112], [33201, 173598001.81272584], [33215, 172398285.39228594], [33229, 168968310.11887527], [33243, 169102789.29993847], [33271, 164803108.45689774], [33299, 164369056.4922324], [33313, 164504380.51939443], [33327, 164986070.01422268], [33341, 165007028.8712022], [33355, 165066843.1706371], [33369, 165229925.17988452], [33383, 165901815.30908966], [33397, 166432155.3664868], [33411, 166362250.6117862], [33425, 166387370.10011017], [33439, 167375379.05389237], [33453, 162500502.69106564], [33467, 162561745.45426393], [33523, 162390024.38921997], [33537, 162584097.45423865], [33551, 161994532.56807297], [33649, 161087682.75984973], [33705, 160711841.59742108], [33719, 160928488.47973704], [33733, 160941415.11856046], [33747, 160889247.34743804], [33761, 160911333.25635517], [33775, 160923168.2143123], [33803, 160723882.16592062], [33817, 160580205.65345514], [33831, 160652196.41920075], [33845, 160677439.06616187], [34041, 160304577.52583987], [34055, 160589940.1083144], [34069, 160541036.01428473], [34083, 160435479.3511091], [34125, 160519578.9940158], [34139, 160528996.63779604], [34153, 160531300.76859078], [34167, 160540773.03220913]] \ No newline at end of file +[[28511, 157196335.01359454], [29225, 151198833.01063806], [29239, 151187879.646973], [29253, 154462637.2513421], [29267, 154487158.0719025], [29281, 154498394.70258096], [29295, 154634232.06529334], [29309, 154392875.3866372], [29323, 154378794.25634563], [29337, 154524653.08042392], [29351, 153866762.34589028], [29365, 153751719.55213717], [29379, 153838384.6837494], [29393, 153863492.10298932], [29407, 153814318.85543203], [29421, 153825656.67770627], [29435, 154154246.70789728], [29449, 151157690.10457993], [29463, 151099337.104477], [29477, 151142132.92724374], [29547, 151446264.17421594], [29561, 151285886.1126236], [29575, 150881679.5189661], [29603, 152012366.35932967], [29617, 152096934.31363177], [29631, 152223865.67641246], [29645, 152272373.68115175], [29659, 152231246.32914186], [29673, 152120520.63033378], [29743, 152173473.64473107], [29757, 152180275.91662288], [29771, 152248314.5086969], [29785, 152267295.25736713], [29799, 152164186.25144485], [29813, 152308712.07673085], [29827, 152389809.91393018], [29841, 152163920.43661392], [29855, 152180836.75042084], [29869, 152429157.0774693], [30009, 152365660.20977777], [30023, 152455847.13879955], [30037, 152204283.07134685], [30051, 152377682.77305996], [30065, 152256028.9793264], [30079, 152402810.4457368], [30093, 152330732.48979062], [30107, 152287559.67344108], [30121, 152445635.25141728], [30135, 152344150.12558436], [30149, 152597609.23124665], [30163, 152688394.69229135], [30177, 152587699.49813998], [30191, 152824746.6980148], [30205, 152795782.24593422], [30219, 152629818.76083094], [30233, 152525973.83435127], [30247, 152740795.92383698], [30261, 152647593.13353917], [30513, 152876285.10907298], [30527, 152710740.2280054], [30541, 152619567.86370337], [30555, 152482022.60979667], [30569, 152486649.8540756], [30583, 152718024.42375535], [30597, 152480933.96369097], [30625, 152553901.40350005], [30639, 152718202.43634892], [30653, 152541137.355937], [30667, 152549205.4991878], [30681, 152572441.00180283], [30695, 152605610.65690866], [30709, 152583493.37036073], [30723, 152501459.88266787], [30737, 152668879.75801566], [30751, 152683788.19917914], [30765, 153029313.46102566], [30779, 152580660.0772371], [30793, 152653980.63980612], [30807, 152796082.98816246], [30821, 152865087.17472926], [30835, 152963712.08606318], [30849, 152864583.602788], [30863, 152743444.07191348], [30877, 152630359.6111018], [30891, 152820624.12700358], [30905, 152822743.59672746], [30919, 152737634.94937333], [30933, 152695892.5649904], [30947, 152669656.96804535], [30961, 152751784.01668355], [30975, 152749090.88842875], [30989, 152799912.47364637], [31003, 152875016.72332728], [31017, 152929661.4428669], [31031, 152851654.69232544], [31045, 152806004.88528556], [32095, 165047014.55048934], [32109, 165247147.53136417], [32123, 165315533.57662877], [32137, 165374318.16823962], [32151, 165248678.70527685], [32165, 165273790.42545596], [32179, 165187986.55092412], [32193, 165392546.0825313], [32207, 166699904.34613016], [32221, 168468573.83551252], [32235, 168639620.21332264], [32249, 168555340.60938784], [32263, 168594113.14157653], [32277, 168067100.40870932], [32305, 170437986.76399374], [32319, 175234677.47643292], [32333, 175326352.1082478], [32347, 175249466.86806482], [32361, 175338018.27875897], [32375, 175248772.98745546], [32389, 175145761.41462755], [32403, 175420045.36754593], [32417, 175176310.34633902], [32431, 175288312.40033317], [32445, 175405901.9006072], [32585, 172156974.70733604], [32599, 172288111.03111863], [32613, 172152218.36812797], [32627, 172244358.7805349], [32641, 172152646.46045268], [32655, 172202188.37632418], [32851, 173216374.66908202], [32865, 173246034.79168135], [32879, 173255171.26954144], [32893, 173333142.96417198], [32907, 173273969.71520108], [32921, 173159625.76992655], [32991, 173393155.2124869], [33005, 173187342.7124321], [33019, 173008396.67245674], [33033, 173141040.03808194], [33047, 173210645.4030764], [33061, 173634191.63402423], [33075, 173494195.41212276], [33089, 182420404.27073658], [33103, 191206139.75865617], [33117, 191308925.6355124], [33131, 191078600.20225075], [33145, 191549064.90885973], [33159, 191678347.92701066], [33187, 173760934.32526112], [33201, 173598001.81272584], [33215, 172398285.39228594], [33229, 168968310.11887527], [33243, 169102789.29993847], [33271, 164803108.45689774], [33299, 164369056.4922324], [33313, 164504380.51939443], [33327, 164986070.01422268], [33341, 165007028.8712022], [33355, 165066843.1706371], [33369, 165229925.17988452], [33383, 165901815.30908966], [33397, 166432155.3664868], [33411, 166362250.6117862], [33425, 166387370.10011017], [33439, 167375379.05389237], [33453, 162500502.69106564], [33467, 162561745.45426393], [33523, 162390024.38921997], [33537, 162584097.45423865], [33551, 161994532.56807297], [33649, 161087682.75984973], [33705, 160711841.59742108], [33719, 160928488.47973704], [33733, 160941415.11856046], [33747, 160889247.34743804], [33761, 160911333.25635517], [33775, 160923168.2143123], [33803, 160723882.16592062], [33817, 160580205.65345514], [33831, 160652196.41920075], [33845, 160677439.06616187], [34041, 160304577.52583987], [34055, 160589940.1083144], [34069, 160541036.01428473], [34083, 160435479.3511091], [34125, 160519578.9940158], [34139, 160528996.63779604], [34153, 160531300.76859078], [34167, 160495900.47395617]] \ No newline at end of file diff --git a/graphs/summary/model_selection.CrossValidationBenchmark.time_crossval.json b/graphs/summary/model_selection.CrossValidationBenchmark.time_crossval.json index 9b36be1773..b0249aa320 100644 --- a/graphs/summary/model_selection.CrossValidationBenchmark.time_crossval.json +++ b/graphs/summary/model_selection.CrossValidationBenchmark.time_crossval.json @@ -1 +1 @@ -[[28511, 22.81852091093184], [29225, 26.728847404091365], [29239, 24.782934932664354], [29253, 23.014567937263745], [29267, 22.890812412784783], [29281, 22.86477601798429], [29295, 23.013984169022518], [29309, 22.970868456694912], [29323, 22.860527199848327], [29337, 23.001886694476017], [29351, 22.900415704188706], [29365, 22.808483183457124], [29379, 22.964500696111276], [29393, 22.912056830642978], [29407, 22.933997627210957], [29421, 22.949502890830555], [29435, 23.095296753775813], [29449, 29.244775080556177], [29463, 29.405308041187062], [29477, 28.506723132386757], [29547, 28.909004098813174], [29561, 28.59408632108061], [29575, 25.680488260405784], [29603, 24.480661187527318], [29617, 24.49096423959605], [29631, 23.837317669282832], [29645, 24.777665305620786], [29659, 24.99605705029896], [29673, 24.634326632715897], [29743, 25.407317312193825], [29757, 24.647803994675705], [29771, 25.43141497285064], [29785, 28.806691958475465], [29799, 24.59399157123754], [29813, 24.78433183926164], [29827, 25.77870803813767], [29841, 24.621987955092372], [29855, 24.76380940360317], [29869, 23.966388308458182], [30009, 24.888890027839974], [30023, 24.209558353382842], [30037, 25.06318401304914], [30051, 25.169244032950115], [30065, 26.079794352637748], [30079, 24.82443844551375], [30093, 24.656700949349585], [30107, 24.559813319650885], [30121, 24.085704789229137], [30135, 25.250107012781154], [30149, 25.426253728068666], [30163, 24.97227566687087], [30177, 24.68850914996406], [30191, 25.212150937046122], [30205, 24.230342921206073], [30219, 25.64186900298056], [30233, 25.78067208323297], [30247, 25.049195310420984], [30261, 25.40084291868648], [30513, 24.32538880196532], [30527, 24.847084493971956], [30541, 25.418547885310886], [30555, 24.824067884528393], [30569, 25.130972078896185], [30583, 25.304408065225978], [30597, 25.08636161547753], [30625, 24.16114660282122], [30639, 24.378240919586673], [30653, 25.176143719534736], [30667, 24.25998891631474], [30681, 25.262473991781018], [30695, 23.44083719920863], [30709, 24.42132890857411], [30723, 25.577116124692125], [30737, 25.701113258462236], [30751, 25.085381515569892], [30765, 25.015795585457155], [30779, 25.614130220048352], [30793, 24.968858500534363], [30807, 25.193429237329028], [30821, 25.15040313489375], [30835, 25.373293010615797], [30849, 27.398382280994703], [30863, 25.14046630336005], [30877, 25.760530990807688], [30891, 25.904493846514452], [30905, 24.395430159997687], [30919, 24.123311356799434], [30933, 22.884612306363103], [30947, 22.42454907326976], [30961, 23.207330073282908], [30975, 23.72069866567749], [30989, 22.696696112320932], [31003, 23.38613296659333], [31017, 22.23655557853121], [31031, 22.501636156779657], [31045, 22.479094042988088], [32095, 25.361662869534534], [32109, 25.16174032332484], [32123, 25.749255780976654], [32137, 25.773606041364612], [32151, 24.893856429444124], [32165, 25.312225213974934], [32179, 24.28300107812351], [32193, 24.78753110377649], [32207, 24.608758433301958], [32221, 24.476367390697547], [32235, 25.085916384356047], [32249, 23.509451084831923], [32263, 24.84681309550203], [32277, 25.01649374200838], [32305, 25.145201337314944], [32319, 24.954054995226624], [32333, 24.947530758699493], [32347, 26.338068223641557], [32361, 25.40234883982129], [32375, 25.29285749931251], [32389, 25.076977748486538], [32403, 24.647743893486624], [32417, 25.895205687549794], [32431, 33.13298747228855], [32445, 33.03600097006035], [32585, 36.781643588092095], [32599, 47.89856539047951], [32613, 46.43935184192956], [32627, 52.62677073149028], [32641, 51.41655746984526], [32655, 50.732576226504364], [32851, 45.657502567683736], [32865, 46.40010286271813], [32879, 46.345711654281786], [32893, 47.23458936427081], [32907, 47.888942719700175], [32921, 47.6986795370097], [32991, 46.48212208422277], [33005, 48.764581899495724], [33019, 45.3475993458341], [33033, 46.574159294140884], [33047, 45.87259094215587], [33061, 45.639707472239635], [33075, 45.73274504607608], [33089, 45.89751296685694], [33103, 47.105794356645795], [33117, 47.7923274626086], [33131, 45.98703235434855], [33145, 45.49069755538295], [33159, 46.09567359454806], [33187, 46.25859817217376], [33201, 47.594673497731954], [33215, 45.2522472757894], [33229, 38.32998275934503], [33243, 37.63427335704194], [33271, 31.00384673521123], [33299, 39.59597662755005], [33313, 32.300701235806855], [33327, 31.82771222022229], [33341, 32.587408444577484], [33355, 33.19860784168946], [33369, 32.56878505005624], [33383, 31.87055352709798], [33397, 32.05750089070504], [33411, 32.40979135530269], [33425, 32.088874612560446], [33439, 31.57958173321792], [33453, 32.44916045208974], [33467, 34.78882630107882], [33523, 32.398010947001666], [33537, 32.33004278411709], [33551, 32.599422638185594], [33649, 79.4201939229808], [33705, 80.27173355800187], [33719, 80.91845319705914], [33733, 35.39357476746922], [33747, 34.1515975469859], [33761, 31.772302546134007], [33775, 34.7036036068964], [33803, 32.48259666995007], [33817, 32.20017080190445], [33831, 32.36740289169991], [33845, 31.353894454500978], [34041, 78.74009093750624], [34055, 78.86470331697986], [34069, 79.6809823054541], [34083, 84.14243217419559], [34125, 33.22509887065322], [34139, 33.281621391303716], [34153, 31.813439299937283], [34167, 32.679314395171836]] \ No newline at end of file +[[28511, 22.81852091093184], [29225, 26.728847404091365], [29239, 24.782934932664354], [29253, 23.014567937263745], [29267, 22.890812412784783], [29281, 22.86477601798429], [29295, 23.013984169022518], [29309, 22.970868456694912], [29323, 22.860527199848327], [29337, 23.001886694476017], [29351, 22.900415704188706], [29365, 22.808483183457124], [29379, 22.964500696111276], [29393, 22.912056830642978], [29407, 22.933997627210957], [29421, 22.949502890830555], [29435, 23.095296753775813], [29449, 29.244775080556177], [29463, 29.405308041187062], [29477, 28.506723132386757], [29547, 28.909004098813174], [29561, 28.59408632108061], [29575, 25.680488260405784], [29603, 24.480661187527318], [29617, 24.49096423959605], [29631, 23.837317669282832], [29645, 24.777665305620786], [29659, 24.99605705029896], [29673, 24.634326632715897], [29743, 25.407317312193825], [29757, 24.647803994675705], [29771, 25.43141497285064], [29785, 28.806691958475465], [29799, 24.59399157123754], [29813, 24.78433183926164], [29827, 25.77870803813767], [29841, 24.621987955092372], [29855, 24.76380940360317], [29869, 23.966388308458182], [30009, 24.888890027839974], [30023, 24.209558353382842], [30037, 25.06318401304914], [30051, 25.169244032950115], [30065, 26.079794352637748], [30079, 24.82443844551375], [30093, 24.656700949349585], [30107, 24.559813319650885], [30121, 24.085704789229137], [30135, 25.250107012781154], [30149, 25.426253728068666], [30163, 24.97227566687087], [30177, 24.68850914996406], [30191, 25.212150937046122], [30205, 24.230342921206073], [30219, 25.64186900298056], [30233, 25.78067208323297], [30247, 25.049195310420984], [30261, 25.40084291868648], [30513, 24.32538880196532], [30527, 24.847084493971956], [30541, 25.418547885310886], [30555, 24.824067884528393], [30569, 25.130972078896185], [30583, 25.304408065225978], [30597, 25.08636161547753], [30625, 24.16114660282122], [30639, 24.378240919586673], [30653, 25.176143719534736], [30667, 24.25998891631474], [30681, 25.262473991781018], [30695, 23.44083719920863], [30709, 24.42132890857411], [30723, 25.577116124692125], [30737, 25.701113258462236], [30751, 25.085381515569892], [30765, 25.015795585457155], [30779, 25.614130220048352], [30793, 24.968858500534363], [30807, 25.193429237329028], [30821, 25.15040313489375], [30835, 25.373293010615797], [30849, 27.398382280994703], [30863, 25.14046630336005], [30877, 25.760530990807688], [30891, 25.904493846514452], [30905, 24.395430159997687], [30919, 24.123311356799434], [30933, 22.884612306363103], [30947, 22.42454907326976], [30961, 23.207330073282908], [30975, 23.72069866567749], [30989, 22.696696112320932], [31003, 23.38613296659333], [31017, 22.23655557853121], [31031, 22.501636156779657], [31045, 22.479094042988088], [32095, 25.361662869534534], [32109, 25.16174032332484], [32123, 25.749255780976654], [32137, 25.773606041364612], [32151, 24.893856429444124], [32165, 25.312225213974934], [32179, 24.28300107812351], [32193, 24.78753110377649], [32207, 24.608758433301958], [32221, 24.476367390697547], [32235, 25.085916384356047], [32249, 23.509451084831923], [32263, 24.84681309550203], [32277, 25.01649374200838], [32305, 25.145201337314944], [32319, 24.954054995226624], [32333, 24.947530758699493], [32347, 26.338068223641557], [32361, 25.40234883982129], [32375, 25.29285749931251], [32389, 25.076977748486538], [32403, 24.647743893486624], [32417, 25.895205687549794], [32431, 33.13298747228855], [32445, 33.03600097006035], [32585, 36.781643588092095], [32599, 47.89856539047951], [32613, 46.43935184192956], [32627, 52.62677073149028], [32641, 51.41655746984526], [32655, 50.732576226504364], [32851, 45.657502567683736], [32865, 46.40010286271813], [32879, 46.345711654281786], [32893, 47.23458936427081], [32907, 47.888942719700175], [32921, 47.6986795370097], [32991, 46.48212208422277], [33005, 48.764581899495724], [33019, 45.3475993458341], [33033, 46.574159294140884], [33047, 45.87259094215587], [33061, 45.639707472239635], [33075, 45.73274504607608], [33089, 45.89751296685694], [33103, 47.105794356645795], [33117, 47.7923274626086], [33131, 45.98703235434855], [33145, 45.49069755538295], [33159, 46.09567359454806], [33187, 46.25859817217376], [33201, 47.594673497731954], [33215, 45.2522472757894], [33229, 38.32998275934503], [33243, 37.63427335704194], [33271, 31.00384673521123], [33299, 39.59597662755005], [33313, 32.300701235806855], [33327, 31.82771222022229], [33341, 32.587408444577484], [33355, 33.19860784168946], [33369, 32.56878505005624], [33383, 31.87055352709798], [33397, 32.05750089070504], [33411, 32.40979135530269], [33425, 32.088874612560446], [33439, 31.57958173321792], [33453, 32.44916045208974], [33467, 34.78882630107882], [33523, 32.398010947001666], [33537, 32.33004278411709], [33551, 32.599422638185594], [33649, 79.4201939229808], [33705, 80.27173355800187], [33719, 80.91845319705914], [33733, 35.39357476746922], [33747, 34.1515975469859], [33761, 31.772302546134007], [33775, 34.7036036068964], [33803, 32.48259666995007], [33817, 32.20017080190445], [33831, 32.36740289169991], [33845, 31.353894454500978], [34041, 78.74009093750624], [34055, 78.86470331697986], [34069, 79.6809823054541], [34083, 84.14243217419559], [34125, 33.22509887065322], [34139, 33.281621391303716], [34153, 31.813439299937283], [34167, 32.32725823315871]] \ No newline at end of file diff --git a/graphs/summary/model_selection.CrossValidationBenchmark.track_crossval.json b/graphs/summary/model_selection.CrossValidationBenchmark.track_crossval.json index 2655610f8c..110d22882a 100644 --- a/graphs/summary/model_selection.CrossValidationBenchmark.track_crossval.json +++ b/graphs/summary/model_selection.CrossValidationBenchmark.track_crossval.json @@ -1 +1 @@ -[[28511, 0.9001555555555556], [29225, 0.9001555555555556], [29239, 0.9001555555555555], [29253, 0.9001555555555556], [29267, 0.9001555555555556], [29281, 0.9001555555555556], [29295, 0.9001555555555556], [29309, 0.9001555555555556], [29323, 0.9001555555555556], [29337, 0.9001555555555556], [29351, 0.9001555555555556], [29365, 0.9001555555555556], [29379, 0.9001555555555556], [29393, 0.9001555555555556], [29407, 0.9001555555555556], [29421, 0.9001555555555556], [29435, 0.9001555555555556], [29449, 0.9001555555555556], [29463, 0.9001555555555555], [29477, 0.9001555555555556], [29547, 0.9001555555555556], [29561, 0.9001555555555556], [29575, 0.9001555555555556], [29603, 0.9001555555555556], [29617, 0.9001555555555556], [29631, 0.9001555555555556], [29645, 0.9001555555555556], [29659, 0.9001555555555556], [29673, 0.9001555555555556], [29743, 0.9001555555555556], [29757, 0.9001555555555556], [29771, 0.9001555555555555], [29785, 0.9001555555555556], [29799, 0.9001555555555555], [29813, 0.9001555555555556], [29827, 0.9001555555555556], [29841, 0.9001555555555556], [29855, 0.9001555555555556], [29869, 0.9001555555555556], [30009, 0.9001555555555556], [30023, 0.9001555555555556], [30037, 0.9001555555555556], [30051, 0.9001555555555556], [30065, 0.9001555555555556], [30079, 0.9001555555555554], [30093, 0.9001555555555556], [30107, 0.9001555555555556], [30121, 0.9001555555555556], [30135, 0.9001555555555556], [30149, 0.9001555555555556], [30163, 0.9001555555555556], [30177, 0.9001555555555556], [30191, 0.9001555555555556], [30205, 0.9001555555555556], [30219, 0.9001555555555555], [30233, 0.9001555555555556], [30247, 0.9001555555555556], [30261, 0.9001555555555556], [30513, 0.9001555555555555], [30527, 0.9001555555555555], [30541, 0.9001555555555556], [30555, 0.9001555555555555], [30569, 0.9001555555555556], [30583, 0.9001555555555556], [30597, 0.9001555555555556], [30625, 0.9001555555555556], [30639, 0.9001555555555556], [30653, 0.9001555555555555], [30667, 0.9001555555555556], [30681, 0.9001555555555556], [30695, 0.9001555555555556], [30709, 0.9001555555555556], [30723, 0.9001555555555556], [30737, 0.9001555555555556], [30751, 0.9001555555555556], [30765, 0.9001555555555556], [30779, 0.9001555555555556], [30793, 0.9001555555555556], [30807, 0.9001555555555556], [30821, 0.9001555555555556], [30835, 0.9001555555555556], [30849, 0.9001555555555556], [30863, 0.9001555555555556], [30877, 0.9001555555555556], [30891, 0.9001555555555556], [30905, 0.9001555555555556], [30919, 0.9001555555555556], [30933, 0.9001555555555556], [30947, 0.9001555555555556], [30961, 0.9001555555555556], [30975, 0.9001555555555556], [30989, 0.9001555555555556], [31003, 0.9001555555555556], [31017, 0.9001555555555556], [31031, 0.9001555555555556], [31045, 0.9001555555555556], [32095, 0.9001555555555556], [32109, 0.9001555555555556], [32123, 0.9001555555555556], [32137, 0.9001555555555556], [32151, 0.9001555555555556], [32165, 0.9001555555555556], [32179, 0.9001555555555556], [32193, 0.9001555555555556], [32207, 0.9001555555555556], [32221, 0.9001555555555556], [32235, 0.9001555555555556], [32249, 0.9001555555555556], [32263, 0.9001555555555555], [32277, 0.9001555555555556], [32305, 0.9001555555555556], [32319, 0.9001555555555556], [32333, 0.9001555555555556], [32347, 0.9001555555555556], [32361, 0.9001555555555556], [32375, 0.9001555555555556], [32389, 0.9001555555555556], [32403, 0.9001555555555556], [32417, 0.9001555555555556], [32431, 0.9001555555555556], [32445, 0.9001555555555556], [32585, 0.9001555555555556], [32599, 0.9001555555555556], [32613, 0.9001555555555556], [32627, 0.9001555555555556], [32641, 0.9001555555555556], [32655, 0.9001555555555556], [32851, 0.9001555555555556], [32865, 0.9001555555555556], [32879, 0.9001555555555556], [32893, 0.9001555555555556], [32907, 0.9001555555555556], [32921, 0.9001555555555556], [32991, 0.9001555555555556], [33005, 0.9001555555555556], [33019, 0.9001555555555556], [33033, 0.9001555555555556], [33047, 0.9001555555555556], [33061, 0.9001555555555556], [33075, 0.9001555555555556], [33089, 0.9001555555555556], [33103, 0.9001555555555556], [33117, 0.9001555555555556], [33131, 0.9001555555555556], [33145, 0.9001555555555556], [33159, 0.9001555555555556], [33187, 0.9001555555555556], [33201, 0.9001555555555556], [33215, 0.9001555555555556], [33229, 0.9001555555555556], [33243, 0.9001555555555556], [33271, 0.9001555555555556], [33299, 0.9001555555555556], [33313, 0.9001555555555556], [33327, 0.9001555555555556], [33341, 0.9001555555555556], [33355, 0.9001555555555556], [33369, 0.9001555555555556], [33383, 0.9001555555555556], [33397, 0.9001555555555556], [33411, 0.9001555555555556], [33425, 0.9001555555555556], [33439, 0.9001555555555556], [33453, 0.9001555555555556], [33467, 0.9001555555555556], [33523, 0.9001555555555556], [33537, 0.9001555555555556], [33551, 0.9001555555555556], [33649, 0.9001555555555556], [33705, 0.9001555555555556], [33719, 0.9001555555555556], [33733, 0.9001555555555556], [33747, 0.9001555555555556], [33761, 0.9001555555555556], [33775, 0.9001555555555556], [33803, 0.9001555555555556], [33817, 0.9001555555555556], [33831, 0.9001555555555556], [33845, 0.9001555555555556], [34041, 0.9001555555555556], [34055, 0.9001555555555556], [34069, 0.9001555555555556], [34083, 0.9001555555555556], [34125, 0.9001555555555556], [34139, 0.9001555555555556], [34153, 0.9001555555555556], [34167, 0.9001555555555556]] \ No newline at end of file +[[28511, 0.9001555555555556], [29225, 0.9001555555555556], [29239, 0.9001555555555555], [29253, 0.9001555555555556], [29267, 0.9001555555555556], [29281, 0.9001555555555556], [29295, 0.9001555555555556], [29309, 0.9001555555555556], [29323, 0.9001555555555556], [29337, 0.9001555555555556], [29351, 0.9001555555555556], [29365, 0.9001555555555556], [29379, 0.9001555555555556], [29393, 0.9001555555555556], [29407, 0.9001555555555556], [29421, 0.9001555555555556], [29435, 0.9001555555555556], [29449, 0.9001555555555556], [29463, 0.9001555555555555], [29477, 0.9001555555555556], [29547, 0.9001555555555556], [29561, 0.9001555555555556], [29575, 0.9001555555555556], [29603, 0.9001555555555556], [29617, 0.9001555555555556], [29631, 0.9001555555555556], [29645, 0.9001555555555556], [29659, 0.9001555555555556], [29673, 0.9001555555555556], [29743, 0.9001555555555556], [29757, 0.9001555555555556], [29771, 0.9001555555555555], [29785, 0.9001555555555556], [29799, 0.9001555555555555], [29813, 0.9001555555555556], [29827, 0.9001555555555556], [29841, 0.9001555555555556], [29855, 0.9001555555555556], [29869, 0.9001555555555556], [30009, 0.9001555555555556], [30023, 0.9001555555555556], [30037, 0.9001555555555556], [30051, 0.9001555555555556], [30065, 0.9001555555555556], [30079, 0.9001555555555554], [30093, 0.9001555555555556], [30107, 0.9001555555555556], [30121, 0.9001555555555556], [30135, 0.9001555555555556], [30149, 0.9001555555555556], [30163, 0.9001555555555556], [30177, 0.9001555555555556], [30191, 0.9001555555555556], [30205, 0.9001555555555556], [30219, 0.9001555555555555], [30233, 0.9001555555555556], [30247, 0.9001555555555556], [30261, 0.9001555555555556], [30513, 0.9001555555555555], [30527, 0.9001555555555555], [30541, 0.9001555555555556], [30555, 0.9001555555555555], [30569, 0.9001555555555556], [30583, 0.9001555555555556], [30597, 0.9001555555555556], [30625, 0.9001555555555556], [30639, 0.9001555555555556], [30653, 0.9001555555555555], [30667, 0.9001555555555556], [30681, 0.9001555555555556], [30695, 0.9001555555555556], [30709, 0.9001555555555556], [30723, 0.9001555555555556], [30737, 0.9001555555555556], [30751, 0.9001555555555556], [30765, 0.9001555555555556], [30779, 0.9001555555555556], [30793, 0.9001555555555556], [30807, 0.9001555555555556], [30821, 0.9001555555555556], [30835, 0.9001555555555556], [30849, 0.9001555555555556], [30863, 0.9001555555555556], [30877, 0.9001555555555556], [30891, 0.9001555555555556], [30905, 0.9001555555555556], [30919, 0.9001555555555556], [30933, 0.9001555555555556], [30947, 0.9001555555555556], [30961, 0.9001555555555556], [30975, 0.9001555555555556], [30989, 0.9001555555555556], [31003, 0.9001555555555556], [31017, 0.9001555555555556], [31031, 0.9001555555555556], [31045, 0.9001555555555556], [32095, 0.9001555555555556], [32109, 0.9001555555555556], [32123, 0.9001555555555556], [32137, 0.9001555555555556], [32151, 0.9001555555555556], [32165, 0.9001555555555556], [32179, 0.9001555555555556], [32193, 0.9001555555555556], [32207, 0.9001555555555556], [32221, 0.9001555555555556], [32235, 0.9001555555555556], [32249, 0.9001555555555556], [32263, 0.9001555555555555], [32277, 0.9001555555555556], [32305, 0.9001555555555556], [32319, 0.9001555555555556], [32333, 0.9001555555555556], [32347, 0.9001555555555556], [32361, 0.9001555555555556], [32375, 0.9001555555555556], [32389, 0.9001555555555556], [32403, 0.9001555555555556], [32417, 0.9001555555555556], [32431, 0.9001555555555556], [32445, 0.9001555555555556], [32585, 0.9001555555555556], [32599, 0.9001555555555556], [32613, 0.9001555555555556], [32627, 0.9001555555555556], [32641, 0.9001555555555556], [32655, 0.9001555555555556], [32851, 0.9001555555555556], [32865, 0.9001555555555556], [32879, 0.9001555555555556], [32893, 0.9001555555555556], [32907, 0.9001555555555556], [32921, 0.9001555555555556], [32991, 0.9001555555555556], [33005, 0.9001555555555556], [33019, 0.9001555555555556], [33033, 0.9001555555555556], [33047, 0.9001555555555556], [33061, 0.9001555555555556], [33075, 0.9001555555555556], [33089, 0.9001555555555556], [33103, 0.9001555555555556], [33117, 0.9001555555555556], [33131, 0.9001555555555556], [33145, 0.9001555555555556], [33159, 0.9001555555555556], [33187, 0.9001555555555556], [33201, 0.9001555555555556], [33215, 0.9001555555555556], [33229, 0.9001555555555556], [33243, 0.9001555555555556], [33271, 0.9001555555555556], [33299, 0.9001555555555556], [33313, 0.9001555555555556], [33327, 0.9001555555555556], [33341, 0.9001555555555556], [33355, 0.9001555555555556], [33369, 0.9001555555555556], [33383, 0.9001555555555556], [33397, 0.9001555555555556], [33411, 0.9001555555555556], [33425, 0.9001555555555556], [33439, 0.9001555555555556], [33453, 0.9001555555555556], [33467, 0.9001555555555556], [33523, 0.9001555555555556], [33537, 0.9001555555555556], [33551, 0.9001555555555556], [33649, 0.9001555555555556], [33705, 0.9001555555555556], [33719, 0.9001555555555556], [33733, 0.9001555555555556], [33747, 0.9001555555555556], [33761, 0.9001555555555556], [33775, 0.9001555555555556], [33803, 0.9001555555555556], [33817, 0.9001555555555556], [33831, 0.9001555555555556], [33845, 0.9001555555555556], [34041, 0.9001555555555556], [34055, 0.9001555555555556], [34069, 0.9001555555555556], [34083, 0.9001555555555556], [34125, 0.9001555555555556], [34139, 0.9001555555555556], [34153, 0.9001555555555556], [34167, 0.9001555555555555]] \ No newline at end of file diff --git a/graphs/summary/model_selection.GridSearchBenchmark.peakmem_fit.json b/graphs/summary/model_selection.GridSearchBenchmark.peakmem_fit.json index 316008e799..e72a608b36 100644 --- a/graphs/summary/model_selection.GridSearchBenchmark.peakmem_fit.json +++ b/graphs/summary/model_selection.GridSearchBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 86322228.22703315], [29225, 83784833.90063383], [29239, 83574075.1213358], [29253, 83735503.7007549], [29267, 83840137.33567695], [29281, 83903502.19080393], [29295, 83869471.38821624], [29309, 83764978.94380853], [29323, 83682238.54209527], [29337, 83894906.92431034], [29351, 83390882.53012013], [29365, 83506060.62114188], [29379, 83303256.05169293], [29393, 83370723.09102903], [29407, 83291128.08360156], [29421, 83381708.0714557], [29435, 83758689.00583039], [29449, 83786685.52661566], [29463, 83716654.55315392], [29477, 83659694.52390799], [29547, 84108616.62260939], [29561, 83974536.19920045], [29575, 83225359.65100944], [29603, 84624733.20113254], [29617, 84779661.9123446], [29631, 84766313.16993459], [29645, 84854545.96562089], [29659, 84809417.39347352], [29673, 84685581.23090895], [29743, 84687877.4334884], [29757, 84659770.46317738], [29771, 84874590.72472982], [29785, 84715235.50556305], [29799, 84686551.34252182], [29813, 85009537.30736615], [29827, 84917794.17252877], [29841, 84845846.0691868], [29855, 84798704.42839448], [29869, 85158836.78390035], [30009, 84953443.55098847], [30023, 84945255.15640424], [30037, 85000656.61278176], [30051, 85197915.06962597], [30065, 85125254.58697408], [30079, 85091370.74890767], [30093, 85105255.01520963], [30107, 85054196.08038898], [30121, 85261486.34955876], [30135, 85136842.74454278], [30149, 85295138.82708241], [30163, 85500992.38114649], [30177, 85271436.6835587], [30191, 85547809.88512474], [30205, 85621660.17395443], [30219, 85412758.64040656], [30233, 85484393.15768304], [30247, 85561216.41341394], [30261, 85521555.77757517], [30513, 85635110.89674526], [30527, 85496093.83429927], [30541, 85393259.13431087], [30555, 85326293.92900278], [30569, 85326511.60389207], [30583, 85419584.50749978], [30597, 85386068.13228023], [30625, 85410025.53549886], [30639, 85638063.14833918], [30653, 85403203.29496692], [30667, 85418697.13564533], [30681, 85482864.85282357], [30695, 85304134.72592567], [30709, 85406001.98503235], [30723, 85471710.064892], [30737, 85444713.60180137], [30751, 85526117.3018471], [30765, 85839179.23260546], [30779, 85550813.93195266], [30793, 85570379.75277555], [30807, 85673909.02902758], [30821, 85687563.7306202], [30835, 85897560.44144379], [30849, 85607495.13404778], [30863, 85646125.59854567], [30877, 85632123.3809488], [30891, 85642531.05009432], [30905, 85582918.27231881], [30919, 85479741.14179748], [30933, 85588972.10536526], [30947, 85438395.32817358], [30961, 85500796.17152335], [30975, 85465159.5439984], [30989, 85554696.63202977], [31003, 85441330.1723054], [31017, 85688882.02339587], [31031, 85543777.672653], [31045, 85631417.74029648], [32095, 97630848.26909265], [32109, 97401971.96205814], [32123, 97495719.7272736], [32137, 97473928.46794467], [32151, 97334548.26040494], [32165, 97453007.45197205], [32179, 97149367.16453566], [32193, 97419857.74884589], [32207, 98912675.0245809], [32221, 100618848.53857498], [32235, 100533556.14241254], [32249, 101196368.69639432], [32263, 101057189.84883466], [32277, 100324893.9499224], [32305, 103044578.10930322], [32319, 108412451.20292754], [32333, 108486319.17670283], [32347, 108422308.1019307], [32361, 108459014.40448844], [32375, 108662326.28890747], [32389, 108494354.18991846], [32403, 108342775.38508616], [32417, 108448203.46704309], [32431, 108530261.39506906], [32445, 108457425.18591641], [32585, 103986104.6987915], [32599, 104050436.4457733], [32613, 104005542.40831292], [32627, 104208762.80464926], [32641, 104016589.04827581], [32655, 104046222.7816323], [32851, 105399582.3977443], [32865, 105319330.60857782], [32879, 105255644.6432689], [32893, 105260257.29011913], [32907, 105325658.4010713], [32921, 105298715.96945885], [32991, 105511683.17239869], [33005, 105336788.27980584], [33019, 105093746.09186979], [33033, 105317179.46616876], [33047, 105179528.21657114], [33061, 105624915.79457456], [33075, 105374314.71294686], [33089, 119660516.95507115], [33103, 133718294.4265088], [33117, 133897813.16867758], [33131, 133600800.50886075], [33145, 134137714.14988606], [33159, 134157256.25223818], [33187, 105911071.88683517], [33201, 105573554.7951231], [33215, 104521059.90976712], [33229, 101427678.37041637], [33243, 101391348.95776416], [33271, 97427115.38358016], [33299, 97414943.333719], [33313, 97427291.1414124], [33327, 97964394.67910087], [33341, 97923902.72993702], [33355, 98083953.1171127], [33369, 98349895.30591272], [33383, 99157681.55936436], [33397, 99615971.30477351], [33411, 99450714.67531563], [33425, 99611377.46648486], [33439, 100544505.41852163], [33453, 95544155.4607661], [33467, 95764489.19760434], [33523, 95745086.31948984], [33537, 96033688.43656802], [33551, 95149209.34600778], [33649, 94836994.08382617], [33705, 94387086.7683617], [33719, 94524372.00585726], [33733, 94566077.53092828], [33747, 94514847.72934103], [33761, 94431079.18493783], [33775, 94454991.27870494], [33803, 94384897.23003815], [33817, 94156120.29777533], [33831, 94232315.82628137], [33845, 94174697.81894428], [34041, 93789369.57207093], [34055, 94333561.9984041], [34069, 94239143.74899869], [34083, 94152943.2984151], [34125, 94076596.72670728], [34139, 94055773.65503156], [34153, 94115427.52061217], [34167, 94117271.21130712]] \ No newline at end of file +[[28511, 86322228.22703315], [29225, 83784833.90063383], [29239, 83574075.1213358], [29253, 83735503.7007549], [29267, 83840137.33567695], [29281, 83903502.19080393], [29295, 83869471.38821624], [29309, 83764978.94380853], [29323, 83682238.54209527], [29337, 83894906.92431034], [29351, 83390882.53012013], [29365, 83506060.62114188], [29379, 83303256.05169293], [29393, 83370723.09102903], [29407, 83291128.08360156], [29421, 83381708.0714557], [29435, 83758689.00583039], [29449, 83786685.52661566], [29463, 83716654.55315392], [29477, 83659694.52390799], [29547, 84108616.62260939], [29561, 83974536.19920045], [29575, 83225359.65100944], [29603, 84624733.20113254], [29617, 84779661.9123446], [29631, 84766313.16993459], [29645, 84854545.96562089], [29659, 84809417.39347352], [29673, 84685581.23090895], [29743, 84687877.4334884], [29757, 84659770.46317738], [29771, 84874590.72472982], [29785, 84715235.50556305], [29799, 84686551.34252182], [29813, 85009537.30736615], [29827, 84917794.17252877], [29841, 84845846.0691868], [29855, 84798704.42839448], [29869, 85158836.78390035], [30009, 84953443.55098847], [30023, 84945255.15640424], [30037, 85000656.61278176], [30051, 85197915.06962597], [30065, 85125254.58697408], [30079, 85091370.74890767], [30093, 85105255.01520963], [30107, 85054196.08038898], [30121, 85261486.34955876], [30135, 85136842.74454278], [30149, 85295138.82708241], [30163, 85500992.38114649], [30177, 85271436.6835587], [30191, 85547809.88512474], [30205, 85621660.17395443], [30219, 85412758.64040656], [30233, 85484393.15768304], [30247, 85561216.41341394], [30261, 85521555.77757517], [30513, 85635110.89674526], [30527, 85496093.83429927], [30541, 85393259.13431087], [30555, 85326293.92900278], [30569, 85326511.60389207], [30583, 85419584.50749978], [30597, 85386068.13228023], [30625, 85410025.53549886], [30639, 85638063.14833918], [30653, 85403203.29496692], [30667, 85418697.13564533], [30681, 85482864.85282357], [30695, 85304134.72592567], [30709, 85406001.98503235], [30723, 85471710.064892], [30737, 85444713.60180137], [30751, 85526117.3018471], [30765, 85839179.23260546], [30779, 85550813.93195266], [30793, 85570379.75277555], [30807, 85673909.02902758], [30821, 85687563.7306202], [30835, 85897560.44144379], [30849, 85607495.13404778], [30863, 85646125.59854567], [30877, 85632123.3809488], [30891, 85642531.05009432], [30905, 85582918.27231881], [30919, 85479741.14179748], [30933, 85588972.10536526], [30947, 85438395.32817358], [30961, 85500796.17152335], [30975, 85465159.5439984], [30989, 85554696.63202977], [31003, 85441330.1723054], [31017, 85688882.02339587], [31031, 85543777.672653], [31045, 85631417.74029648], [32095, 97630848.26909265], [32109, 97401971.96205814], [32123, 97495719.7272736], [32137, 97473928.46794467], [32151, 97334548.26040494], [32165, 97453007.45197205], [32179, 97149367.16453566], [32193, 97419857.74884589], [32207, 98912675.0245809], [32221, 100618848.53857498], [32235, 100533556.14241254], [32249, 101196368.69639432], [32263, 101057189.84883466], [32277, 100324893.9499224], [32305, 103044578.10930322], [32319, 108412451.20292754], [32333, 108486319.17670283], [32347, 108422308.1019307], [32361, 108459014.40448844], [32375, 108662326.28890747], [32389, 108494354.18991846], [32403, 108342775.38508616], [32417, 108448203.46704309], [32431, 108530261.39506906], [32445, 108457425.18591641], [32585, 103986104.6987915], [32599, 104050436.4457733], [32613, 104005542.40831292], [32627, 104208762.80464926], [32641, 104016589.04827581], [32655, 104046222.7816323], [32851, 105399582.3977443], [32865, 105319330.60857782], [32879, 105255644.6432689], [32893, 105260257.29011913], [32907, 105325658.4010713], [32921, 105298715.96945885], [32991, 105511683.17239869], [33005, 105336788.27980584], [33019, 105093746.09186979], [33033, 105317179.46616876], [33047, 105179528.21657114], [33061, 105624915.79457456], [33075, 105374314.71294686], [33089, 119660516.95507115], [33103, 133718294.4265088], [33117, 133897813.16867758], [33131, 133600800.50886075], [33145, 134137714.14988606], [33159, 134157256.25223818], [33187, 105911071.88683517], [33201, 105573554.7951231], [33215, 104521059.90976712], [33229, 101427678.37041637], [33243, 101391348.95776416], [33271, 97427115.38358016], [33299, 97414943.333719], [33313, 97427291.1414124], [33327, 97964394.67910087], [33341, 97923902.72993702], [33355, 98083953.1171127], [33369, 98349895.30591272], [33383, 99157681.55936436], [33397, 99615971.30477351], [33411, 99450714.67531563], [33425, 99611377.46648486], [33439, 100544505.41852163], [33453, 95544155.4607661], [33467, 95764489.19760434], [33523, 95745086.31948984], [33537, 96033688.43656802], [33551, 95149209.34600778], [33649, 94836994.08382617], [33705, 94387086.7683617], [33719, 94524372.00585726], [33733, 94566077.53092828], [33747, 94514847.72934103], [33761, 94431079.18493783], [33775, 94454991.27870494], [33803, 94384897.23003815], [33817, 94156120.29777533], [33831, 94232315.82628137], [33845, 94174697.81894428], [34041, 93789369.57207093], [34055, 94333561.9984041], [34069, 94239143.74899869], [34083, 94152943.2984151], [34125, 94076596.72670728], [34139, 94055773.65503156], [34153, 94115427.52061217], [34167, 94061675.1667185]] \ No newline at end of file diff --git a/graphs/summary/model_selection.GridSearchBenchmark.peakmem_predict.json b/graphs/summary/model_selection.GridSearchBenchmark.peakmem_predict.json index e57dbae0d8..da60c1d7d1 100644 --- a/graphs/summary/model_selection.GridSearchBenchmark.peakmem_predict.json +++ b/graphs/summary/model_selection.GridSearchBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28511, 80171007.99999999], [29225, 77565938.91408244], [29239, 77434869.969102], [29253, 77612364.47434616], [29267, 77745143.55917716], [29281, 77789182.67898796], [29295, 77791225.91569032], [29309, 77680630.9152739], [29323, 77619195.66088189], [29337, 77841065.92122325], [29351, 77201407.94557025], [29365, 77193209.0451021], [29379, 77175807.93207711], [29393, 77281277.38112038], [29407, 77147124.58663388], [29421, 77216754.11124802], [29435, 77598034.1525814], [29449, 77630122.07292205], [29463, 77565951.94581547], [29477, 77555711.9729594], [29547, 77887487.9730746], [29561, 77836968.2490866], [29575, 77131776.0], [29603, 78288895.97321264], [29617, 78424064.0], [29631, 78520319.99999999], [29645, 78490623.93316028], [29659, 78415872.0], [29673, 78324394.63989139], [29743, 78328831.9866203], [29757, 78470143.82621709], [29771, 78460927.98396811], [29785, 78401535.97325107], [29799, 78461745.63016462], [29813, 78696959.96665362], [29827, 78738431.98669404], [29841, 78563327.94659713], [29855, 78594047.89326662], [29869, 78768128.0], [30009, 78503935.973286], [30023, 78538751.89319132], [30037, 78581759.98220508], [30051, 78727151.35110773], [30065, 78680063.89338332], [30079, 78773686.83431955], [30093, 78769142.29188114], [30107, 78652074.65778495], [30121, 78815231.98222823], [30135, 78735359.89345804], [30149, 78871551.98669957], [30163, 79138133.28910923], [30177, 79013887.94682729], [30191, 79153151.98674229], [30205, 79165439.99115556], [30219, 79011430.39469472], [30233, 79175679.94704726], [30247, 79174655.9072453], [30261, 79029247.8805333], [30513, 79234246.11870041], [30527, 79054847.96286461], [30541, 78995455.99999999], [30555, 78942207.50419836], [30569, 78935551.82050967], [30583, 79004671.93354666], [30597, 79032319.97346464], [30625, 79140179.99241112], [30639, 79142910.9400683], [30653, 78989310.54858941], [30667, 78964735.86724263], [30681, 79108093.02432096], [30695, 78925823.57486117], [30709, 79058944.0], [30723, 79147008.0], [30737, 79090175.96686393], [30751, 79121919.99337046], [30765, 79466495.96471459], [30779, 79126528.00000001], [30793, 79067816.91935715], [30807, 79160319.88079779], [30821, 79237119.89413285], [30835, 79482880.0], [30849, 79218687.97352704], [30863, 79231999.9867813], [30877, 79335423.97356601], [30891, 79323136.0], [30905, 79167487.89403974], [30919, 79050751.92042586], [30933, 79173631.973512], [30947, 79199231.93372566], [30961, 79214591.9558702], [30975, 79215615.93380736], [30989, 79269887.96467078], [31003, 79349760.0], [31017, 79425536.0], [31031, 79083519.97348182], [31045, 79309311.9933978], [32095, 91131904.00000001], [32109, 91210751.98847702], [32123, 91227135.96552885], [32137, 91254101.32568066], [32151, 91173887.98850808], [32165, 91195381.35034736], [32179, 90904575.97693017], [32193, 91256831.97701924], [32207, 92448255.61342812], [32221, 94053714.56039917], [32235, 94121984.0], [32249, 94216192.00000001], [32263, 94132633.57325962], [32277, 93818879.98508029], [32305, 96524970.65236594], [32319, 101995861.31962764], [32333, 101935103.9794266], [32347, 101990911.97426297], [32361, 102081023.96402684], [32375, 102287359.97949745], [32389, 101949435.8842442], [32403, 101906422.92457607], [32417, 101852495.14398532], [32431, 102062079.9794522], [32445, 102207488.00000001], [32585, 97370794.65948902], [32599, 97418581.31180608], [32613, 97346218.63078739], [32627, 97509376.0], [32641, 97257471.97843707], [32655, 97498453.33333333], [32851, 98372266.59551935], [32865, 98410495.96805167], [32879, 98351098.79995345], [32893, 98502655.97870968], [32907, 98479445.29781906], [32921, 98463743.95738305], [32991, 98435071.99999999], [33005, 98535422.95712177], [33019, 98193408.0], [33033, 98507773.90122104], [33047, 98486271.97870614], [33061, 98785280.0], [33075, 98578431.99999999], [33089, 112547839.86735322], [33103, 126423722.61691509], [33117, 126624767.95864302], [33131, 126273535.916839], [33145, 126795775.93384157], [33159, 126838783.983466], [33187, 98869248.00000001], [33201, 98734079.97875959], [33215, 97692633.1220869], [33229, 94759223.29258674], [33243, 95001002.20362122], [33271, 91430911.90825197], [33299, 91539455.97709018], [33313, 91532287.97714694], [33327, 91952127.98861387], [33341, 91979262.51536286], [33355, 92291071.96971041], [33369, 92336782.42259856], [33383, 92912979.39947452], [33397, 93268991.98874947], [33411, 93061114.23098575], [33425, 93284349.12649617], [33439, 94322685.15543202], [33453, 89464825.99908413], [33467, 89489408.0], [33523, 89457654.0556908], [33537, 89643007.92985816], [33551, 88900266.51720467], [33649, 88375295.90507971], [33705, 87844863.40316601], [33719, 88028148.71322638], [33733, 87994367.90466881], [33747, 88004607.97616994], [33761, 87785472.00000001], [33775, 88051712.00000001], [33803, 88129535.99999999], [33817, 87564287.88023505], [33831, 87720618.62683944], [33845, 87662591.99999999], [34041, 87544792.71741244], [34055, 87810730.62683572], [34069, 87794346.62696238], [34083, 87721983.90437278], [34125, 87704917.33333333], [34139, 87748583.52686024], [34153, 87768405.32540216], [34167, 87720959.98803288]] \ No newline at end of file +[[28511, 80171007.99999999], [29225, 77565938.91408244], [29239, 77434869.969102], [29253, 77612364.47434616], [29267, 77745143.55917716], [29281, 77789182.67898796], [29295, 77791225.91569032], [29309, 77680630.9152739], [29323, 77619195.66088189], [29337, 77841065.92122325], [29351, 77201407.94557025], [29365, 77193209.0451021], [29379, 77175807.93207711], [29393, 77281277.38112038], [29407, 77147124.58663388], [29421, 77216754.11124802], [29435, 77598034.1525814], [29449, 77630122.07292205], [29463, 77565951.94581547], [29477, 77555711.9729594], [29547, 77887487.9730746], [29561, 77836968.2490866], [29575, 77131776.0], [29603, 78288895.97321264], [29617, 78424064.0], [29631, 78520319.99999999], [29645, 78490623.93316028], [29659, 78415872.0], [29673, 78324394.63989139], [29743, 78328831.9866203], [29757, 78470143.82621709], [29771, 78460927.98396811], [29785, 78401535.97325107], [29799, 78461745.63016462], [29813, 78696959.96665362], [29827, 78738431.98669404], [29841, 78563327.94659713], [29855, 78594047.89326662], [29869, 78768128.0], [30009, 78503935.973286], [30023, 78538751.89319132], [30037, 78581759.98220508], [30051, 78727151.35110773], [30065, 78680063.89338332], [30079, 78773686.83431955], [30093, 78769142.29188114], [30107, 78652074.65778495], [30121, 78815231.98222823], [30135, 78735359.89345804], [30149, 78871551.98669957], [30163, 79138133.28910923], [30177, 79013887.94682729], [30191, 79153151.98674229], [30205, 79165439.99115556], [30219, 79011430.39469472], [30233, 79175679.94704726], [30247, 79174655.9072453], [30261, 79029247.8805333], [30513, 79234246.11870041], [30527, 79054847.96286461], [30541, 78995455.99999999], [30555, 78942207.50419836], [30569, 78935551.82050967], [30583, 79004671.93354666], [30597, 79032319.97346464], [30625, 79140179.99241112], [30639, 79142910.9400683], [30653, 78989310.54858941], [30667, 78964735.86724263], [30681, 79108093.02432096], [30695, 78925823.57486117], [30709, 79058944.0], [30723, 79147008.0], [30737, 79090175.96686393], [30751, 79121919.99337046], [30765, 79466495.96471459], [30779, 79126528.00000001], [30793, 79067816.91935715], [30807, 79160319.88079779], [30821, 79237119.89413285], [30835, 79482880.0], [30849, 79218687.97352704], [30863, 79231999.9867813], [30877, 79335423.97356601], [30891, 79323136.0], [30905, 79167487.89403974], [30919, 79050751.92042586], [30933, 79173631.973512], [30947, 79199231.93372566], [30961, 79214591.9558702], [30975, 79215615.93380736], [30989, 79269887.96467078], [31003, 79349760.0], [31017, 79425536.0], [31031, 79083519.97348182], [31045, 79309311.9933978], [32095, 91131904.00000001], [32109, 91210751.98847702], [32123, 91227135.96552885], [32137, 91254101.32568066], [32151, 91173887.98850808], [32165, 91195381.35034736], [32179, 90904575.97693017], [32193, 91256831.97701924], [32207, 92448255.61342812], [32221, 94053714.56039917], [32235, 94121984.0], [32249, 94216192.00000001], [32263, 94132633.57325962], [32277, 93818879.98508029], [32305, 96524970.65236594], [32319, 101995861.31962764], [32333, 101935103.9794266], [32347, 101990911.97426297], [32361, 102081023.96402684], [32375, 102287359.97949745], [32389, 101949435.8842442], [32403, 101906422.92457607], [32417, 101852495.14398532], [32431, 102062079.9794522], [32445, 102207488.00000001], [32585, 97370794.65948902], [32599, 97418581.31180608], [32613, 97346218.63078739], [32627, 97509376.0], [32641, 97257471.97843707], [32655, 97498453.33333333], [32851, 98372266.59551935], [32865, 98410495.96805167], [32879, 98351098.79995345], [32893, 98502655.97870968], [32907, 98479445.29781906], [32921, 98463743.95738305], [32991, 98435071.99999999], [33005, 98535422.95712177], [33019, 98193408.0], [33033, 98507773.90122104], [33047, 98486271.97870614], [33061, 98785280.0], [33075, 98578431.99999999], [33089, 112547839.86735322], [33103, 126423722.61691509], [33117, 126624767.95864302], [33131, 126273535.916839], [33145, 126795775.93384157], [33159, 126838783.983466], [33187, 98869248.00000001], [33201, 98734079.97875959], [33215, 97692633.1220869], [33229, 94759223.29258674], [33243, 95001002.20362122], [33271, 91430911.90825197], [33299, 91539455.97709018], [33313, 91532287.97714694], [33327, 91952127.98861387], [33341, 91979262.51536286], [33355, 92291071.96971041], [33369, 92336782.42259856], [33383, 92912979.39947452], [33397, 93268991.98874947], [33411, 93061114.23098575], [33425, 93284349.12649617], [33439, 94322685.15543202], [33453, 89464825.99908413], [33467, 89489408.0], [33523, 89457654.0556908], [33537, 89643007.92985816], [33551, 88900266.51720467], [33649, 88375295.90507971], [33705, 87844863.40316601], [33719, 88028148.71322638], [33733, 87994367.90466881], [33747, 88004607.97616994], [33761, 87785472.00000001], [33775, 88051712.00000001], [33803, 88129535.99999999], [33817, 87564287.88023505], [33831, 87720618.62683944], [33845, 87662591.99999999], [34041, 87544792.71741244], [34055, 87810730.62683572], [34069, 87794346.62696238], [34083, 87721983.90437278], [34125, 87704917.33333333], [34139, 87748583.52686024], [34153, 87768405.32540216], [34167, 87659724.5553163]] \ No newline at end of file diff --git a/graphs/summary/model_selection.GridSearchBenchmark.time_fit.json b/graphs/summary/model_selection.GridSearchBenchmark.time_fit.json index e550b37810..6c08ff93ad 100644 --- a/graphs/summary/model_selection.GridSearchBenchmark.time_fit.json +++ b/graphs/summary/model_selection.GridSearchBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 130.02699368040066], [29225, 140.72616560182152], [29239, 139.74785221041748], [29253, 130.29682540441902], [29267, 129.77344168744713], [29281, 129.84920253582365], [29295, 130.09071207538227], [29309, 130.77973955487573], [29323, 129.84384835471107], [29337, 130.18204393339724], [29351, 129.9347388377067], [29365, 130.17276017751132], [29379, 130.93774844389833], [29393, 129.82655006817086], [29407, 129.69923896768114], [29421, 130.17271296107145], [29435, 130.60140721554416], [29449, 168.78424943690376], [29463, 161.80173277542158], [29477, 158.0774909878197], [29547, 159.76791434814632], [29561, 153.93390870036953], [29575, 145.76449727162483], [29603, 138.36633802192864], [29617, 144.8870251198498], [29631, 137.9962729981885], [29645, 145.47872769341086], [29659, 144.82010254610543], [29673, 142.39141287508025], [29743, 145.158036236792], [29757, 144.6819808958391], [29771, 144.00240841058888], [29785, 158.8224007465796], [29799, 137.62062229126667], [29813, 137.5400337026072], [29827, 137.56056279097206], [29841, 143.42705794422378], [29855, 136.83079914124042], [29869, 138.17187687675204], [30009, 140.38065574060846], [30023, 138.87596673981557], [30037, 140.8655620740135], [30051, 141.78844887868246], [30065, 138.19249292259045], [30079, 140.5831088387235], [30093, 141.30545238032266], [30107, 138.9008174768464], [30121, 138.45747270269018], [30135, 143.07209494082986], [30149, 139.0231604200527], [30163, 138.35277194787344], [30177, 139.86843124334746], [30191, 137.93813554058062], [30205, 138.23725429714796], [30219, 140.10988634592633], [30233, 142.8288477540615], [30247, 141.61721196336384], [30261, 136.61355283362133], [30513, 139.09462986875678], [30527, 141.0429739433974], [30541, 138.81450749256044], [30555, 138.75112807771418], [30569, 139.50134761410587], [30583, 138.14728952194912], [30597, 135.2508760918417], [30625, 143.50284255187702], [30639, 139.6687027852381], [30653, 139.6786385934653], [30667, 138.2290393721578], [30681, 142.34605064423326], [30695, 137.65622648451253], [30709, 138.25739011501], [30723, 136.33472561908687], [30737, 138.13351127511214], [30751, 139.62949307422252], [30765, 136.30995400982297], [30779, 136.8912450991393], [30793, 139.4762681049542], [30807, 141.66551640953645], [30821, 140.0214001539435], [30835, 140.30669701052284], [30849, 139.16118926371726], [30863, 140.09800021589578], [30877, 138.70918362061053], [30891, 147.05003546262097], [30905, 140.49079537287733], [30919, 137.88093501407909], [30933, 126.78374419743733], [30947, 125.57494024371877], [30961, 124.39568941401853], [30975, 130.52629772785923], [30989, 127.59882692800755], [31003, 132.6279486807345], [31017, 129.66862739037364], [31031, 138.25366274547463], [31045, 128.36409749863307], [32095, 148.6316427810283], [32109, 144.2529775092982], [32123, 144.11212722085304], [32137, 146.46486160880218], [32151, 145.87809418572903], [32165, 142.81257764529045], [32179, 141.64290441359478], [32193, 147.54406561488986], [32207, 145.31624663470194], [32221, 146.92957465392172], [32235, 147.8299321996033], [32249, 143.43662766444655], [32263, 143.43671860122294], [32277, 142.53757795562427], [32305, 143.25121408527613], [32319, 140.71927865394323], [32333, 141.9315586181523], [32347, 146.11327753422594], [32361, 141.87110122788377], [32375, 137.73323784957768], [32389, 143.40845137281184], [32403, 142.61843278317735], [32417, 142.8122165409898], [32431, 192.6773195940823], [32445, 190.48027161225505], [32585, 209.8248927684327], [32599, 282.4758130472222], [32613, 279.60235023799356], [32627, 313.05573614338437], [32641, 312.3120151542661], [32655, 302.46513680562435], [32851, 278.61463896410334], [32865, 279.8224456976982], [32879, 279.9495356439573], [32893, 271.4502032344498], [32907, 278.17585337660745], [32921, 280.7795967829493], [32991, 280.2572166905198], [33005, 288.6509967767268], [33019, 287.84218761009515], [33033, 276.2511224298179], [33047, 273.13814204129244], [33061, 278.7940033168958], [33075, 287.6717096842384], [33089, 277.5036614534624], [33103, 277.61263125977445], [33117, 287.3564821874738], [33131, 280.632143130278], [33145, 277.41807084215947], [33159, 280.6312406291813], [33187, 285.103511159649], [33201, 281.31547714540045], [33215, 266.1145925476197], [33229, 231.86755186954355], [33243, 233.4676717133439], [33271, 199.04612453944875], [33299, 234.6878322257866], [33313, 193.71658587752913], [33327, 189.21111272256994], [33341, 190.569748167682], [33355, 195.5491603964937], [33369, 193.81395658991212], [33383, 189.50337685689775], [33397, 189.58162701963522], [33411, 189.16281482105532], [33425, 191.71618179503557], [33439, 189.33634763481302], [33453, 189.2814165647172], [33467, 204.6939115938984], [33523, 190.8719403121742], [33537, 194.9702292183254], [33551, 190.79947572759102], [33649, 506.21993542552343], [33705, 532.4946831308506], [33719, 513.0169506412936], [33733, 198.68960938787603], [33747, 202.1182387437741], [33761, 210.05509216728598], [33775, 196.6556450630268], [33803, 188.16594898382124], [33817, 195.90075906694477], [33831, 194.2916297698497], [33845, 200.91125431446147], [34041, 496.76084496394645], [34055, 523.2108530028578], [34069, 498.8978302035912], [34083, 497.67597783930745], [34125, 193.30081305675185], [34139, 195.58484909064825], [34153, 194.447186173336], [34167, 190.5446425132153]] \ No newline at end of file +[[28511, 130.02699368040066], [29225, 140.72616560182152], [29239, 139.74785221041748], [29253, 130.29682540441902], [29267, 129.77344168744713], [29281, 129.84920253582365], [29295, 130.09071207538227], [29309, 130.77973955487573], [29323, 129.84384835471107], [29337, 130.18204393339724], [29351, 129.9347388377067], [29365, 130.17276017751132], [29379, 130.93774844389833], [29393, 129.82655006817086], [29407, 129.69923896768114], [29421, 130.17271296107145], [29435, 130.60140721554416], [29449, 168.78424943690376], [29463, 161.80173277542158], [29477, 158.0774909878197], [29547, 159.76791434814632], [29561, 153.93390870036953], [29575, 145.76449727162483], [29603, 138.36633802192864], [29617, 144.8870251198498], [29631, 137.9962729981885], [29645, 145.47872769341086], [29659, 144.82010254610543], [29673, 142.39141287508025], [29743, 145.158036236792], [29757, 144.6819808958391], [29771, 144.00240841058888], [29785, 158.8224007465796], [29799, 137.62062229126667], [29813, 137.5400337026072], [29827, 137.56056279097206], [29841, 143.42705794422378], [29855, 136.83079914124042], [29869, 138.17187687675204], [30009, 140.38065574060846], [30023, 138.87596673981557], [30037, 140.8655620740135], [30051, 141.78844887868246], [30065, 138.19249292259045], [30079, 140.5831088387235], [30093, 141.30545238032266], [30107, 138.9008174768464], [30121, 138.45747270269018], [30135, 143.07209494082986], [30149, 139.0231604200527], [30163, 138.35277194787344], [30177, 139.86843124334746], [30191, 137.93813554058062], [30205, 138.23725429714796], [30219, 140.10988634592633], [30233, 142.8288477540615], [30247, 141.61721196336384], [30261, 136.61355283362133], [30513, 139.09462986875678], [30527, 141.0429739433974], [30541, 138.81450749256044], [30555, 138.75112807771418], [30569, 139.50134761410587], [30583, 138.14728952194912], [30597, 135.2508760918417], [30625, 143.50284255187702], [30639, 139.6687027852381], [30653, 139.6786385934653], [30667, 138.2290393721578], [30681, 142.34605064423326], [30695, 137.65622648451253], [30709, 138.25739011501], [30723, 136.33472561908687], [30737, 138.13351127511214], [30751, 139.62949307422252], [30765, 136.30995400982297], [30779, 136.8912450991393], [30793, 139.4762681049542], [30807, 141.66551640953645], [30821, 140.0214001539435], [30835, 140.30669701052284], [30849, 139.16118926371726], [30863, 140.09800021589578], [30877, 138.70918362061053], [30891, 147.05003546262097], [30905, 140.49079537287733], [30919, 137.88093501407909], [30933, 126.78374419743733], [30947, 125.57494024371877], [30961, 124.39568941401853], [30975, 130.52629772785923], [30989, 127.59882692800755], [31003, 132.6279486807345], [31017, 129.66862739037364], [31031, 138.25366274547463], [31045, 128.36409749863307], [32095, 148.6316427810283], [32109, 144.2529775092982], [32123, 144.11212722085304], [32137, 146.46486160880218], [32151, 145.87809418572903], [32165, 142.81257764529045], [32179, 141.64290441359478], [32193, 147.54406561488986], [32207, 145.31624663470194], [32221, 146.92957465392172], [32235, 147.8299321996033], [32249, 143.43662766444655], [32263, 143.43671860122294], [32277, 142.53757795562427], [32305, 143.25121408527613], [32319, 140.71927865394323], [32333, 141.9315586181523], [32347, 146.11327753422594], [32361, 141.87110122788377], [32375, 137.73323784957768], [32389, 143.40845137281184], [32403, 142.61843278317735], [32417, 142.8122165409898], [32431, 192.6773195940823], [32445, 190.48027161225505], [32585, 209.8248927684327], [32599, 282.4758130472222], [32613, 279.60235023799356], [32627, 313.05573614338437], [32641, 312.3120151542661], [32655, 302.46513680562435], [32851, 278.61463896410334], [32865, 279.8224456976982], [32879, 279.9495356439573], [32893, 271.4502032344498], [32907, 278.17585337660745], [32921, 280.7795967829493], [32991, 280.2572166905198], [33005, 288.6509967767268], [33019, 287.84218761009515], [33033, 276.2511224298179], [33047, 273.13814204129244], [33061, 278.7940033168958], [33075, 287.6717096842384], [33089, 277.5036614534624], [33103, 277.61263125977445], [33117, 287.3564821874738], [33131, 280.632143130278], [33145, 277.41807084215947], [33159, 280.6312406291813], [33187, 285.103511159649], [33201, 281.31547714540045], [33215, 266.1145925476197], [33229, 231.86755186954355], [33243, 233.4676717133439], [33271, 199.04612453944875], [33299, 234.6878322257866], [33313, 193.71658587752913], [33327, 189.21111272256994], [33341, 190.569748167682], [33355, 195.5491603964937], [33369, 193.81395658991212], [33383, 189.50337685689775], [33397, 189.58162701963522], [33411, 189.16281482105532], [33425, 191.71618179503557], [33439, 189.33634763481302], [33453, 189.2814165647172], [33467, 204.6939115938984], [33523, 190.8719403121742], [33537, 194.9702292183254], [33551, 190.79947572759102], [33649, 506.21993542552343], [33705, 532.4946831308506], [33719, 513.0169506412936], [33733, 198.68960938787603], [33747, 202.1182387437741], [33761, 210.05509216728598], [33775, 196.6556450630268], [33803, 188.16594898382124], [33817, 195.90075906694477], [33831, 194.2916297698497], [33845, 200.91125431446147], [34041, 496.76084496394645], [34055, 523.2108530028578], [34069, 498.8978302035912], [34083, 497.67597783930745], [34125, 193.30081305675185], [34139, 195.58484909064825], [34153, 194.447186173336], [34167, 189.89783727889514]] \ No newline at end of file diff --git a/graphs/summary/model_selection.GridSearchBenchmark.time_predict.json b/graphs/summary/model_selection.GridSearchBenchmark.time_predict.json index 190d3f7e9e..3177fd51f5 100644 --- a/graphs/summary/model_selection.GridSearchBenchmark.time_predict.json +++ b/graphs/summary/model_selection.GridSearchBenchmark.time_predict.json @@ -1 +1 @@ -[[28511, 0.04812026756023343], [29225, 0.06284853944540783], [29239, 0.05683422191245191], [29253, 0.04837983229252075], [29267, 0.04807506699730135], [29281, 0.04814558429982324], [29295, 0.04821085877647113], [29309, 0.0481297742241438], [29323, 0.04802633809749721], [29337, 0.048145718018632155], [29351, 0.048220511417840124], [29365, 0.04802839543700679], [29379, 0.04812131382396743], [29393, 0.04806237647221678], [29407, 0.048013303288949365], [29421, 0.048323039845017866], [29435, 0.04811171409709819], [29449, 0.07396662133650052], [29463, 0.06664888877786172], [29477, 0.061831632237644034], [29547, 0.07499014898299285], [29561, 0.06573475655185665], [29575, 0.057383374430636444], [29603, 0.05966231769483819], [29617, 0.061796556008096096], [29631, 0.05497575946733863], [29645, 0.055028446583371804], [29659, 0.06230784019533643], [29673, 0.05999299361974947], [29743, 0.06176618388178472], [29757, 0.06295985075081252], [29771, 0.06070043669986911], [29785, 0.05896752798147935], [29799, 0.059288622585993246], [29813, 0.07855244745022044], [29827, 0.07810992462657992], [29841, 0.07856826075581505], [29855, 0.07889103700454828], [29869, 0.0735056272103194], [30009, 0.07308199899481213], [30023, 0.07755122551357571], [30037, 0.07862543389795952], [30051, 0.08092288449908733], [30065, 0.08038592899664566], [30079, 0.0778923808444522], [30093, 0.07583507370304768], [30107, 0.08077007488356125], [30121, 0.08049021227324271], [30135, 0.08047774861947102], [30149, 0.08067789231809666], [30163, 0.08062504562503486], [30177, 0.08038442908337612], [30191, 0.08066131124069915], [30205, 0.08064878083520009], [30219, 0.07865490900962505], [30233, 0.08117418170645055], [30247, 0.08012575002045055], [30261, 0.07502436226671591], [30513, 0.07911080693588021], [30527, 0.0755561515476936], [30541, 0.0792481668707679], [30555, 0.07981780515225241], [30569, 0.0798603644673118], [30583, 0.07970963879116952], [30597, 0.0795042364374649], [30625, 0.0734067095487889], [30639, 0.07931112288605947], [30653, 0.07659307438127176], [30667, 0.07921800075966687], [30681, 0.07941840004455299], [30695, 0.07873287960830681], [30709, 0.07915439235757737], [30723, 0.07989470219599457], [30737, 0.07987997984981257], [30751, 0.07712855554652175], [30765, 0.07921258880320145], [30779, 0.07836603265520381], [30793, 0.07864967614099681], [30807, 0.07837079699495628], [30821, 0.07865461025653622], [30835, 0.07893312121006642], [30849, 0.07857129976289076], [30863, 0.07920567569572735], [30877, 0.06911729096180333], [30891, 0.0782444516158252], [30905, 0.06876659232955318], [30919, 0.07857797440179824], [30933, 0.07858841986577453], [30947, 0.0779078723512279], [30961, 0.07834059922185253], [30975, 0.07900786316395687], [30989, 0.07604332169835873], [31003, 0.07924824130366638], [31017, 0.078289213128918], [31031, 0.07851463164494574], [31045, 0.07837923053842172], [32095, 0.08024929170281277], [32109, 0.07990537107914075], [32123, 0.07976798703280974], [32137, 0.08022714371071527], [32151, 0.07039135907646753], [32165, 0.07890732587300217], [32179, 0.07896672667175757], [32193, 0.06916427109762112], [32207, 0.07786788996474582], [32221, 0.07691040913508575], [32235, 0.07707840328897723], [32249, 0.0584865265494294], [32263, 0.0765248256579203], [32277, 0.07059121913494483], [32305, 0.0702676019862617], [32319, 0.07518940826371474], [32333, 0.07576524782809668], [32347, 0.07572582768501154], [32361, 0.07512610971714223], [32375, 0.07605968274098616], [32389, 0.0712843959600892], [32403, 0.0764038768173557], [32417, 0.07602582483101653], [32431, 0.07488072877077342], [32445, 0.07510483520703914], [32585, 0.07539632126172456], [32599, 0.0751332232281892], [32613, 0.07441422522510836], [32627, 0.07492612938761199], [32641, 0.06896549392333637], [32655, 0.0745499562674074], [32851, 0.07701514665744529], [32865, 0.07654082463870596], [32879, 0.07663320438837952], [32893, 0.06773422046439032], [32907, 0.07096584779935097], [32921, 0.0770478217479258], [32991, 0.0770766489667239], [33005, 0.07655270419145899], [33019, 0.07653124226841017], [33033, 0.06792001235181987], [33047, 0.07642338557764843], [33061, 0.07256157761550601], [33075, 0.0762530298205735], [33089, 0.07732028449260378], [33103, 0.07719024904994477], [33117, 0.07678458685483039], [33131, 0.07672721631450713], [33145, 0.07623547425658664], [33159, 0.07775103821660749], [33187, 0.07703586938574755], [33201, 0.07231737028498596], [33215, 0.06756971834979218], [33229, 0.0772998467707892], [33243, 0.07461800072439186], [33271, 0.07780424573838425], [33299, 0.07619977373605957], [33313, 0.07089219593216373], [33327, 0.07134814398032785], [33341, 0.06908612766116917], [33355, 0.07115972131790867], [33369, 0.07114893074328761], [33383, 0.06630195483332325], [33397, 0.07173794433517261], [33411, 0.07112507307850924], [33425, 0.07189155991655617], [33439, 0.0717247057365586], [33453, 0.06920855902143347], [33467, 0.0689248533757127], [33523, 0.06775363372803236], [33537, 0.06834572494725626], [33551, 0.06874699455559195], [33649, 0.06984538783576781], [33705, 0.07056080570070422], [33719, 0.0699512840514869], [33733, 0.06925855192194479], [33747, 0.06310249053297598], [33761, 0.0688335118257124], [33775, 0.06812343321974117], [33803, 0.0689549249818263], [33817, 0.06879872607922918], [33831, 0.06841205079054395], [33845, 0.06854860159412794], [34041, 0.07026241339176657], [34055, 0.07045472156964255], [34069, 0.06425752777906552], [34083, 0.07052261780600481], [34125, 0.07036135961613642], [34139, 0.07117666582148979], [34153, 0.0710789475269128], [34167, 0.06901023908372565]] \ No newline at end of file +[[28511, 0.04812026756023343], [29225, 0.06284853944540783], [29239, 0.05683422191245191], [29253, 0.04837983229252075], [29267, 0.04807506699730135], [29281, 0.04814558429982324], [29295, 0.04821085877647113], [29309, 0.0481297742241438], [29323, 0.04802633809749721], [29337, 0.048145718018632155], [29351, 0.048220511417840124], [29365, 0.04802839543700679], [29379, 0.04812131382396743], [29393, 0.04806237647221678], [29407, 0.048013303288949365], [29421, 0.048323039845017866], [29435, 0.04811171409709819], [29449, 0.07396662133650052], [29463, 0.06664888877786172], [29477, 0.061831632237644034], [29547, 0.07499014898299285], [29561, 0.06573475655185665], [29575, 0.057383374430636444], [29603, 0.05966231769483819], [29617, 0.061796556008096096], [29631, 0.05497575946733863], [29645, 0.055028446583371804], [29659, 0.06230784019533643], [29673, 0.05999299361974947], [29743, 0.06176618388178472], [29757, 0.06295985075081252], [29771, 0.06070043669986911], [29785, 0.05896752798147935], [29799, 0.059288622585993246], [29813, 0.07855244745022044], [29827, 0.07810992462657992], [29841, 0.07856826075581505], [29855, 0.07889103700454828], [29869, 0.0735056272103194], [30009, 0.07308199899481213], [30023, 0.07755122551357571], [30037, 0.07862543389795952], [30051, 0.08092288449908733], [30065, 0.08038592899664566], [30079, 0.0778923808444522], [30093, 0.07583507370304768], [30107, 0.08077007488356125], [30121, 0.08049021227324271], [30135, 0.08047774861947102], [30149, 0.08067789231809666], [30163, 0.08062504562503486], [30177, 0.08038442908337612], [30191, 0.08066131124069915], [30205, 0.08064878083520009], [30219, 0.07865490900962505], [30233, 0.08117418170645055], [30247, 0.08012575002045055], [30261, 0.07502436226671591], [30513, 0.07911080693588021], [30527, 0.0755561515476936], [30541, 0.0792481668707679], [30555, 0.07981780515225241], [30569, 0.0798603644673118], [30583, 0.07970963879116952], [30597, 0.0795042364374649], [30625, 0.0734067095487889], [30639, 0.07931112288605947], [30653, 0.07659307438127176], [30667, 0.07921800075966687], [30681, 0.07941840004455299], [30695, 0.07873287960830681], [30709, 0.07915439235757737], [30723, 0.07989470219599457], [30737, 0.07987997984981257], [30751, 0.07712855554652175], [30765, 0.07921258880320145], [30779, 0.07836603265520381], [30793, 0.07864967614099681], [30807, 0.07837079699495628], [30821, 0.07865461025653622], [30835, 0.07893312121006642], [30849, 0.07857129976289076], [30863, 0.07920567569572735], [30877, 0.06911729096180333], [30891, 0.0782444516158252], [30905, 0.06876659232955318], [30919, 0.07857797440179824], [30933, 0.07858841986577453], [30947, 0.0779078723512279], [30961, 0.07834059922185253], [30975, 0.07900786316395687], [30989, 0.07604332169835873], [31003, 0.07924824130366638], [31017, 0.078289213128918], [31031, 0.07851463164494574], [31045, 0.07837923053842172], [32095, 0.08024929170281277], [32109, 0.07990537107914075], [32123, 0.07976798703280974], [32137, 0.08022714371071527], [32151, 0.07039135907646753], [32165, 0.07890732587300217], [32179, 0.07896672667175757], [32193, 0.06916427109762112], [32207, 0.07786788996474582], [32221, 0.07691040913508575], [32235, 0.07707840328897723], [32249, 0.0584865265494294], [32263, 0.0765248256579203], [32277, 0.07059121913494483], [32305, 0.0702676019862617], [32319, 0.07518940826371474], [32333, 0.07576524782809668], [32347, 0.07572582768501154], [32361, 0.07512610971714223], [32375, 0.07605968274098616], [32389, 0.0712843959600892], [32403, 0.0764038768173557], [32417, 0.07602582483101653], [32431, 0.07488072877077342], [32445, 0.07510483520703914], [32585, 0.07539632126172456], [32599, 0.0751332232281892], [32613, 0.07441422522510836], [32627, 0.07492612938761199], [32641, 0.06896549392333637], [32655, 0.0745499562674074], [32851, 0.07701514665744529], [32865, 0.07654082463870596], [32879, 0.07663320438837952], [32893, 0.06773422046439032], [32907, 0.07096584779935097], [32921, 0.0770478217479258], [32991, 0.0770766489667239], [33005, 0.07655270419145899], [33019, 0.07653124226841017], [33033, 0.06792001235181987], [33047, 0.07642338557764843], [33061, 0.07256157761550601], [33075, 0.0762530298205735], [33089, 0.07732028449260378], [33103, 0.07719024904994477], [33117, 0.07678458685483039], [33131, 0.07672721631450713], [33145, 0.07623547425658664], [33159, 0.07775103821660749], [33187, 0.07703586938574755], [33201, 0.07231737028498596], [33215, 0.06756971834979218], [33229, 0.0772998467707892], [33243, 0.07461800072439186], [33271, 0.07780424573838425], [33299, 0.07619977373605957], [33313, 0.07089219593216373], [33327, 0.07134814398032785], [33341, 0.06908612766116917], [33355, 0.07115972131790867], [33369, 0.07114893074328761], [33383, 0.06630195483332325], [33397, 0.07173794433517261], [33411, 0.07112507307850924], [33425, 0.07189155991655617], [33439, 0.0717247057365586], [33453, 0.06920855902143347], [33467, 0.0689248533757127], [33523, 0.06775363372803236], [33537, 0.06834572494725626], [33551, 0.06874699455559195], [33649, 0.06984538783576781], [33705, 0.07056080570070422], [33719, 0.0699512840514869], [33733, 0.06925855192194479], [33747, 0.06310249053297598], [33761, 0.0688335118257124], [33775, 0.06812343321974117], [33803, 0.0689549249818263], [33817, 0.06879872607922918], [33831, 0.06841205079054395], [33845, 0.06854860159412794], [34041, 0.07026241339176657], [34055, 0.07045472156964255], [34069, 0.06425752777906552], [34083, 0.07052261780600481], [34125, 0.07036135961613642], [34139, 0.07117666582148979], [34153, 0.0710789475269128], [34167, 0.06936919732113986]] \ No newline at end of file diff --git a/graphs/summary/model_selection.GridSearchBenchmark.track_test_score.json b/graphs/summary/model_selection.GridSearchBenchmark.track_test_score.json index b26023e8ee..70e6be6b54 100644 --- a/graphs/summary/model_selection.GridSearchBenchmark.track_test_score.json +++ b/graphs/summary/model_selection.GridSearchBenchmark.track_test_score.json @@ -1 +1 @@ -[[28511, 0.8678060899936386], [29225, 0.8678060899936386], [29239, 0.8678060899936387], [29253, 0.8678060899936386], [29267, 0.8678060899936386], [29281, 0.8678060899936386], [29295, 0.8678060899936386], [29309, 0.8678060899936386], [29323, 0.8678060899936386], [29337, 0.8678060899936386], [29351, 0.8678060899936386], [29365, 0.8678060899936386], [29379, 0.8678060899936386], [29393, 0.8678060899936386], [29407, 0.8678060899936386], [29421, 0.8678060899936386], [29435, 0.8678060899936386], [29449, 0.8678060899936386], [29463, 0.8678060899936387], [29477, 0.8678060899936386], [29547, 0.8678060899936386], [29561, 0.8678060899936386], [29575, 0.8678060899936386], [29603, 0.8678060899936386], [29617, 0.8678060899936386], [29631, 0.8678060899936386], [29645, 0.8678060899936386], [29659, 0.8678060899936386], [29673, 0.8678060899936386], [29743, 0.8678060899936386], [29757, 0.8678060899936386], [29771, 0.8678060899936387], [29785, 0.8678060899936386], [29799, 0.8678060899936387], [29813, 0.8678060899936386], [29827, 0.8678060899936386], [29841, 0.8678060899936386], [29855, 0.8678060899936386], [29869, 0.8678060899936386], [30009, 0.8678060899936386], [30023, 0.8678060899936386], [30037, 0.8678060899936386], [30051, 0.8678060899936386], [30065, 0.8678060899936386], [30079, 0.8678060899936388], [30093, 0.8678060899936386], [30107, 0.8678060899936386], [30121, 0.8678060899936386], [30135, 0.8678060899936386], [30149, 0.8678060899936386], [30163, 0.8678060899936386], [30177, 0.8678060899936386], [30191, 0.8678060899936386], [30205, 0.8678060899936386], [30219, 0.8678060899936387], [30233, 0.8678060899936386], [30247, 0.8678060899936386], [30261, 0.8678060899936386], [30513, 0.8678060899936387], [30527, 0.8678060899936387], [30541, 0.8678060899936386], [30555, 0.8678060899936387], [30569, 0.8678060899936386], [30583, 0.8678060899936386], [30597, 0.8678060899936386], [30625, 0.8678060899936386], [30639, 0.8678060899936386], [30653, 0.8678060899936387], [30667, 0.8678060899936386], [30681, 0.8678060899936386], [30695, 0.8678060899936386], [30709, 0.8678060899936386], [30723, 0.8678060899936386], [30737, 0.8678060899936386], [30751, 0.8678060899936386], [30765, 0.8678060899936386], [30779, 0.8678060899936386], [30793, 0.8678060899936386], [30807, 0.8678060899936386], [30821, 0.8678060899936386], [30835, 0.8678060899936386], [30849, 0.8678060899936386], [30863, 0.8678060899936386], [30877, 0.8678060899936386], [30891, 0.8678060899936386], [30905, 0.8678060899936386], [30919, 0.8678060899936386], [30933, 0.8678060899936386], [30947, 0.8678060899936386], [30961, 0.8678060899936386], [30975, 0.8678060899936386], [30989, 0.8678060899936386], [31003, 0.8678060899936386], [31017, 0.8678060899936386], [31031, 0.8678060899936386], [31045, 0.8678060899936386], [32095, 0.8678060899936386], [32109, 0.8678060899936386], [32123, 0.8678060899936386], [32137, 0.8678060899936386], [32151, 0.8678060899936386], [32165, 0.8678060899936386], [32179, 0.8678060899936386], [32193, 0.8678060899936386], [32207, 0.8678060899936386], [32221, 0.8678060899936386], [32235, 0.8678060899936386], [32249, 0.8678060899936386], [32263, 0.8678060899936387], [32277, 0.8678060899936386], [32305, 0.8678060899936386], [32319, 0.8678060899936386], [32333, 0.8678060899936386], [32347, 0.8678060899936386], [32361, 0.8678060899936386], [32375, 0.8678060899936386], [32389, 0.8678060899936386], [32403, 0.8678060899936386], [32417, 0.8678060899936386], [32431, 0.8678060899936386], [32445, 0.8678060899936386], [32585, 0.8678060899936386], [32599, 0.8678060899936386], [32613, 0.8678060899936386], [32627, 0.8678060899936386], [32641, 0.8678060899936386], [32655, 0.8678060899936386], [32851, 0.8678060899936386], [32865, 0.8678060899936386], [32879, 0.8678060899936386], [32893, 0.8678060899936386], [32907, 0.8678060899936386], [32921, 0.8678060899936386], [32991, 0.8678060899936386], [33005, 0.8678060899936386], [33019, 0.8678060899936386], [33033, 0.8678060899936386], [33047, 0.8678060899936386], [33061, 0.8678060899936386], [33075, 0.8678060899936386], [33089, 0.8678060899936386], [33103, 0.8678060899936386], [33117, 0.8678060899936386], [33131, 0.8678060899936386], [33145, 0.8678060899936386], [33159, 0.8678060899936386], [33187, 0.8678060899936386], [33201, 0.8678060899936386], [33215, 0.8678060899936386], [33229, 0.8678060899936386], [33243, 0.8678060899936386], [33271, 0.8678060899936386], [33299, 0.8678060899936386], [33313, 0.8678060899936386], [33327, 0.8678060899936386], [33341, 0.8678060899936386], [33355, 0.8678060899936386], [33369, 0.8678060899936386], [33383, 0.8678060899936386], [33397, 0.8678060899936386], [33411, 0.8678060899936386], [33425, 0.8678060899936386], [33439, 0.8678060899936386], [33453, 0.8678060899936386], [33467, 0.8678060899936386], [33523, 0.8678060899936386], [33537, 0.8678060899936386], [33551, 0.8678060899936386], [33649, 0.8678060899936386], [33705, 0.8678060899936386], [33719, 0.8678060899936386], [33733, 0.8678060899936386], [33747, 0.8678060899936386], [33761, 0.8678060899936386], [33775, 0.8678060899936386], [33803, 0.8678060899936386], [33817, 0.8678060899936386], [33831, 0.8678060899936386], [33845, 0.8678060899936386], [34041, 0.8678060899936386], [34055, 0.8678060899936386], [34069, 0.8678060899936386], [34083, 0.8678060899936386], [34125, 0.8678060899936386], [34139, 0.8678060899936386], [34153, 0.8678060899936386], [34167, 0.8678060899936386]] \ No newline at end of file +[[28511, 0.8678060899936386], [29225, 0.8678060899936386], [29239, 0.8678060899936387], [29253, 0.8678060899936386], [29267, 0.8678060899936386], [29281, 0.8678060899936386], [29295, 0.8678060899936386], [29309, 0.8678060899936386], [29323, 0.8678060899936386], [29337, 0.8678060899936386], [29351, 0.8678060899936386], [29365, 0.8678060899936386], [29379, 0.8678060899936386], [29393, 0.8678060899936386], [29407, 0.8678060899936386], [29421, 0.8678060899936386], [29435, 0.8678060899936386], [29449, 0.8678060899936386], [29463, 0.8678060899936387], [29477, 0.8678060899936386], [29547, 0.8678060899936386], [29561, 0.8678060899936386], [29575, 0.8678060899936386], [29603, 0.8678060899936386], [29617, 0.8678060899936386], [29631, 0.8678060899936386], [29645, 0.8678060899936386], [29659, 0.8678060899936386], [29673, 0.8678060899936386], [29743, 0.8678060899936386], [29757, 0.8678060899936386], [29771, 0.8678060899936387], [29785, 0.8678060899936386], [29799, 0.8678060899936387], [29813, 0.8678060899936386], [29827, 0.8678060899936386], [29841, 0.8678060899936386], [29855, 0.8678060899936386], [29869, 0.8678060899936386], [30009, 0.8678060899936386], [30023, 0.8678060899936386], [30037, 0.8678060899936386], [30051, 0.8678060899936386], [30065, 0.8678060899936386], [30079, 0.8678060899936388], [30093, 0.8678060899936386], [30107, 0.8678060899936386], [30121, 0.8678060899936386], [30135, 0.8678060899936386], [30149, 0.8678060899936386], [30163, 0.8678060899936386], [30177, 0.8678060899936386], [30191, 0.8678060899936386], [30205, 0.8678060899936386], [30219, 0.8678060899936387], [30233, 0.8678060899936386], [30247, 0.8678060899936386], [30261, 0.8678060899936386], [30513, 0.8678060899936387], [30527, 0.8678060899936387], [30541, 0.8678060899936386], [30555, 0.8678060899936387], [30569, 0.8678060899936386], [30583, 0.8678060899936386], [30597, 0.8678060899936386], [30625, 0.8678060899936386], [30639, 0.8678060899936386], [30653, 0.8678060899936387], [30667, 0.8678060899936386], [30681, 0.8678060899936386], [30695, 0.8678060899936386], [30709, 0.8678060899936386], [30723, 0.8678060899936386], [30737, 0.8678060899936386], [30751, 0.8678060899936386], [30765, 0.8678060899936386], [30779, 0.8678060899936386], [30793, 0.8678060899936386], [30807, 0.8678060899936386], [30821, 0.8678060899936386], [30835, 0.8678060899936386], [30849, 0.8678060899936386], [30863, 0.8678060899936386], [30877, 0.8678060899936386], [30891, 0.8678060899936386], [30905, 0.8678060899936386], [30919, 0.8678060899936386], [30933, 0.8678060899936386], [30947, 0.8678060899936386], [30961, 0.8678060899936386], [30975, 0.8678060899936386], [30989, 0.8678060899936386], [31003, 0.8678060899936386], [31017, 0.8678060899936386], [31031, 0.8678060899936386], [31045, 0.8678060899936386], [32095, 0.8678060899936386], [32109, 0.8678060899936386], [32123, 0.8678060899936386], [32137, 0.8678060899936386], [32151, 0.8678060899936386], [32165, 0.8678060899936386], [32179, 0.8678060899936386], [32193, 0.8678060899936386], [32207, 0.8678060899936386], [32221, 0.8678060899936386], [32235, 0.8678060899936386], [32249, 0.8678060899936386], [32263, 0.8678060899936387], [32277, 0.8678060899936386], [32305, 0.8678060899936386], [32319, 0.8678060899936386], [32333, 0.8678060899936386], [32347, 0.8678060899936386], [32361, 0.8678060899936386], [32375, 0.8678060899936386], [32389, 0.8678060899936386], [32403, 0.8678060899936386], [32417, 0.8678060899936386], [32431, 0.8678060899936386], [32445, 0.8678060899936386], [32585, 0.8678060899936386], [32599, 0.8678060899936386], [32613, 0.8678060899936386], [32627, 0.8678060899936386], [32641, 0.8678060899936386], [32655, 0.8678060899936386], [32851, 0.8678060899936386], [32865, 0.8678060899936386], [32879, 0.8678060899936386], [32893, 0.8678060899936386], [32907, 0.8678060899936386], [32921, 0.8678060899936386], [32991, 0.8678060899936386], [33005, 0.8678060899936386], [33019, 0.8678060899936386], [33033, 0.8678060899936386], [33047, 0.8678060899936386], [33061, 0.8678060899936386], [33075, 0.8678060899936386], [33089, 0.8678060899936386], [33103, 0.8678060899936386], [33117, 0.8678060899936386], [33131, 0.8678060899936386], [33145, 0.8678060899936386], [33159, 0.8678060899936386], [33187, 0.8678060899936386], [33201, 0.8678060899936386], [33215, 0.8678060899936386], [33229, 0.8678060899936386], [33243, 0.8678060899936386], [33271, 0.8678060899936386], [33299, 0.8678060899936386], [33313, 0.8678060899936386], [33327, 0.8678060899936386], [33341, 0.8678060899936386], [33355, 0.8678060899936386], [33369, 0.8678060899936386], [33383, 0.8678060899936386], [33397, 0.8678060899936386], [33411, 0.8678060899936386], [33425, 0.8678060899936386], [33439, 0.8678060899936386], [33453, 0.8678060899936386], [33467, 0.8678060899936386], [33523, 0.8678060899936386], [33537, 0.8678060899936386], [33551, 0.8678060899936386], [33649, 0.8678060899936386], [33705, 0.8678060899936386], [33719, 0.8678060899936386], [33733, 0.8678060899936386], [33747, 0.8678060899936386], [33761, 0.8678060899936386], [33775, 0.8678060899936386], [33803, 0.8678060899936386], [33817, 0.8678060899936386], [33831, 0.8678060899936386], [33845, 0.8678060899936386], [34041, 0.8678060899936386], [34055, 0.8678060899936386], [34069, 0.8678060899936386], [34083, 0.8678060899936386], [34125, 0.8678060899936386], [34139, 0.8678060899936386], [34153, 0.8678060899936386], [34167, 0.8678060899936387]] \ No newline at end of file diff --git a/graphs/summary/model_selection.GridSearchBenchmark.track_train_score.json b/graphs/summary/model_selection.GridSearchBenchmark.track_train_score.json index 802d43b043..b399ac5378 100644 --- a/graphs/summary/model_selection.GridSearchBenchmark.track_train_score.json +++ b/graphs/summary/model_selection.GridSearchBenchmark.track_train_score.json @@ -1 +1 @@ -[[28511, 0.9966662088870577], [29225, 0.9966662088870577], [29239, 0.9966662088870578], [29253, 0.9966662088870577], [29267, 0.9966662088870577], [29281, 0.9966662088870577], [29295, 0.9966662088870577], [29309, 0.9966662088870577], [29323, 0.9966662088870577], [29337, 0.9966662088870577], [29351, 0.9966662088870577], [29365, 0.9966662088870577], [29379, 0.9966662088870577], [29393, 0.9966662088870577], [29407, 0.9966662088870577], [29421, 0.9966662088870577], [29435, 0.9966662088870577], [29449, 0.9966662088870577], [29463, 0.9966662088870578], [29477, 0.9966662088870577], [29547, 0.9966662088870577], [29561, 0.9966662088870577], [29575, 0.9966662088870577], [29603, 0.9966662088870577], [29617, 0.9966662088870577], [29631, 0.9966662088870577], [29645, 0.9966662088870577], [29659, 0.9966662088870577], [29673, 0.9966662088870577], [29743, 0.9966662088870577], [29757, 0.9966662088870577], [29771, 0.9966662088870578], [29785, 0.9966662088870577], [29799, 0.9966662088870578], [29813, 0.9966662088870577], [29827, 0.9966662088870577], [29841, 0.9966662088870577], [29855, 0.9966662088870577], [29869, 0.9966662088870577], [30009, 0.9966662088870577], [30023, 0.9966662088870577], [30037, 0.9966662088870577], [30051, 0.9966662088870577], [30065, 0.9966662088870577], [30079, 0.9966662088870579], [30093, 0.9966662088870577], [30107, 0.9966662088870577], [30121, 0.9966662088870577], [30135, 0.9966662088870577], [30149, 0.9966662088870577], [30163, 0.9966662088870577], [30177, 0.9966662088870577], [30191, 0.9966662088870577], [30205, 0.9966662088870577], [30219, 0.9966662088870578], [30233, 0.9966662088870577], [30247, 0.9966662088870577], [30261, 0.9966662088870577], [30513, 0.9966662088870578], [30527, 0.9966662088870578], [30541, 0.9966662088870577], [30555, 0.9966662088870578], [30569, 0.9966662088870577], [30583, 0.9966662088870577], [30597, 0.9966662088870577], [30625, 0.9966662088870577], [30639, 0.9966662088870577], [30653, 0.9966662088870578], [30667, 0.9966662088870577], [30681, 0.9966662088870577], [30695, 0.9966662088870577], [30709, 0.9966662088870577], [30723, 0.9966662088870577], [30737, 0.9966662088870577], [30751, 0.9966662088870577], [30765, 0.9966662088870577], [30779, 0.9966662088870577], [30793, 0.9966662088870577], [30807, 0.9966662088870577], [30821, 0.9966662088870577], [30835, 0.9966662088870577], [30849, 0.9966662088870577], [30863, 0.9966662088870577], [30877, 0.9966662088870577], [30891, 0.9966662088870577], [30905, 0.9966662088870577], [30919, 0.9966662088870577], [30933, 0.9966662088870577], [30947, 0.9966662088870577], [30961, 0.9966662088870577], [30975, 0.9966662088870577], [30989, 0.9966662088870577], [31003, 0.9966662088870577], [31017, 0.9966662088870577], [31031, 0.9966662088870577], [31045, 0.9966662088870577], [32095, 0.9966662088870577], [32109, 0.9966662088870577], [32123, 0.9966662088870577], [32137, 0.9966662088870577], [32151, 0.9966662088870577], [32165, 0.9966662088870577], [32179, 0.9966662088870577], [32193, 0.9966662088870577], [32207, 0.9966662088870577], [32221, 0.9966662088870577], [32235, 0.9966662088870577], [32249, 0.9966662088870577], [32263, 0.9966662088870578], [32277, 0.9966662088870577], [32305, 0.9966662088870577], [32319, 0.9966662088870577], [32333, 0.9966662088870577], [32347, 0.9966662088870577], [32361, 0.9966662088870577], [32375, 0.9966662088870577], [32389, 0.9966662088870577], [32403, 0.9966662088870577], [32417, 0.9966662088870577], [32431, 0.9966662088870577], [32445, 0.9966662088870577], [32585, 0.9966662088870577], [32599, 0.9966662088870577], [32613, 0.9966662088870577], [32627, 0.9966662088870577], [32641, 0.9966662088870577], [32655, 0.9966662088870577], [32851, 0.9966662088870577], [32865, 0.9966662088870577], [32879, 0.9966662088870577], [32893, 0.9966662088870577], [32907, 0.9966662088870577], [32921, 0.9966662088870577], [32991, 0.9966662088870577], [33005, 0.9966662088870577], [33019, 0.9966662088870577], [33033, 0.9966662088870577], [33047, 0.9966662088870577], [33061, 0.9966662088870577], [33075, 0.9966662088870577], [33089, 0.9966662088870577], [33103, 0.9966662088870577], [33117, 0.9966662088870577], [33131, 0.9966662088870577], [33145, 0.9966662088870577], [33159, 0.9966662088870577], [33187, 0.9966662088870577], [33201, 0.9966662088870577], [33215, 0.9966662088870577], [33229, 0.9966662088870578], [33243, 0.9966662088870578], [33271, 0.9966662088870577], [33299, 0.9966662088870577], [33313, 0.9966662088870577], [33327, 0.9966662088870577], [33341, 0.9966662088870577], [33355, 0.9966662088870577], [33369, 0.9966662088870577], [33383, 0.9966662088870577], [33397, 0.9966662088870577], [33411, 0.9966662088870577], [33425, 0.9966662088870577], [33439, 0.9966662088870577], [33453, 0.9966662088870577], [33467, 0.9966662088870577], [33523, 0.9966662088870577], [33537, 0.9966662088870577], [33551, 0.9966662088870577], [33649, 0.9966662088870577], [33705, 0.9966662088870577], [33719, 0.9966662088870577], [33733, 0.9966662088870577], [33747, 0.9966662088870577], [33761, 0.9966662088870577], [33775, 0.9966662088870577], [33803, 0.9966662088870577], [33817, 0.9966662088870577], [33831, 0.9966662088870577], [33845, 0.9966662088870577], [34041, 0.9966662088870577], [34055, 0.9966662088870577], [34069, 0.9966662088870577], [34083, 0.9966662088870577], [34125, 0.9966662088870577], [34139, 0.9966662088870577], [34153, 0.9966662088870577], [34167, 0.9966662088870577]] \ No newline at end of file +[[28511, 0.9966662088870577], [29225, 0.9966662088870577], [29239, 0.9966662088870578], [29253, 0.9966662088870577], [29267, 0.9966662088870577], [29281, 0.9966662088870577], [29295, 0.9966662088870577], [29309, 0.9966662088870577], [29323, 0.9966662088870577], [29337, 0.9966662088870577], [29351, 0.9966662088870577], [29365, 0.9966662088870577], [29379, 0.9966662088870577], [29393, 0.9966662088870577], [29407, 0.9966662088870577], [29421, 0.9966662088870577], [29435, 0.9966662088870577], [29449, 0.9966662088870577], [29463, 0.9966662088870578], [29477, 0.9966662088870577], [29547, 0.9966662088870577], [29561, 0.9966662088870577], [29575, 0.9966662088870577], [29603, 0.9966662088870577], [29617, 0.9966662088870577], [29631, 0.9966662088870577], [29645, 0.9966662088870577], [29659, 0.9966662088870577], [29673, 0.9966662088870577], [29743, 0.9966662088870577], [29757, 0.9966662088870577], [29771, 0.9966662088870578], [29785, 0.9966662088870577], [29799, 0.9966662088870578], [29813, 0.9966662088870577], [29827, 0.9966662088870577], [29841, 0.9966662088870577], [29855, 0.9966662088870577], [29869, 0.9966662088870577], [30009, 0.9966662088870577], [30023, 0.9966662088870577], [30037, 0.9966662088870577], [30051, 0.9966662088870577], [30065, 0.9966662088870577], [30079, 0.9966662088870579], [30093, 0.9966662088870577], [30107, 0.9966662088870577], [30121, 0.9966662088870577], [30135, 0.9966662088870577], [30149, 0.9966662088870577], [30163, 0.9966662088870577], [30177, 0.9966662088870577], [30191, 0.9966662088870577], [30205, 0.9966662088870577], [30219, 0.9966662088870578], [30233, 0.9966662088870577], [30247, 0.9966662088870577], [30261, 0.9966662088870577], [30513, 0.9966662088870578], [30527, 0.9966662088870578], [30541, 0.9966662088870577], [30555, 0.9966662088870578], [30569, 0.9966662088870577], [30583, 0.9966662088870577], [30597, 0.9966662088870577], [30625, 0.9966662088870577], [30639, 0.9966662088870577], [30653, 0.9966662088870578], [30667, 0.9966662088870577], [30681, 0.9966662088870577], [30695, 0.9966662088870577], [30709, 0.9966662088870577], [30723, 0.9966662088870577], [30737, 0.9966662088870577], [30751, 0.9966662088870577], [30765, 0.9966662088870577], [30779, 0.9966662088870577], [30793, 0.9966662088870577], [30807, 0.9966662088870577], [30821, 0.9966662088870577], [30835, 0.9966662088870577], [30849, 0.9966662088870577], [30863, 0.9966662088870577], [30877, 0.9966662088870577], [30891, 0.9966662088870577], [30905, 0.9966662088870577], [30919, 0.9966662088870577], [30933, 0.9966662088870577], [30947, 0.9966662088870577], [30961, 0.9966662088870577], [30975, 0.9966662088870577], [30989, 0.9966662088870577], [31003, 0.9966662088870577], [31017, 0.9966662088870577], [31031, 0.9966662088870577], [31045, 0.9966662088870577], [32095, 0.9966662088870577], [32109, 0.9966662088870577], [32123, 0.9966662088870577], [32137, 0.9966662088870577], [32151, 0.9966662088870577], [32165, 0.9966662088870577], [32179, 0.9966662088870577], [32193, 0.9966662088870577], [32207, 0.9966662088870577], [32221, 0.9966662088870577], [32235, 0.9966662088870577], [32249, 0.9966662088870577], [32263, 0.9966662088870578], [32277, 0.9966662088870577], [32305, 0.9966662088870577], [32319, 0.9966662088870577], [32333, 0.9966662088870577], [32347, 0.9966662088870577], [32361, 0.9966662088870577], [32375, 0.9966662088870577], [32389, 0.9966662088870577], [32403, 0.9966662088870577], [32417, 0.9966662088870577], [32431, 0.9966662088870577], [32445, 0.9966662088870577], [32585, 0.9966662088870577], [32599, 0.9966662088870577], [32613, 0.9966662088870577], [32627, 0.9966662088870577], [32641, 0.9966662088870577], [32655, 0.9966662088870577], [32851, 0.9966662088870577], [32865, 0.9966662088870577], [32879, 0.9966662088870577], [32893, 0.9966662088870577], [32907, 0.9966662088870577], [32921, 0.9966662088870577], [32991, 0.9966662088870577], [33005, 0.9966662088870577], [33019, 0.9966662088870577], [33033, 0.9966662088870577], [33047, 0.9966662088870577], [33061, 0.9966662088870577], [33075, 0.9966662088870577], [33089, 0.9966662088870577], [33103, 0.9966662088870577], [33117, 0.9966662088870577], [33131, 0.9966662088870577], [33145, 0.9966662088870577], [33159, 0.9966662088870577], [33187, 0.9966662088870577], [33201, 0.9966662088870577], [33215, 0.9966662088870577], [33229, 0.9966662088870578], [33243, 0.9966662088870578], [33271, 0.9966662088870577], [33299, 0.9966662088870577], [33313, 0.9966662088870577], [33327, 0.9966662088870577], [33341, 0.9966662088870577], [33355, 0.9966662088870577], [33369, 0.9966662088870577], [33383, 0.9966662088870577], [33397, 0.9966662088870577], [33411, 0.9966662088870577], [33425, 0.9966662088870577], [33439, 0.9966662088870577], [33453, 0.9966662088870577], [33467, 0.9966662088870577], [33523, 0.9966662088870577], [33537, 0.9966662088870577], [33551, 0.9966662088870577], [33649, 0.9966662088870577], [33705, 0.9966662088870577], [33719, 0.9966662088870577], [33733, 0.9966662088870577], [33747, 0.9966662088870577], [33761, 0.9966662088870577], [33775, 0.9966662088870577], [33803, 0.9966662088870577], [33817, 0.9966662088870577], [33831, 0.9966662088870577], [33845, 0.9966662088870577], [34041, 0.9966662088870577], [34055, 0.9966662088870577], [34069, 0.9966662088870577], [34083, 0.9966662088870577], [34125, 0.9966662088870577], [34139, 0.9966662088870577], [34153, 0.9966662088870577], [34167, 0.9966662088870578]] \ No newline at end of file diff --git a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json index 13e4b3cb0c..2a0ec92ac2 100644 --- a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json +++ b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 74793249.20346113], [29225, 72441876.47731802], [29239, 72321992.53491206], [29253, 72468683.96178721], [29267, 72532913.10905208], [29281, 72632431.42109753], [29295, 72521232.13820772], [29309, 72570692.64482412], [29323, 72429110.08023769], [29337, 72649874.31043859], [29351, 72066532.9311044], [29365, 72059716.88475305], [29379, 72166411.63052599], [29393, 72220757.64658853], [29407, 72030679.22104433], [29421, 72121523.74418005], [29435, 72529664.3023989], [29449, 72625307.18057813], [29463, 72518210.87214729], [29477, 72516627.53158516], [29547, 72619906.52476752], [29561, 72621629.39983028], [29575, 72043492.27936262], [29603, 73190460.62415558], [29617, 73331959.0282135], [29631, 73438565.41786918], [29645, 73392413.76075557], [29659, 73272877.29204518], [29673, 73261330.25932351], [29743, 73158108.76690564], [29757, 73317719.3572312], [29771, 73230149.80277367], [29785, 73345684.96004719], [29799, 73394409.8493276], [29813, 73527214.23015323], [29827, 73630419.47803116], [29841, 73617684.182087], [29855, 73664479.03767852], [29869, 73741440.79959165], [30009, 73507243.74411407], [30023, 73412295.18027854], [30037, 73545865.480105], [30051, 73490190.84055437], [30065, 73773694.00374627], [30079, 73681226.13098046], [30093, 73667938.90073863], [30107, 73539710.68604869], [30121, 73853641.7446345], [30135, 73740901.69798455], [30149, 73965682.59502345], [30163, 74043410.88421436], [30177, 74117456.35870883], [30191, 74153340.17769715], [30205, 74104337.94636865], [30219, 74132165.4935194], [30233, 73871683.98620644], [30247, 74149553.11699195], [30261, 73996965.8632882], [30513, 74224444.33169545], [30527, 74029539.36210124], [30541, 73982423.77453299], [30555, 73856797.39389746], [30569, 73932335.4829534], [30583, 73999254.67901343], [30597, 74023886.89729983], [30625, 74000965.49621], [30639, 74059592.03931817], [30653, 73941551.71370657], [30667, 73957574.62874332], [30681, 74061789.86805867], [30695, 74022472.48895195], [30709, 74024282.16209191], [30723, 74031841.18226114], [30737, 74008601.53763461], [30751, 74141007.7589143], [30765, 74450169.9821661], [30779, 74040145.97374766], [30793, 74031666.73661812], [30807, 73984558.93770884], [30821, 74185398.85317689], [30835, 74396213.6852535], [30849, 74251782.20728448], [30863, 74091331.573614], [30877, 74252018.46073984], [30891, 74204201.60292481], [30905, 74246837.28405999], [30919, 74038060.54245175], [30933, 73914756.0550753], [30947, 74092460.33871004], [30961, 74085277.07883269], [30975, 74099937.20718697], [30989, 74286730.9371968], [31003, 74373083.81441289], [31017, 74385539.97083183], [31031, 73893502.30647728], [31045, 74180487.55243851], [32095, 85963294.63136178], [32109, 85624825.75607683], [32123, 85743050.14642431], [32137, 85757464.24179603], [32151, 85646662.13211624], [32165, 85652636.96259716], [32179, 85397277.58153705], [32193, 85828643.57952397], [32207, 87087222.96299465], [32221, 89141194.07116391], [32235, 89120679.24030253], [32249, 89234993.81239414], [32263, 89180414.25702184], [32277, 88422274.70177135], [32305, 89759106.51567781], [32319, 92381430.72362769], [32333, 92348530.66736569], [32347, 92439286.64706263], [32361, 92482210.88424824], [32375, 92623850.10567118], [32389, 92397713.02689356], [32403, 92200900.04400682], [32417, 92238477.27399953], [32431, 92391559.59982613], [32445, 92474184.96493685], [32585, 92559761.04683258], [32599, 92626433.43428059], [32613, 92617434.23363918], [32627, 92702691.19697496], [32641, 92582746.59271911], [32655, 92658420.6786059], [32851, 93530746.6871534], [32865, 93507652.11365369], [32879, 93452684.24889402], [32893, 93523345.47572559], [32907, 93463175.58683734], [32921, 93556861.13260978], [32991, 93599734.50751756], [33005, 93462332.9161237], [33019, 93222247.99932538], [33033, 93592466.81906016], [33047, 93648179.93033908], [33061, 93742045.78346975], [33075, 93667044.67451546], [33089, 109241306.16711156], [33103, 124799566.67616343], [33117, 124999094.00157511], [33131, 124695442.32883161], [33145, 125205083.06634066], [33159, 125319185.27383122], [33187, 93927073.45821197], [33201, 93867275.74462853], [33215, 92760630.14553043], [33229, 89661005.08057053], [33243, 89854801.21660846], [33271, 85860580.36716275], [33299, 85601864.4168429], [33313, 85915113.14034042], [33327, 86491387.64466041], [33341, 86401623.3500206], [33355, 86670800.56568147], [33369, 86698338.25933115], [33383, 87397126.88763809], [33397, 87747354.4918417], [33411, 87664352.6482617], [33425, 87800244.37532794], [33439, 88709582.7674911], [33453, 84001247.97864649], [33467, 84092441.40046208], [33523, 84064757.16490749], [33537, 84281359.13440822], [33551, 83638621.0166284], [33649, 82965570.65504526], [33705, 82527508.06212138], [33719, 82652932.36298771], [33733, 82632684.62895511], [33747, 82593206.05374382], [33761, 82751351.58711821], [33775, 82568310.26311958], [33803, 82545627.02455637], [33817, 82411209.08777645], [33831, 82424556.89588414], [33845, 82537723.8075955], [34041, 82153855.78289264], [34055, 82487440.82433502], [34069, 82392069.73197311], [34083, 82215150.77019176], [34125, 82354009.15600903], [34139, 82376667.10291737], [34153, 82301064.09696425], [34167, 82358344.79499015]] \ No newline at end of file +[[28511, 74793249.20346113], [29225, 72441876.47731802], [29239, 72321992.53491206], [29253, 72468683.96178721], [29267, 72532913.10905208], [29281, 72632431.42109753], [29295, 72521232.13820772], [29309, 72570692.64482412], [29323, 72429110.08023769], [29337, 72649874.31043859], [29351, 72066532.9311044], [29365, 72059716.88475305], [29379, 72166411.63052599], [29393, 72220757.64658853], [29407, 72030679.22104433], [29421, 72121523.74418005], [29435, 72529664.3023989], [29449, 72625307.18057813], [29463, 72518210.87214729], [29477, 72516627.53158516], [29547, 72619906.52476752], [29561, 72621629.39983028], [29575, 72043492.27936262], [29603, 73190460.62415558], [29617, 73331959.0282135], [29631, 73438565.41786918], [29645, 73392413.76075557], [29659, 73272877.29204518], [29673, 73261330.25932351], [29743, 73158108.76690564], [29757, 73317719.3572312], [29771, 73230149.80277367], [29785, 73345684.96004719], [29799, 73394409.8493276], [29813, 73527214.23015323], [29827, 73630419.47803116], [29841, 73617684.182087], [29855, 73664479.03767852], [29869, 73741440.79959165], [30009, 73507243.74411407], [30023, 73412295.18027854], [30037, 73545865.480105], [30051, 73490190.84055437], [30065, 73773694.00374627], [30079, 73681226.13098046], [30093, 73667938.90073863], [30107, 73539710.68604869], [30121, 73853641.7446345], [30135, 73740901.69798455], [30149, 73965682.59502345], [30163, 74043410.88421436], [30177, 74117456.35870883], [30191, 74153340.17769715], [30205, 74104337.94636865], [30219, 74132165.4935194], [30233, 73871683.98620644], [30247, 74149553.11699195], [30261, 73996965.8632882], [30513, 74224444.33169545], [30527, 74029539.36210124], [30541, 73982423.77453299], [30555, 73856797.39389746], [30569, 73932335.4829534], [30583, 73999254.67901343], [30597, 74023886.89729983], [30625, 74000965.49621], [30639, 74059592.03931817], [30653, 73941551.71370657], [30667, 73957574.62874332], [30681, 74061789.86805867], [30695, 74022472.48895195], [30709, 74024282.16209191], [30723, 74031841.18226114], [30737, 74008601.53763461], [30751, 74141007.7589143], [30765, 74450169.9821661], [30779, 74040145.97374766], [30793, 74031666.73661812], [30807, 73984558.93770884], [30821, 74185398.85317689], [30835, 74396213.6852535], [30849, 74251782.20728448], [30863, 74091331.573614], [30877, 74252018.46073984], [30891, 74204201.60292481], [30905, 74246837.28405999], [30919, 74038060.54245175], [30933, 73914756.0550753], [30947, 74092460.33871004], [30961, 74085277.07883269], [30975, 74099937.20718697], [30989, 74286730.9371968], [31003, 74373083.81441289], [31017, 74385539.97083183], [31031, 73893502.30647728], [31045, 74180487.55243851], [32095, 85963294.63136178], [32109, 85624825.75607683], [32123, 85743050.14642431], [32137, 85757464.24179603], [32151, 85646662.13211624], [32165, 85652636.96259716], [32179, 85397277.58153705], [32193, 85828643.57952397], [32207, 87087222.96299465], [32221, 89141194.07116391], [32235, 89120679.24030253], [32249, 89234993.81239414], [32263, 89180414.25702184], [32277, 88422274.70177135], [32305, 89759106.51567781], [32319, 92381430.72362769], [32333, 92348530.66736569], [32347, 92439286.64706263], [32361, 92482210.88424824], [32375, 92623850.10567118], [32389, 92397713.02689356], [32403, 92200900.04400682], [32417, 92238477.27399953], [32431, 92391559.59982613], [32445, 92474184.96493685], [32585, 92559761.04683258], [32599, 92626433.43428059], [32613, 92617434.23363918], [32627, 92702691.19697496], [32641, 92582746.59271911], [32655, 92658420.6786059], [32851, 93530746.6871534], [32865, 93507652.11365369], [32879, 93452684.24889402], [32893, 93523345.47572559], [32907, 93463175.58683734], [32921, 93556861.13260978], [32991, 93599734.50751756], [33005, 93462332.9161237], [33019, 93222247.99932538], [33033, 93592466.81906016], [33047, 93648179.93033908], [33061, 93742045.78346975], [33075, 93667044.67451546], [33089, 109241306.16711156], [33103, 124799566.67616343], [33117, 124999094.00157511], [33131, 124695442.32883161], [33145, 125205083.06634066], [33159, 125319185.27383122], [33187, 93927073.45821197], [33201, 93867275.74462853], [33215, 92760630.14553043], [33229, 89661005.08057053], [33243, 89854801.21660846], [33271, 85860580.36716275], [33299, 85601864.4168429], [33313, 85915113.14034042], [33327, 86491387.64466041], [33341, 86401623.3500206], [33355, 86670800.56568147], [33369, 86698338.25933115], [33383, 87397126.88763809], [33397, 87747354.4918417], [33411, 87664352.6482617], [33425, 87800244.37532794], [33439, 88709582.7674911], [33453, 84001247.97864649], [33467, 84092441.40046208], [33523, 84064757.16490749], [33537, 84281359.13440822], [33551, 83638621.0166284], [33649, 82965570.65504526], [33705, 82527508.06212138], [33719, 82652932.36298771], [33733, 82632684.62895511], [33747, 82593206.05374382], [33761, 82751351.58711821], [33775, 82568310.26311958], [33803, 82545627.02455637], [33817, 82411209.08777645], [33831, 82424556.89588414], [33845, 82537723.8075955], [34041, 82153855.78289264], [34055, 82487440.82433502], [34069, 82392069.73197311], [34083, 82215150.77019176], [34125, 82354009.15600903], [34139, 82376667.10291737], [34153, 82301064.09696425], [34167, 82276192.2680374]] \ No newline at end of file diff --git a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json index 5292659d2b..02b82e8dc4 100644 --- a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json +++ b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28511, 206062277.18948048], [29225, 201760729.75549385], [29239, 202151191.77099404], [29253, 201958015.76073265], [29267, 202079551.28744575], [29281, 202063468.00739807], [29295, 202503790.2660561], [29309, 202262693.4714781], [29323, 202222506.82922456], [29337, 202468478.4904847], [29351, 201173952.00386274], [29365, 200749127.66909382], [29379, 201539266.09315836], [29393, 201639408.63357362], [29407, 201369779.01753092], [29421, 201439517.95601377], [29435, 201708842.11931813], [29449, 201937506.88889933], [29463, 202370970.66494888], [29477, 202705049.7772843], [29547, 202353793.81484482], [29561, 202727707.66715994], [29575, 202119328.787425], [29603, 203498962.72538394], [29617, 203871112.36635506], [29631, 204537700.73201686], [29645, 204051739.411309], [29659, 203566331.1000226], [29673, 203751575.62111175], [29743, 203717771.3770991], [29757, 204158715.29600823], [29771, 203817325.06635267], [29785, 203913078.18924356], [29799, 203893513.2608483], [29813, 203861080.07080266], [29827, 204265966.4865622], [29841, 204054216.01117134], [29855, 204198621.27030048], [29869, 204479980.9006473], [30009, 204223340.96750945], [30023, 203728835.18574163], [30037, 204238704.56434914], [30051, 204151439.35291082], [30065, 204524086.18614453], [30079, 204402043.88289484], [30093, 204390888.50042382], [30107, 204086003.67006588], [30121, 204828513.6826551], [30135, 204485172.2173419], [30149, 204917350.41588995], [30163, 205155730.3229334], [30177, 205123393.79837787], [30191, 205237213.82966912], [30205, 204724819.23126912], [30219, 205328431.2166917], [30233, 205218637.89107287], [30247, 205311435.75426006], [30261, 205185473.61467278], [30513, 205468027.95229533], [30527, 204896053.56474903], [30541, 204677054.46291065], [30555, 204480476.41523242], [30569, 204740591.48224226], [30583, 204652713.9962244], [30597, 204741639.65503597], [30625, 204978086.44909367], [30639, 204922726.46900046], [30653, 204940324.46349803], [30667, 204621724.38377696], [30681, 204971352.33574784], [30695, 204099908.57286435], [30709, 204509190.80096054], [30723, 204991765.36247134], [30737, 204762789.06225127], [30751, 205014478.58322722], [30765, 205693520.48444572], [30779, 203974485.28991124], [30793, 205089597.93627694], [30807, 205089498.85340345], [30821, 205202987.0037421], [30835, 205230295.68870583], [30849, 205643811.19345635], [30863, 204688899.94380125], [30877, 205227653.51043493], [30891, 205201688.9253997], [30905, 204537699.40245718], [30919, 205359700.25962138], [30933, 204700637.61053097], [30947, 205148714.72000733], [30961, 205416310.11268413], [30975, 205163432.23127717], [30989, 205195644.47247538], [31003, 205409176.76545233], [31017, 205903836.27547368], [31031, 205112212.62032565], [31045, 205486880.83820575], [32095, 94361842.28767529], [32109, 94170779.472817], [32123, 94298550.75020792], [32137, 94340748.42911823], [32151, 94215520.07875527], [32165, 94300082.45026383], [32179, 94043193.85033476], [32193, 94448581.97672893], [32207, 95719002.04120794], [32221, 97567678.92518876], [32235, 97912144.95253624], [32249, 97714523.86158153], [32263, 97656969.1269261], [32277, 96903118.25729759], [32305, 98777914.63072713], [32319, 102527183.2639875], [32333, 102590143.34754059], [32347, 102521857.39708954], [32361, 102532759.8494481], [32375, 102711545.8929124], [32389, 102479701.7087516], [32403, 102338138.69578017], [32417, 102449683.82367106], [32431, 102566915.50690472], [32445, 102713957.19381233], [32585, 101318823.22344339], [32599, 101287054.40962596], [32613, 101309796.70953166], [32627, 101416349.51309389], [32641, 101252733.0137357], [32655, 101254119.47885013], [32851, 102152871.56043053], [32865, 102162461.40295887], [32879, 102262712.63491404], [32893, 102351867.21778598], [32907, 102088276.26186], [32921, 102137455.3869968], [32991, 102207285.43047601], [33005, 102080912.37863706], [33019, 101783499.13632546], [33033, 102234861.22439137], [33047, 102623900.67560638], [33061, 102820957.37917802], [33075, 102580311.07504784], [33089, 117672530.19149193], [33103, 132434876.35488641], [33117, 132668672.946932], [33131, 132270246.64509736], [33145, 132694090.08990933], [33159, 132846201.70590295], [33187, 103019666.37306908], [33201, 102895814.69401017], [33215, 101348317.25023729], [33229, 96814889.19394886], [33243, 96942533.2074748], [33271, 91340977.88918293], [33299, 91114693.25264971], [33313, 91399751.13771981], [33327, 91959612.41193007], [33341, 91884778.22711846], [33355, 92073322.34453869], [33369, 92067824.57839747], [33383, 92684079.36286402], [33397, 93038478.37511367], [33411, 93198925.4059778], [33425, 93129370.12265581], [33439, 94285468.99502578], [33453, 89400453.23404005], [33467, 89512570.86842862], [33523, 89418248.80644006], [33537, 89555382.99136908], [33551, 88869918.1693155], [33649, 88667306.54674034], [33705, 88197008.889858], [33719, 88259281.26150237], [33733, 88308232.84818439], [33747, 88102130.03437996], [33761, 88036423.36707932], [33775, 88158002.32204984], [33803, 88266171.39217965], [33817, 87865963.73774791], [33831, 88051640.41593884], [33845, 87803353.78490694], [34041, 87808313.67784286], [34055, 88171349.32047524], [34069, 88125907.51058316], [34083, 87953988.28620693], [34125, 87876955.20351346], [34139, 88022661.60882321], [34153, 87955780.49693392], [34167, 87855007.83489028]] \ No newline at end of file +[[28511, 206062277.18948048], [29225, 201760729.75549385], [29239, 202151191.77099404], [29253, 201958015.76073265], [29267, 202079551.28744575], [29281, 202063468.00739807], [29295, 202503790.2660561], [29309, 202262693.4714781], [29323, 202222506.82922456], [29337, 202468478.4904847], [29351, 201173952.00386274], [29365, 200749127.66909382], [29379, 201539266.09315836], [29393, 201639408.63357362], [29407, 201369779.01753092], [29421, 201439517.95601377], [29435, 201708842.11931813], [29449, 201937506.88889933], [29463, 202370970.66494888], [29477, 202705049.7772843], [29547, 202353793.81484482], [29561, 202727707.66715994], [29575, 202119328.787425], [29603, 203498962.72538394], [29617, 203871112.36635506], [29631, 204537700.73201686], [29645, 204051739.411309], [29659, 203566331.1000226], [29673, 203751575.62111175], [29743, 203717771.3770991], [29757, 204158715.29600823], [29771, 203817325.06635267], [29785, 203913078.18924356], [29799, 203893513.2608483], [29813, 203861080.07080266], [29827, 204265966.4865622], [29841, 204054216.01117134], [29855, 204198621.27030048], [29869, 204479980.9006473], [30009, 204223340.96750945], [30023, 203728835.18574163], [30037, 204238704.56434914], [30051, 204151439.35291082], [30065, 204524086.18614453], [30079, 204402043.88289484], [30093, 204390888.50042382], [30107, 204086003.67006588], [30121, 204828513.6826551], [30135, 204485172.2173419], [30149, 204917350.41588995], [30163, 205155730.3229334], [30177, 205123393.79837787], [30191, 205237213.82966912], [30205, 204724819.23126912], [30219, 205328431.2166917], [30233, 205218637.89107287], [30247, 205311435.75426006], [30261, 205185473.61467278], [30513, 205468027.95229533], [30527, 204896053.56474903], [30541, 204677054.46291065], [30555, 204480476.41523242], [30569, 204740591.48224226], [30583, 204652713.9962244], [30597, 204741639.65503597], [30625, 204978086.44909367], [30639, 204922726.46900046], [30653, 204940324.46349803], [30667, 204621724.38377696], [30681, 204971352.33574784], [30695, 204099908.57286435], [30709, 204509190.80096054], [30723, 204991765.36247134], [30737, 204762789.06225127], [30751, 205014478.58322722], [30765, 205693520.48444572], [30779, 203974485.28991124], [30793, 205089597.93627694], [30807, 205089498.85340345], [30821, 205202987.0037421], [30835, 205230295.68870583], [30849, 205643811.19345635], [30863, 204688899.94380125], [30877, 205227653.51043493], [30891, 205201688.9253997], [30905, 204537699.40245718], [30919, 205359700.25962138], [30933, 204700637.61053097], [30947, 205148714.72000733], [30961, 205416310.11268413], [30975, 205163432.23127717], [30989, 205195644.47247538], [31003, 205409176.76545233], [31017, 205903836.27547368], [31031, 205112212.62032565], [31045, 205486880.83820575], [32095, 94361842.28767529], [32109, 94170779.472817], [32123, 94298550.75020792], [32137, 94340748.42911823], [32151, 94215520.07875527], [32165, 94300082.45026383], [32179, 94043193.85033476], [32193, 94448581.97672893], [32207, 95719002.04120794], [32221, 97567678.92518876], [32235, 97912144.95253624], [32249, 97714523.86158153], [32263, 97656969.1269261], [32277, 96903118.25729759], [32305, 98777914.63072713], [32319, 102527183.2639875], [32333, 102590143.34754059], [32347, 102521857.39708954], [32361, 102532759.8494481], [32375, 102711545.8929124], [32389, 102479701.7087516], [32403, 102338138.69578017], [32417, 102449683.82367106], [32431, 102566915.50690472], [32445, 102713957.19381233], [32585, 101318823.22344339], [32599, 101287054.40962596], [32613, 101309796.70953166], [32627, 101416349.51309389], [32641, 101252733.0137357], [32655, 101254119.47885013], [32851, 102152871.56043053], [32865, 102162461.40295887], [32879, 102262712.63491404], [32893, 102351867.21778598], [32907, 102088276.26186], [32921, 102137455.3869968], [32991, 102207285.43047601], [33005, 102080912.37863706], [33019, 101783499.13632546], [33033, 102234861.22439137], [33047, 102623900.67560638], [33061, 102820957.37917802], [33075, 102580311.07504784], [33089, 117672530.19149193], [33103, 132434876.35488641], [33117, 132668672.946932], [33131, 132270246.64509736], [33145, 132694090.08990933], [33159, 132846201.70590295], [33187, 103019666.37306908], [33201, 102895814.69401017], [33215, 101348317.25023729], [33229, 96814889.19394886], [33243, 96942533.2074748], [33271, 91340977.88918293], [33299, 91114693.25264971], [33313, 91399751.13771981], [33327, 91959612.41193007], [33341, 91884778.22711846], [33355, 92073322.34453869], [33369, 92067824.57839747], [33383, 92684079.36286402], [33397, 93038478.37511367], [33411, 93198925.4059778], [33425, 93129370.12265581], [33439, 94285468.99502578], [33453, 89400453.23404005], [33467, 89512570.86842862], [33523, 89418248.80644006], [33537, 89555382.99136908], [33551, 88869918.1693155], [33649, 88667306.54674034], [33705, 88197008.889858], [33719, 88259281.26150237], [33733, 88308232.84818439], [33747, 88102130.03437996], [33761, 88036423.36707932], [33775, 88158002.32204984], [33803, 88266171.39217965], [33817, 87865963.73774791], [33831, 88051640.41593884], [33845, 87803353.78490694], [34041, 87808313.67784286], [34055, 88171349.32047524], [34069, 88125907.51058316], [34083, 87953988.28620693], [34125, 87876955.20351346], [34139, 88022661.60882321], [34153, 87955780.49693392], [34167, 87821244.10147187]] \ No newline at end of file diff --git a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.time_fit.json b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.time_fit.json index bad97ef617..ce399d57e1 100644 --- a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.time_fit.json +++ b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 0.0067133538508198105], [29225, 0.010486652798421045], [29239, 0.00900091296766373], [29253, 0.006697005302614288], [29267, 0.006675152950660134], [29281, 0.006682844924076062], [29295, 0.006679687793049374], [29309, 0.00667235838130658], [29323, 0.0066818252022242015], [29337, 0.006677075403254801], [29351, 0.006678568203676519], [29365, 0.006679033568753519], [29379, 0.006675124054391479], [29393, 0.006671167016796484], [29407, 0.006688501706278136], [29421, 0.0066766062459526244], [29435, 0.006695120765730363], [29449, 0.011274566393149651], [29463, 0.011523690461377082], [29477, 0.010541981138411587], [29547, 0.012332095500023446], [29561, 0.010633851391353288], [29575, 0.009299608287342763], [29603, 0.008449064390682527], [29617, 0.009115742974319108], [29631, 0.009141082372802416], [29645, 0.008945194459062385], [29659, 0.009364740022927621], [29673, 0.009087005589791844], [29743, 0.00932977541107754], [29757, 0.01006063546059744], [29771, 0.00917520268564824], [29785, 0.0106565722553697], [29799, 0.00912729043195045], [29813, 0.009282854985659741], [29827, 0.009041389067693108], [29841, 0.009379472773338572], [29855, 0.009761425401647872], [29869, 0.009374171503660926], [30009, 0.00886957996390344], [30023, 0.008894225026943026], [30037, 0.009585178978218534], [30051, 0.009042064837596647], [30065, 0.008836390299947297], [30079, 0.009115974025055021], [30093, 0.009401680345891786], [30107, 0.009440831940827605], [30121, 0.009083328770776188], [30135, 0.009097169090594777], [30149, 0.008750097050369839], [30163, 0.008982497457794334], [30177, 0.009822828501994126], [30191, 0.008946661849545625], [30205, 0.008920456689988641], [30219, 0.008631533974736455], [30233, 0.009761156636678356], [30247, 0.009138434108019598], [30261, 0.009337035775996629], [30513, 0.009091710042966465], [30527, 0.009555211965524588], [30541, 0.009400441888626933], [30555, 0.008753765453409312], [30569, 0.008925392204219847], [30583, 0.008892091918464465], [30597, 0.009812242556488233], [30625, 0.009432178470961712], [30639, 0.009372881523615003], [30653, 0.00977269237152141], [30667, 0.009510980100818207], [30681, 0.00947330486333022], [30695, 0.007880150300252593], [30709, 0.008901695768432277], [30723, 0.009968855722497508], [30737, 0.009396138674453176], [30751, 0.00905038526593921], [30765, 0.009016465704572983], [30779, 0.008211000366356434], [30793, 0.009129065113595168], [30807, 0.009443757542365715], [30821, 0.00945005636736701], [30835, 0.00919323723281456], [30849, 0.008852503654186064], [30863, 0.009358535068618981], [30877, 0.009109369393889975], [30891, 0.009423985508433748], [30905, 0.009371882452073805], [30919, 0.008918437832980344], [30933, 0.008935592113343768], [30947, 0.009296524960954556], [30961, 0.008972071936495183], [30975, 0.009158265127786721], [30989, 0.009489237848090686], [31003, 0.00908663934338595], [31017, 0.009122975814422249], [31031, 0.00883075743578066], [31045, 0.008986657743066638], [32095, 0.009668882014934231], [32109, 0.009422070646594817], [32123, 0.00949172935953334], [32137, 0.00894195095336255], [32151, 0.009512544141554367], [32165, 0.009438192974829042], [32179, 0.009658801031025439], [32193, 0.009567758357808752], [32207, 0.009200500208854415], [32221, 0.009525775169909283], [32235, 0.009617132734941023], [32249, 0.009712715443572377], [32263, 0.009221451631686858], [32277, 0.009210846539155415], [32305, 0.009309802455955822], [32319, 0.009258164761528668], [32333, 0.009861829686729676], [32347, 0.009455099018320173], [32361, 0.008979194796363622], [32375, 0.008759161177355604], [32389, 0.009388466596471672], [32403, 0.01030860439534174], [32417, 0.009211957033730758], [32431, 0.008896414998704881], [32445, 0.0099948533794963], [32585, 0.009746611498037603], [32599, 0.009529214753941384], [32613, 0.00960651270981665], [32627, 0.009844002073646918], [32641, 0.010048751824803501], [32655, 0.009625146713863726], [32851, 0.009255938585782634], [32865, 0.00943496466423874], [32879, 0.0096944206324992], [32893, 0.009616478461602455], [32907, 0.009589573210819033], [32921, 0.009555967340020167], [32991, 0.009475764112296396], [33005, 0.009086644822850005], [33019, 0.009540046597937722], [33033, 0.009399538780122157], [33047, 0.008997297064088328], [33061, 0.009447869325179636], [33075, 0.008986294667081207], [33089, 0.009379574838600057], [33103, 0.008873594995162182], [33117, 0.009553944022605065], [33131, 0.009088139526326328], [33145, 0.009583746581592174], [33159, 0.008906699140729259], [33187, 0.008767516497972761], [33201, 0.009911033765811738], [33215, 0.009485530786454097], [33229, 0.00886669048950668], [33243, 0.009216319441054142], [33271, 0.008823327596092957], [33299, 0.0089812590165799], [33313, 0.008882557369817152], [33327, 0.008898436350588042], [33341, 0.008698643295043624], [33355, 0.008366193000230254], [33369, 0.009005821307555612], [33383, 0.008631046409390145], [33397, 0.008923605131058714], [33411, 0.009008349107657378], [33425, 0.00980238918029204], [33439, 0.009767294381946144], [33453, 0.007977362428959151], [33467, 0.009301260773565367], [33523, 0.008385758693398217], [33537, 0.009058831295680995], [33551, 0.008701610451448414], [33649, 0.009141254244562124], [33705, 0.008107435385228644], [33719, 0.00907921261311105], [33733, 0.009184050837035357], [33747, 0.009355065014545853], [33761, 0.009990909569037693], [33775, 0.00866943889597056], [33803, 0.009505465606352624], [33817, 0.00877621086385801], [33831, 0.008716242280257325], [33845, 0.008189259204356349], [34041, 0.009431121484453138], [34055, 0.009645904155468862], [34069, 0.00890097697778982], [34083, 0.009681090036743261], [34125, 0.009363730013101782], [34139, 0.008553795651592588], [34153, 0.009429243531500575], [34167, 0.008591030800316386]] \ No newline at end of file +[[28511, 0.0067133538508198105], [29225, 0.010486652798421045], [29239, 0.00900091296766373], [29253, 0.006697005302614288], [29267, 0.006675152950660134], [29281, 0.006682844924076062], [29295, 0.006679687793049374], [29309, 0.00667235838130658], [29323, 0.0066818252022242015], [29337, 0.006677075403254801], [29351, 0.006678568203676519], [29365, 0.006679033568753519], [29379, 0.006675124054391479], [29393, 0.006671167016796484], [29407, 0.006688501706278136], [29421, 0.0066766062459526244], [29435, 0.006695120765730363], [29449, 0.011274566393149651], [29463, 0.011523690461377082], [29477, 0.010541981138411587], [29547, 0.012332095500023446], [29561, 0.010633851391353288], [29575, 0.009299608287342763], [29603, 0.008449064390682527], [29617, 0.009115742974319108], [29631, 0.009141082372802416], [29645, 0.008945194459062385], [29659, 0.009364740022927621], [29673, 0.009087005589791844], [29743, 0.00932977541107754], [29757, 0.01006063546059744], [29771, 0.00917520268564824], [29785, 0.0106565722553697], [29799, 0.00912729043195045], [29813, 0.009282854985659741], [29827, 0.009041389067693108], [29841, 0.009379472773338572], [29855, 0.009761425401647872], [29869, 0.009374171503660926], [30009, 0.00886957996390344], [30023, 0.008894225026943026], [30037, 0.009585178978218534], [30051, 0.009042064837596647], [30065, 0.008836390299947297], [30079, 0.009115974025055021], [30093, 0.009401680345891786], [30107, 0.009440831940827605], [30121, 0.009083328770776188], [30135, 0.009097169090594777], [30149, 0.008750097050369839], [30163, 0.008982497457794334], [30177, 0.009822828501994126], [30191, 0.008946661849545625], [30205, 0.008920456689988641], [30219, 0.008631533974736455], [30233, 0.009761156636678356], [30247, 0.009138434108019598], [30261, 0.009337035775996629], [30513, 0.009091710042966465], [30527, 0.009555211965524588], [30541, 0.009400441888626933], [30555, 0.008753765453409312], [30569, 0.008925392204219847], [30583, 0.008892091918464465], [30597, 0.009812242556488233], [30625, 0.009432178470961712], [30639, 0.009372881523615003], [30653, 0.00977269237152141], [30667, 0.009510980100818207], [30681, 0.00947330486333022], [30695, 0.007880150300252593], [30709, 0.008901695768432277], [30723, 0.009968855722497508], [30737, 0.009396138674453176], [30751, 0.00905038526593921], [30765, 0.009016465704572983], [30779, 0.008211000366356434], [30793, 0.009129065113595168], [30807, 0.009443757542365715], [30821, 0.00945005636736701], [30835, 0.00919323723281456], [30849, 0.008852503654186064], [30863, 0.009358535068618981], [30877, 0.009109369393889975], [30891, 0.009423985508433748], [30905, 0.009371882452073805], [30919, 0.008918437832980344], [30933, 0.008935592113343768], [30947, 0.009296524960954556], [30961, 0.008972071936495183], [30975, 0.009158265127786721], [30989, 0.009489237848090686], [31003, 0.00908663934338595], [31017, 0.009122975814422249], [31031, 0.00883075743578066], [31045, 0.008986657743066638], [32095, 0.009668882014934231], [32109, 0.009422070646594817], [32123, 0.00949172935953334], [32137, 0.00894195095336255], [32151, 0.009512544141554367], [32165, 0.009438192974829042], [32179, 0.009658801031025439], [32193, 0.009567758357808752], [32207, 0.009200500208854415], [32221, 0.009525775169909283], [32235, 0.009617132734941023], [32249, 0.009712715443572377], [32263, 0.009221451631686858], [32277, 0.009210846539155415], [32305, 0.009309802455955822], [32319, 0.009258164761528668], [32333, 0.009861829686729676], [32347, 0.009455099018320173], [32361, 0.008979194796363622], [32375, 0.008759161177355604], [32389, 0.009388466596471672], [32403, 0.01030860439534174], [32417, 0.009211957033730758], [32431, 0.008896414998704881], [32445, 0.0099948533794963], [32585, 0.009746611498037603], [32599, 0.009529214753941384], [32613, 0.00960651270981665], [32627, 0.009844002073646918], [32641, 0.010048751824803501], [32655, 0.009625146713863726], [32851, 0.009255938585782634], [32865, 0.00943496466423874], [32879, 0.0096944206324992], [32893, 0.009616478461602455], [32907, 0.009589573210819033], [32921, 0.009555967340020167], [32991, 0.009475764112296396], [33005, 0.009086644822850005], [33019, 0.009540046597937722], [33033, 0.009399538780122157], [33047, 0.008997297064088328], [33061, 0.009447869325179636], [33075, 0.008986294667081207], [33089, 0.009379574838600057], [33103, 0.008873594995162182], [33117, 0.009553944022605065], [33131, 0.009088139526326328], [33145, 0.009583746581592174], [33159, 0.008906699140729259], [33187, 0.008767516497972761], [33201, 0.009911033765811738], [33215, 0.009485530786454097], [33229, 0.00886669048950668], [33243, 0.009216319441054142], [33271, 0.008823327596092957], [33299, 0.0089812590165799], [33313, 0.008882557369817152], [33327, 0.008898436350588042], [33341, 0.008698643295043624], [33355, 0.008366193000230254], [33369, 0.009005821307555612], [33383, 0.008631046409390145], [33397, 0.008923605131058714], [33411, 0.009008349107657378], [33425, 0.00980238918029204], [33439, 0.009767294381946144], [33453, 0.007977362428959151], [33467, 0.009301260773565367], [33523, 0.008385758693398217], [33537, 0.009058831295680995], [33551, 0.008701610451448414], [33649, 0.009141254244562124], [33705, 0.008107435385228644], [33719, 0.00907921261311105], [33733, 0.009184050837035357], [33747, 0.009355065014545853], [33761, 0.009990909569037693], [33775, 0.00866943889597056], [33803, 0.009505465606352624], [33817, 0.00877621086385801], [33831, 0.008716242280257325], [33845, 0.008189259204356349], [34041, 0.009431121484453138], [34055, 0.009645904155468862], [34069, 0.00890097697778982], [34083, 0.009681090036743261], [34125, 0.009363730013101782], [34139, 0.008553795651592588], [34153, 0.009429243531500575], [34167, 0.008435079802566758]] \ No newline at end of file diff --git a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.time_predict.json b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.time_predict.json index 24539e0cea..bccab28276 100644 --- a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.time_predict.json +++ b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.time_predict.json @@ -1 +1 @@ -[[28511, 2.331862609994853], [29225, 3.898049177156416], [29239, 4.07952922784767], [29253, 2.371289297071943], [29267, 2.3241616666512503], [29281, 2.345245892128356], [29295, 2.338685010042108], [29309, 2.3599209228205904], [29323, 2.3435054179565387], [29337, 2.3825263546184114], [29351, 2.383600319074111], [29365, 2.310052942555491], [29379, 2.386306246111059], [29393, 2.355000449890173], [29407, 2.382677464414737], [29421, 2.4096530505346037], [29435, 2.372631751366175], [29449, 4.183555165714814], [29463, 4.289797256654881], [29477, 4.3315392224252385], [29547, 4.776817146470581], [29561, 4.1004244893200115], [29575, 3.1914575252760553], [29603, 3.227230712999482], [29617, 3.2672226642738247], [29631, 3.223827448134354], [29645, 3.230038664879566], [29659, 3.2859523987630728], [29673, 3.2298667421484275], [29743, 3.35739150406838], [29757, 3.396921282526543], [29771, 3.270026034693911], [29785, 4.498480136603142], [29799, 3.997803288399647], [29813, 3.8965624754578845], [29827, 3.9179711395816725], [29841, 3.871875204959194], [29855, 4.05599725616755], [29869, 3.83204613682139], [30009, 3.9911262483740564], [30023, 3.9368271629417215], [30037, 3.9433706631556604], [30051, 3.819669248032729], [30065, 3.9076743361622728], [30079, 3.9717058907987526], [30093, 3.92102051405511], [30107, 3.939505437553384], [30121, 3.9766054105833706], [30135, 4.013599245932312], [30149, 4.086255129185543], [30163, 3.970077754597384], [30177, 4.043076108723483], [30191, 3.969852866714009], [30205, 3.983613233822171], [30219, 3.9141160192301996], [30233, 3.889088603385964], [30247, 3.9636272005973745], [30261, 4.018889965452346], [30513, 3.9928988522563076], [30527, 4.017843839522412], [30541, 3.941876649137155], [30555, 3.959681185211854], [30569, 3.9820404632888686], [30583, 4.091229244146272], [30597, 3.8728303652601994], [30625, 4.008997222606733], [30639, 3.8485990127007392], [30653, 3.9765878352880377], [30667, 4.017595713292278], [30681, 4.034975998853756], [30695, 3.9843513384901934], [30709, 3.924515810881726], [30723, 4.092932118927075], [30737, 4.014499813448928], [30751, 3.9590738987276666], [30765, 3.963449195389219], [30779, 4.091614197988834], [30793, 3.9178702672776566], [30807, 4.069220890922864], [30821, 3.89904774759433], [30835, 4.015324221636062], [30849, 3.905144635774569], [30863, 3.9471986920004323], [30877, 3.7443072224174583], [30891, 4.024500259111631], [30905, 4.045300472434095], [30919, 3.9670181635883903], [30933, 3.933973856834214], [30947, 4.056298130088758], [30961, 3.929075776434948], [30975, 3.9326058115246205], [30989, 4.011548849753431], [31003, 4.000375972534933], [31017, 4.164911523817792], [31031, 4.064218137364556], [31045, 3.9129981205862396], [32095, 1.9018761162953772], [32109, 2.0186907288829636], [32123, 1.9289979928467915], [32137, 1.9948289760054516], [32151, 2.0163024631547195], [32165, 1.9327898558900136], [32179, 2.003984400169398], [32193, 1.8863256174015606], [32207, 1.9154106308192305], [32221, 1.9493401980086968], [32235, 2.056855478170172], [32249, 2.0263341345953254], [32263, 2.017867365311173], [32277, 2.0399937443193292], [32305, 1.9919100212591978], [32319, 1.9302894739459286], [32333, 1.9476734307867818], [32347, 1.9849774127421456], [32361, 1.8837682702978864], [32375, 1.9880018383881848], [32389, 1.9519396363694137], [32403, 2.0260661011209007], [32417, 1.9847548582891437], [32431, 1.8467419183168903], [32445, 2.0120897787445275], [32585, 1.8004067648496607], [32599, 1.8517204775414269], [32613, 1.7976693368701069], [32627, 1.737051264691795], [32641, 1.7768681569435207], [32655, 1.6875234793384921], [32851, 1.905935546613726], [32865, 1.9242760407520376], [32879, 1.9330236659821498], [32893, 1.902058681034907], [32907, 1.9690009847476404], [32921, 1.9262450434573373], [32991, 1.899174231888412], [33005, 1.8381646341592872], [33019, 1.9191800100053733], [33033, 1.5434076786074553], [33047, 1.1283819776955348], [33061, 1.145686502560297], [33075, 1.1280881493047032], [33089, 1.1643614795582131], [33103, 1.1697067865726944], [33117, 1.151188911837187], [33131, 1.1617302816895765], [33145, 1.1847614151190275], [33159, 1.205189389318906], [33187, 1.154030125788494], [33201, 1.150875971098807], [33215, 1.1950656259822336], [33229, 1.2193701998297977], [33243, 1.2222026359240237], [33271, 1.2480035243849135], [33299, 1.2825839829889267], [33313, 1.1893740968705826], [33327, 1.219199320538578], [33341, 1.2375632000621923], [33355, 1.2202154994279866], [33369, 1.1496163782884692], [33383, 1.2039242995871033], [33397, 1.2167884642916267], [33411, 1.1785320457141915], [33425, 1.2436555022276314], [33439, 1.2870146307342396], [33453, 1.2980253241119497], [33467, 1.348902312488998], [33523, 1.3355115730834084], [33537, 1.3114149751122917], [33551, 1.2926766048350418], [33649, 2.995296443773345], [33705, 2.9860135680025963], [33719, 2.9744914881695195], [33733, 1.3431835112647805], [33747, 1.3414228022562191], [33761, 1.3413272821895375], [33775, 1.3510390765853153], [33803, 1.3520602022333366], [33817, 1.3039650261918265], [33831, 1.3158794203581505], [33845, 1.3211042673800455], [34041, 2.966136466020841], [34055, 3.008083555454643], [34069, 2.9985042469491856], [34083, 2.490161171130283], [34125, 1.3494039910551472], [34139, 1.3569357404496316], [34153, 1.3369506611465714], [34167, 1.3595074836704244]] \ No newline at end of file +[[28511, 2.331862609994853], [29225, 3.898049177156416], [29239, 4.07952922784767], [29253, 2.371289297071943], [29267, 2.3241616666512503], [29281, 2.345245892128356], [29295, 2.338685010042108], [29309, 2.3599209228205904], [29323, 2.3435054179565387], [29337, 2.3825263546184114], [29351, 2.383600319074111], [29365, 2.310052942555491], [29379, 2.386306246111059], [29393, 2.355000449890173], [29407, 2.382677464414737], [29421, 2.4096530505346037], [29435, 2.372631751366175], [29449, 4.183555165714814], [29463, 4.289797256654881], [29477, 4.3315392224252385], [29547, 4.776817146470581], [29561, 4.1004244893200115], [29575, 3.1914575252760553], [29603, 3.227230712999482], [29617, 3.2672226642738247], [29631, 3.223827448134354], [29645, 3.230038664879566], [29659, 3.2859523987630728], [29673, 3.2298667421484275], [29743, 3.35739150406838], [29757, 3.396921282526543], [29771, 3.270026034693911], [29785, 4.498480136603142], [29799, 3.997803288399647], [29813, 3.8965624754578845], [29827, 3.9179711395816725], [29841, 3.871875204959194], [29855, 4.05599725616755], [29869, 3.83204613682139], [30009, 3.9911262483740564], [30023, 3.9368271629417215], [30037, 3.9433706631556604], [30051, 3.819669248032729], [30065, 3.9076743361622728], [30079, 3.9717058907987526], [30093, 3.92102051405511], [30107, 3.939505437553384], [30121, 3.9766054105833706], [30135, 4.013599245932312], [30149, 4.086255129185543], [30163, 3.970077754597384], [30177, 4.043076108723483], [30191, 3.969852866714009], [30205, 3.983613233822171], [30219, 3.9141160192301996], [30233, 3.889088603385964], [30247, 3.9636272005973745], [30261, 4.018889965452346], [30513, 3.9928988522563076], [30527, 4.017843839522412], [30541, 3.941876649137155], [30555, 3.959681185211854], [30569, 3.9820404632888686], [30583, 4.091229244146272], [30597, 3.8728303652601994], [30625, 4.008997222606733], [30639, 3.8485990127007392], [30653, 3.9765878352880377], [30667, 4.017595713292278], [30681, 4.034975998853756], [30695, 3.9843513384901934], [30709, 3.924515810881726], [30723, 4.092932118927075], [30737, 4.014499813448928], [30751, 3.9590738987276666], [30765, 3.963449195389219], [30779, 4.091614197988834], [30793, 3.9178702672776566], [30807, 4.069220890922864], [30821, 3.89904774759433], [30835, 4.015324221636062], [30849, 3.905144635774569], [30863, 3.9471986920004323], [30877, 3.7443072224174583], [30891, 4.024500259111631], [30905, 4.045300472434095], [30919, 3.9670181635883903], [30933, 3.933973856834214], [30947, 4.056298130088758], [30961, 3.929075776434948], [30975, 3.9326058115246205], [30989, 4.011548849753431], [31003, 4.000375972534933], [31017, 4.164911523817792], [31031, 4.064218137364556], [31045, 3.9129981205862396], [32095, 1.9018761162953772], [32109, 2.0186907288829636], [32123, 1.9289979928467915], [32137, 1.9948289760054516], [32151, 2.0163024631547195], [32165, 1.9327898558900136], [32179, 2.003984400169398], [32193, 1.8863256174015606], [32207, 1.9154106308192305], [32221, 1.9493401980086968], [32235, 2.056855478170172], [32249, 2.0263341345953254], [32263, 2.017867365311173], [32277, 2.0399937443193292], [32305, 1.9919100212591978], [32319, 1.9302894739459286], [32333, 1.9476734307867818], [32347, 1.9849774127421456], [32361, 1.8837682702978864], [32375, 1.9880018383881848], [32389, 1.9519396363694137], [32403, 2.0260661011209007], [32417, 1.9847548582891437], [32431, 1.8467419183168903], [32445, 2.0120897787445275], [32585, 1.8004067648496607], [32599, 1.8517204775414269], [32613, 1.7976693368701069], [32627, 1.737051264691795], [32641, 1.7768681569435207], [32655, 1.6875234793384921], [32851, 1.905935546613726], [32865, 1.9242760407520376], [32879, 1.9330236659821498], [32893, 1.902058681034907], [32907, 1.9690009847476404], [32921, 1.9262450434573373], [32991, 1.899174231888412], [33005, 1.8381646341592872], [33019, 1.9191800100053733], [33033, 1.5434076786074553], [33047, 1.1283819776955348], [33061, 1.145686502560297], [33075, 1.1280881493047032], [33089, 1.1643614795582131], [33103, 1.1697067865726944], [33117, 1.151188911837187], [33131, 1.1617302816895765], [33145, 1.1847614151190275], [33159, 1.205189389318906], [33187, 1.154030125788494], [33201, 1.150875971098807], [33215, 1.1950656259822336], [33229, 1.2193701998297977], [33243, 1.2222026359240237], [33271, 1.2480035243849135], [33299, 1.2825839829889267], [33313, 1.1893740968705826], [33327, 1.219199320538578], [33341, 1.2375632000621923], [33355, 1.2202154994279866], [33369, 1.1496163782884692], [33383, 1.2039242995871033], [33397, 1.2167884642916267], [33411, 1.1785320457141915], [33425, 1.2436555022276314], [33439, 1.2870146307342396], [33453, 1.2980253241119497], [33467, 1.348902312488998], [33523, 1.3355115730834084], [33537, 1.3114149751122917], [33551, 1.2926766048350418], [33649, 2.995296443773345], [33705, 2.9860135680025963], [33719, 2.9744914881695195], [33733, 1.3431835112647805], [33747, 1.3414228022562191], [33761, 1.3413272821895375], [33775, 1.3510390765853153], [33803, 1.3520602022333366], [33817, 1.3039650261918265], [33831, 1.3158794203581505], [33845, 1.3211042673800455], [34041, 2.966136466020841], [34055, 3.008083555454643], [34069, 2.9985042469491856], [34083, 2.490161171130283], [34125, 1.3494039910551472], [34139, 1.3569357404496316], [34153, 1.3369506611465714], [34167, 1.3628857279544573]] \ No newline at end of file diff --git a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.track_test_score.json b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.track_test_score.json index c5ebd258ab..7ecf065f16 100644 --- a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.track_test_score.json +++ b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.track_test_score.json @@ -1 +1 @@ -[[28511, 0.5304296401474852], [29225, 0.5435677639519915], [29239, 0.5358525726369026], [29253, 0.5364655026605911], [29267, 0.5451953240816612], [29281, 0.5448573762865215], [29295, 0.5404352548035095], [29309, 0.53600375921964], [29323, 0.5347296556098653], [29337, 0.5343121045221086], [29351, 0.5470706002852664], [29365, 0.5359586810332191], [29379, 0.5364895062389358], [29393, 0.5390045584126085], [29407, 0.5405621009400896], [29421, 0.5407259043435724], [29435, 0.5408745990163614], [29449, 0.5342931980497451], [29463, 0.5380413752536125], [29477, 0.5347739609749047], [29547, 0.5271866701500026], [29561, 0.541688471125679], [29575, 0.5205903808776229], [29603, 0.5389866646451336], [29617, 0.5383752460316965], [29631, 0.5426768420483309], [29645, 0.5385419418230524], [29659, 0.5453181736416725], [29673, 0.5402852648352706], [29743, 0.537950997990916], [29757, 0.5329631061559033], [29771, 0.5384349744852523], [29785, 0.5347002361491758], [29799, 0.5367563989339235], [29813, 0.5411098619141617], [29827, 0.5414468575580607], [29841, 0.5443114237041228], [29855, 0.5336698698124878], [29869, 0.5261383216469127], [30009, 0.5398067489667524], [30023, 0.5386470926855564], [30037, 0.5396933722809276], [30051, 0.5355959415350645], [30065, 0.5408850973250264], [30079, 0.5412118955284788], [30093, 0.5430676145609026], [30107, 0.5369809179307018], [30121, 0.5428282510055342], [30135, 0.54058500247365], [30149, 0.5372831546093129], [30163, 0.5304587600435215], [30177, 0.5351179923387155], [30191, 0.5395484687124676], [30205, 0.5398934256719093], [30219, 0.5389364997290357], [30233, 0.5315758669679815], [30247, 0.5432615399038407], [30261, 0.5413399372205578], [30513, 0.5380239609770381], [30527, 0.5408181191369088], [30541, 0.5461994585059794], [30555, 0.538957854511397], [30569, 0.5363525451488775], [30583, 0.5440825524549343], [30597, 0.537696430194267], [30625, 0.5411638331316313], [30639, 0.5379516291699682], [30653, 0.5378229548588273], [30667, 0.5276533344592617], [30681, 0.5373423482116552], [30695, 0.5405178961214636], [30709, 0.5276696814261057], [30723, 0.5424753717957563], [30737, 0.5372978608284983], [30751, 0.5383163948470583], [30765, 0.5325626558166469], [30779, 0.5405662087845232], [30793, 0.5348775396324172], [30807, 0.5443296111982625], [30821, 0.5399243716399811], [30835, 0.5421470986162547], [30849, 0.549072949770066], [30863, 0.5383908905788282], [30877, 0.5381047975196144], [30891, 0.5449977109286572], [30905, 0.5359660255679707], [30919, 0.534785858719775], [30933, 0.5357726152568947], [30947, 0.5383781028759272], [30961, 0.5417373377755801], [30975, 0.5342695742339358], [30989, 0.5373135481223617], [31003, 0.5414197749759467], [31017, 0.5345607785072869], [31031, 0.5382771895301448], [31045, 0.5373437077708487], [32095, 0.5310415674990736], [32109, 0.5433737804347902], [32123, 0.5381628675793328], [32137, 0.5374840514003393], [32151, 0.5339440237058176], [32165, 0.5376052215842781], [32179, 0.5313540652452653], [32193, 0.5452220478993118], [32207, 0.5355753759378156], [32221, 0.5391271838828052], [32235, 0.539203626084433], [32249, 0.5432427068759428], [32263, 0.5327907695005649], [32277, 0.5358503592717225], [32305, 0.5400589395906151], [32319, 0.5317598983365414], [32333, 0.5321548771002558], [32347, 0.5381053598680023], [32361, 0.5363646214651235], [32375, 0.5377955317834872], [32389, 0.5356405038163995], [32403, 0.5262928616566415], [32417, 0.5316566113144975], [32431, 0.5360375464332019], [32445, 0.5429459257712435], [32585, 0.5342869095130919], [32599, 0.5415031378933849], [32613, 0.538501340839932], [32627, 0.5397615300789395], [32641, 0.551083971227253], [32655, 0.5399337563720609], [32851, 0.5408942047909653], [32865, 0.5417894064564834], [32879, 0.5375506107202952], [32893, 0.5340817970422113], [32907, 0.5389863204047178], [32921, 0.5332335655120679], [32991, 0.5350741757876865], [33005, 0.538564109143374], [33019, 0.5371951461984352], [33033, 0.5403073870419124], [33047, 0.5373775186402734], [33061, 0.5384152475502046], [33075, 0.53820972314196], [33089, 0.5417961132578744], [33103, 0.5373853822898137], [33117, 0.5321928100958211], [33131, 0.5450450591818943], [33145, 0.5362980249992371], [33159, 0.5531938513446659], [33187, 0.5303795178342905], [33201, 0.531943837965021], [33215, 0.5411529605704015], [33229, 0.5443646059686491], [33243, 0.542464051491967], [33271, 0.5383707961318093], [33299, 0.5292346043462136], [33313, 0.5357073825818155], [33327, 0.5388801824415717], [33341, 0.5442136975196981], [33355, 0.536147719704116], [33369, 0.5339168192045264], [33383, 0.5409514332632], [33397, 0.5317573597163396], [33411, 0.5285937076117263], [33425, 0.5380927622232753], [33439, 0.5352476101886017], [33453, 0.5461779330920111], [33467, 0.5377812463092875], [33523, 0.5402717771320847], [33537, 0.5324372049505723], [33551, 0.5403010370575477], [33649, 0.5363367106182314], [33705, 0.5276048775930409], [33719, 0.5377361726275165], [33733, 0.5331683074791285], [33747, 0.536957042686651], [33761, 0.5397856934212438], [33775, 0.541451173234687], [33803, 0.5311495047143187], [33817, 0.5396854205211961], [33831, 0.5365071707626653], [33845, 0.5382428422747035], [34041, 0.5400263944783228], [34055, 0.5405897210216756], [34069, 0.5380140538510138], [34083, 0.5362972491533605], [34125, 0.5410034500669795], [34139, 0.547588596373119], [34153, 0.5337069096707251], [34167, 0.5331861079028895]] \ No newline at end of file +[[28511, 0.5304296401474852], [29225, 0.5435677639519915], [29239, 0.5358525726369026], [29253, 0.5364655026605911], [29267, 0.5451953240816612], [29281, 0.5448573762865215], [29295, 0.5404352548035095], [29309, 0.53600375921964], [29323, 0.5347296556098653], [29337, 0.5343121045221086], [29351, 0.5470706002852664], [29365, 0.5359586810332191], [29379, 0.5364895062389358], [29393, 0.5390045584126085], [29407, 0.5405621009400896], [29421, 0.5407259043435724], [29435, 0.5408745990163614], [29449, 0.5342931980497451], [29463, 0.5380413752536125], [29477, 0.5347739609749047], [29547, 0.5271866701500026], [29561, 0.541688471125679], [29575, 0.5205903808776229], [29603, 0.5389866646451336], [29617, 0.5383752460316965], [29631, 0.5426768420483309], [29645, 0.5385419418230524], [29659, 0.5453181736416725], [29673, 0.5402852648352706], [29743, 0.537950997990916], [29757, 0.5329631061559033], [29771, 0.5384349744852523], [29785, 0.5347002361491758], [29799, 0.5367563989339235], [29813, 0.5411098619141617], [29827, 0.5414468575580607], [29841, 0.5443114237041228], [29855, 0.5336698698124878], [29869, 0.5261383216469127], [30009, 0.5398067489667524], [30023, 0.5386470926855564], [30037, 0.5396933722809276], [30051, 0.5355959415350645], [30065, 0.5408850973250264], [30079, 0.5412118955284788], [30093, 0.5430676145609026], [30107, 0.5369809179307018], [30121, 0.5428282510055342], [30135, 0.54058500247365], [30149, 0.5372831546093129], [30163, 0.5304587600435215], [30177, 0.5351179923387155], [30191, 0.5395484687124676], [30205, 0.5398934256719093], [30219, 0.5389364997290357], [30233, 0.5315758669679815], [30247, 0.5432615399038407], [30261, 0.5413399372205578], [30513, 0.5380239609770381], [30527, 0.5408181191369088], [30541, 0.5461994585059794], [30555, 0.538957854511397], [30569, 0.5363525451488775], [30583, 0.5440825524549343], [30597, 0.537696430194267], [30625, 0.5411638331316313], [30639, 0.5379516291699682], [30653, 0.5378229548588273], [30667, 0.5276533344592617], [30681, 0.5373423482116552], [30695, 0.5405178961214636], [30709, 0.5276696814261057], [30723, 0.5424753717957563], [30737, 0.5372978608284983], [30751, 0.5383163948470583], [30765, 0.5325626558166469], [30779, 0.5405662087845232], [30793, 0.5348775396324172], [30807, 0.5443296111982625], [30821, 0.5399243716399811], [30835, 0.5421470986162547], [30849, 0.549072949770066], [30863, 0.5383908905788282], [30877, 0.5381047975196144], [30891, 0.5449977109286572], [30905, 0.5359660255679707], [30919, 0.534785858719775], [30933, 0.5357726152568947], [30947, 0.5383781028759272], [30961, 0.5417373377755801], [30975, 0.5342695742339358], [30989, 0.5373135481223617], [31003, 0.5414197749759467], [31017, 0.5345607785072869], [31031, 0.5382771895301448], [31045, 0.5373437077708487], [32095, 0.5310415674990736], [32109, 0.5433737804347902], [32123, 0.5381628675793328], [32137, 0.5374840514003393], [32151, 0.5339440237058176], [32165, 0.5376052215842781], [32179, 0.5313540652452653], [32193, 0.5452220478993118], [32207, 0.5355753759378156], [32221, 0.5391271838828052], [32235, 0.539203626084433], [32249, 0.5432427068759428], [32263, 0.5327907695005649], [32277, 0.5358503592717225], [32305, 0.5400589395906151], [32319, 0.5317598983365414], [32333, 0.5321548771002558], [32347, 0.5381053598680023], [32361, 0.5363646214651235], [32375, 0.5377955317834872], [32389, 0.5356405038163995], [32403, 0.5262928616566415], [32417, 0.5316566113144975], [32431, 0.5360375464332019], [32445, 0.5429459257712435], [32585, 0.5342869095130919], [32599, 0.5415031378933849], [32613, 0.538501340839932], [32627, 0.5397615300789395], [32641, 0.551083971227253], [32655, 0.5399337563720609], [32851, 0.5408942047909653], [32865, 0.5417894064564834], [32879, 0.5375506107202952], [32893, 0.5340817970422113], [32907, 0.5389863204047178], [32921, 0.5332335655120679], [32991, 0.5350741757876865], [33005, 0.538564109143374], [33019, 0.5371951461984352], [33033, 0.5403073870419124], [33047, 0.5373775186402734], [33061, 0.5384152475502046], [33075, 0.53820972314196], [33089, 0.5417961132578744], [33103, 0.5373853822898137], [33117, 0.5321928100958211], [33131, 0.5450450591818943], [33145, 0.5362980249992371], [33159, 0.5531938513446659], [33187, 0.5303795178342905], [33201, 0.531943837965021], [33215, 0.5411529605704015], [33229, 0.5443646059686491], [33243, 0.542464051491967], [33271, 0.5383707961318093], [33299, 0.5292346043462136], [33313, 0.5357073825818155], [33327, 0.5388801824415717], [33341, 0.5442136975196981], [33355, 0.536147719704116], [33369, 0.5339168192045264], [33383, 0.5409514332632], [33397, 0.5317573597163396], [33411, 0.5285937076117263], [33425, 0.5380927622232753], [33439, 0.5352476101886017], [33453, 0.5461779330920111], [33467, 0.5377812463092875], [33523, 0.5402717771320847], [33537, 0.5324372049505723], [33551, 0.5403010370575477], [33649, 0.5363367106182314], [33705, 0.5276048775930409], [33719, 0.5377361726275165], [33733, 0.5331683074791285], [33747, 0.536957042686651], [33761, 0.5397856934212438], [33775, 0.541451173234687], [33803, 0.5311495047143187], [33817, 0.5396854205211961], [33831, 0.5365071707626653], [33845, 0.5382428422747035], [34041, 0.5400263944783228], [34055, 0.5405897210216756], [34069, 0.5380140538510138], [34083, 0.5362972491533605], [34125, 0.5410034500669795], [34139, 0.547588596373119], [34153, 0.5337069096707251], [34167, 0.534695611174715]] \ No newline at end of file diff --git a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.track_train_score.json b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.track_train_score.json index 251d84d080..5672b99e41 100644 --- a/graphs/summary/neighbors.KNeighborsClassifierBenchmark.track_train_score.json +++ b/graphs/summary/neighbors.KNeighborsClassifierBenchmark.track_train_score.json @@ -1 +1 @@ -[[28511, 0.709043232101892], [29225, 0.7132817768760275], [29239, 0.7116749318998883], [29253, 0.7110309911545071], [29267, 0.7123938234960818], [29281, 0.7126119636132864], [29295, 0.7082609196458879], [29309, 0.7099724770074312], [29323, 0.711573343924489], [29337, 0.7096188727959439], [29351, 0.7129623254698609], [29365, 0.7136452124353173], [29379, 0.7099752142359654], [29393, 0.7084754858489033], [29407, 0.7096995803136866], [29421, 0.7110523149436765], [29435, 0.7104127118070163], [29449, 0.7106905918011365], [29463, 0.7096087102500549], [29477, 0.7102917496509723], [29547, 0.7073895430009078], [29561, 0.7109914720433563], [29575, 0.7074502671160456], [29603, 0.7099078127052414], [29617, 0.7107695345958744], [29631, 0.7082341021854921], [29645, 0.7087541317415884], [29659, 0.711680655110528], [29673, 0.7123085438742353], [29743, 0.7090402432160277], [29757, 0.7076495585914149], [29771, 0.7094661116912311], [29785, 0.7112015756905263], [29799, 0.7092628509443799], [29813, 0.7107304747434102], [29827, 0.7086119826916129], [29841, 0.709284236748809], [29855, 0.704291306403425], [29869, 0.7086141446492285], [30009, 0.7115307288722433], [30023, 0.7096243106105633], [30037, 0.7105595551020875], [30051, 0.7129110123668244], [30065, 0.7089950852554022], [30079, 0.7107638986617953], [30093, 0.7108181230701487], [30107, 0.7115271012304283], [30121, 0.7134430835407198], [30135, 0.7109225759943463], [30149, 0.7112157604605962], [30163, 0.7083816221036651], [30177, 0.7088076196532476], [30191, 0.7107475279495287], [30205, 0.7112558311252034], [30219, 0.7099361213097795], [30233, 0.7076384966063289], [30247, 0.7115922523152858], [30261, 0.7111924618001526], [30513, 0.7104109796311185], [30527, 0.7115583322695904], [30541, 0.7130106418127605], [30555, 0.7099796103167783], [30569, 0.709288216924268], [30583, 0.7119405080249659], [30597, 0.7095412543084361], [30625, 0.7128614373655292], [30639, 0.710945043754752], [30653, 0.7098590293930527], [30667, 0.7097658940588805], [30681, 0.7123038930525487], [30695, 0.7112964289071013], [30709, 0.7082594579226886], [30723, 0.708864492950664], [30737, 0.7064840553358652], [30751, 0.7116446995008369], [30765, 0.7090850741390994], [30779, 0.7158601102899571], [30793, 0.7112323335085344], [30807, 0.7097821682648325], [30821, 0.7127815789620088], [30835, 0.7105365906210509], [30849, 0.713088126270239], [30863, 0.7126444620375175], [30877, 0.709715869247546], [30891, 0.705474060799359], [30905, 0.708510425600117], [30919, 0.7074110737009761], [30933, 0.7102646301681691], [30947, 0.7106961134003682], [30961, 0.7118041159872946], [30975, 0.7104369315799786], [30989, 0.7114030203417722], [31003, 0.7110632887011488], [31017, 0.705368674536293], [31031, 0.7071327560381201], [31045, 0.7075730667774516], [32095, 0.7056246158104333], [32109, 0.710584280460473], [32123, 0.709903782943401], [32137, 0.7089228822611774], [32151, 0.7076085682332449], [32165, 0.7090502811430252], [32179, 0.7082107496817684], [32193, 0.7135907331189242], [32207, 0.7092606693362141], [32221, 0.7100361028756826], [32235, 0.7099381874077219], [32249, 0.7071136541627123], [32263, 0.7120211562107974], [32277, 0.7111434076290518], [32305, 0.7099136118506584], [32319, 0.7104387571264517], [32333, 0.7099999030389844], [32347, 0.7100814171596272], [32361, 0.7103415612776008], [32375, 0.7123303070158281], [32389, 0.7116456768147933], [32403, 0.7046391308649365], [32417, 0.7103892764367964], [32431, 0.708064074990753], [32445, 0.7155749016946209], [32585, 0.708190310147589], [32599, 0.713904534877277], [32613, 0.7110431074673564], [32627, 0.7111815700680717], [32641, 0.7152453197600039], [32655, 0.7093326585697985], [32851, 0.7093875902869712], [32865, 0.7110082741418622], [32879, 0.7074946421245176], [32893, 0.7086190095306976], [32907, 0.7108284545384066], [32921, 0.7092495249001283], [32991, 0.7114599440032879], [33005, 0.7145512074672161], [33019, 0.7058530084767077], [33033, 0.7079413975115669], [33047, 0.7075235935845045], [33061, 0.7136681450039533], [33075, 0.7129928053196629], [33089, 0.710750133705571], [33103, 0.7093206158991041], [33117, 0.7091328463954876], [33131, 0.7100089698935188], [33145, 0.7110836216372629], [33159, 0.7151649941030345], [33187, 0.7130086280127647], [33201, 0.7085888284650943], [33215, 0.70937378871421], [33229, 0.7111641479728945], [33243, 0.7121050260992746], [33271, 0.7103643162141833], [33299, 0.705611185055584], [33313, 0.7111597622733451], [33327, 0.710866422485037], [33341, 0.7125425374906456], [33355, 0.7103406391770531], [33369, 0.7094882480455365], [33383, 0.7131138306487328], [33397, 0.7103854616136798], [33411, 0.7065718452104044], [33425, 0.7133031510674128], [33439, 0.7073642032767745], [33453, 0.7121883704041998], [33467, 0.7121726036638236], [33523, 0.7104914721270839], [33537, 0.7103431310671473], [33551, 0.7108725463220531], [33649, 0.7129922560286037], [33705, 0.709454017708782], [33719, 0.7109622664453225], [33733, 0.710667590902187], [33747, 0.7126422024276997], [33761, 0.7090921880179738], [33775, 0.7130789250253504], [33803, 0.7040964922971961], [33817, 0.7125730678210005], [33831, 0.7085105651423439], [33845, 0.7107166899802091], [34041, 0.7098459173756511], [34055, 0.7096548895936378], [34069, 0.7104456587396241], [34083, 0.7118186328567644], [34125, 0.7123113289394434], [34139, 0.7123840665312661], [34153, 0.7087330207196009], [34167, 0.7093877245271187]] \ No newline at end of file +[[28511, 0.709043232101892], [29225, 0.7132817768760275], [29239, 0.7116749318998883], [29253, 0.7110309911545071], [29267, 0.7123938234960818], [29281, 0.7126119636132864], [29295, 0.7082609196458879], [29309, 0.7099724770074312], [29323, 0.711573343924489], [29337, 0.7096188727959439], [29351, 0.7129623254698609], [29365, 0.7136452124353173], [29379, 0.7099752142359654], [29393, 0.7084754858489033], [29407, 0.7096995803136866], [29421, 0.7110523149436765], [29435, 0.7104127118070163], [29449, 0.7106905918011365], [29463, 0.7096087102500549], [29477, 0.7102917496509723], [29547, 0.7073895430009078], [29561, 0.7109914720433563], [29575, 0.7074502671160456], [29603, 0.7099078127052414], [29617, 0.7107695345958744], [29631, 0.7082341021854921], [29645, 0.7087541317415884], [29659, 0.711680655110528], [29673, 0.7123085438742353], [29743, 0.7090402432160277], [29757, 0.7076495585914149], [29771, 0.7094661116912311], [29785, 0.7112015756905263], [29799, 0.7092628509443799], [29813, 0.7107304747434102], [29827, 0.7086119826916129], [29841, 0.709284236748809], [29855, 0.704291306403425], [29869, 0.7086141446492285], [30009, 0.7115307288722433], [30023, 0.7096243106105633], [30037, 0.7105595551020875], [30051, 0.7129110123668244], [30065, 0.7089950852554022], [30079, 0.7107638986617953], [30093, 0.7108181230701487], [30107, 0.7115271012304283], [30121, 0.7134430835407198], [30135, 0.7109225759943463], [30149, 0.7112157604605962], [30163, 0.7083816221036651], [30177, 0.7088076196532476], [30191, 0.7107475279495287], [30205, 0.7112558311252034], [30219, 0.7099361213097795], [30233, 0.7076384966063289], [30247, 0.7115922523152858], [30261, 0.7111924618001526], [30513, 0.7104109796311185], [30527, 0.7115583322695904], [30541, 0.7130106418127605], [30555, 0.7099796103167783], [30569, 0.709288216924268], [30583, 0.7119405080249659], [30597, 0.7095412543084361], [30625, 0.7128614373655292], [30639, 0.710945043754752], [30653, 0.7098590293930527], [30667, 0.7097658940588805], [30681, 0.7123038930525487], [30695, 0.7112964289071013], [30709, 0.7082594579226886], [30723, 0.708864492950664], [30737, 0.7064840553358652], [30751, 0.7116446995008369], [30765, 0.7090850741390994], [30779, 0.7158601102899571], [30793, 0.7112323335085344], [30807, 0.7097821682648325], [30821, 0.7127815789620088], [30835, 0.7105365906210509], [30849, 0.713088126270239], [30863, 0.7126444620375175], [30877, 0.709715869247546], [30891, 0.705474060799359], [30905, 0.708510425600117], [30919, 0.7074110737009761], [30933, 0.7102646301681691], [30947, 0.7106961134003682], [30961, 0.7118041159872946], [30975, 0.7104369315799786], [30989, 0.7114030203417722], [31003, 0.7110632887011488], [31017, 0.705368674536293], [31031, 0.7071327560381201], [31045, 0.7075730667774516], [32095, 0.7056246158104333], [32109, 0.710584280460473], [32123, 0.709903782943401], [32137, 0.7089228822611774], [32151, 0.7076085682332449], [32165, 0.7090502811430252], [32179, 0.7082107496817684], [32193, 0.7135907331189242], [32207, 0.7092606693362141], [32221, 0.7100361028756826], [32235, 0.7099381874077219], [32249, 0.7071136541627123], [32263, 0.7120211562107974], [32277, 0.7111434076290518], [32305, 0.7099136118506584], [32319, 0.7104387571264517], [32333, 0.7099999030389844], [32347, 0.7100814171596272], [32361, 0.7103415612776008], [32375, 0.7123303070158281], [32389, 0.7116456768147933], [32403, 0.7046391308649365], [32417, 0.7103892764367964], [32431, 0.708064074990753], [32445, 0.7155749016946209], [32585, 0.708190310147589], [32599, 0.713904534877277], [32613, 0.7110431074673564], [32627, 0.7111815700680717], [32641, 0.7152453197600039], [32655, 0.7093326585697985], [32851, 0.7093875902869712], [32865, 0.7110082741418622], [32879, 0.7074946421245176], [32893, 0.7086190095306976], [32907, 0.7108284545384066], [32921, 0.7092495249001283], [32991, 0.7114599440032879], [33005, 0.7145512074672161], [33019, 0.7058530084767077], [33033, 0.7079413975115669], [33047, 0.7075235935845045], [33061, 0.7136681450039533], [33075, 0.7129928053196629], [33089, 0.710750133705571], [33103, 0.7093206158991041], [33117, 0.7091328463954876], [33131, 0.7100089698935188], [33145, 0.7110836216372629], [33159, 0.7151649941030345], [33187, 0.7130086280127647], [33201, 0.7085888284650943], [33215, 0.70937378871421], [33229, 0.7111641479728945], [33243, 0.7121050260992746], [33271, 0.7103643162141833], [33299, 0.705611185055584], [33313, 0.7111597622733451], [33327, 0.710866422485037], [33341, 0.7125425374906456], [33355, 0.7103406391770531], [33369, 0.7094882480455365], [33383, 0.7131138306487328], [33397, 0.7103854616136798], [33411, 0.7065718452104044], [33425, 0.7133031510674128], [33439, 0.7073642032767745], [33453, 0.7121883704041998], [33467, 0.7121726036638236], [33523, 0.7104914721270839], [33537, 0.7103431310671473], [33551, 0.7108725463220531], [33649, 0.7129922560286037], [33705, 0.709454017708782], [33719, 0.7109622664453225], [33733, 0.710667590902187], [33747, 0.7126422024276997], [33761, 0.7090921880179738], [33775, 0.7130789250253504], [33803, 0.7040964922971961], [33817, 0.7125730678210005], [33831, 0.7085105651423439], [33845, 0.7107166899802091], [34041, 0.7098459173756511], [34055, 0.7096548895936378], [34069, 0.7104456587396241], [34083, 0.7118186328567644], [34125, 0.7123113289394434], [34139, 0.7123840665312661], [34153, 0.7087330207196009], [34167, 0.7101928637286663]] \ No newline at end of file diff --git a/graphs/summary/svm.SVCBenchmark.peakmem_fit.json b/graphs/summary/svm.SVCBenchmark.peakmem_fit.json index 49361733e4..7b19c1a2e3 100644 --- a/graphs/summary/svm.SVCBenchmark.peakmem_fit.json +++ b/graphs/summary/svm.SVCBenchmark.peakmem_fit.json @@ -1 +1 @@ -[[28511, 269414399.9221588], [29225, 266806271.99410483], [29239, 266723532.79017133], [29253, 266884095.98232004], [29267, 267079167.98920366], [29281, 267007999.97643748], [29295, 266973866.65488267], [29309, 266892287.98036426], [29323, 266929919.9896875], [29337, 267016191.97512808], [29351, 266527743.9770509], [29365, 266443775.96261296], [29379, 266606079.96558094], [29393, 266636287.9744451], [29407, 266459647.9970484], [29421, 266539519.9793474], [29435, 266939733.3150034], [29449, 267047594.63918182], [29463, 266955980.77014047], [29477, 266923007.9941074], [29547, 267031551.99410993], [29561, 267175594.61499545], [29575, 266499071.93114346], [29603, 267771903.97846234], [29617, 267756543.98825365], [29631, 268141567.9628502], [29645, 267952127.9784891], [29659, 267842041.96652088], [29673, 267809791.96410993], [29743, 267807231.96574113], [29757, 267877375.9627976], [29771, 267791155.16631955], [29785, 267910655.97749466], [29799, 267923660.74012288], [29813, 268045055.98288518], [29827, 268147711.9413439], [29841, 267969535.94914114], [29855, 268001279.98434967], [29869, 268220415.9785006], [30009, 268026367.97750434], [30023, 267881471.94128582], [30037, 268116991.97457996], [30051, 268137471.94720715], [30065, 268213247.9628596], [30079, 268178285.64110714], [30093, 268129279.9784912], [30107, 267985578.61579975], [30121, 268217343.93676743], [30135, 268189183.9423307], [30149, 268339711.94626817], [30163, 268467541.31510615], [30177, 268455423.9697307], [30191, 268641791.97853214], [30205, 268606805.3255275], [30219, 268510207.983992], [30233, 268445183.9736427], [30247, 268657919.95363903], [30261, 268551417.7988934], [30513, 268713164.5626], [30527, 268677119.92428076], [30541, 268465151.9459601], [30555, 268434261.2731197], [30569, 268401406.4990343], [30583, 268503039.9375343], [30597, 268523519.9609405], [30625, 268575743.9876384], [30639, 268628991.9628999], [30653, 268539391.95801806], [30667, 268388351.97656843], [30681, 268671658.66666657], [30695, 268577791.96291006], [30709, 268711935.9687699], [30723, 268624895.99414474], [30737, 268664575.9741387], [30751, 268733951.95901525], [30765, 268996949.2923992], [30779, 268693503.96878], [30793, 268678485.26046115], [30807, 268566015.19668317], [30821, 268795391.88391596], [30835, 269119487.99999994], [30849, 268784639.9473342], [30863, 268727807.96975726], [30877, 268813311.9414854], [30891, 268691455.96097463], [30905, 268683263.91414094], [30919, 268585972.70937485], [30933, 268667903.94728506], [30947, 268825087.9853782], [30961, 268749141.301466], [30975, 268795389.3485864], [30989, 268862805.3021434], [31003, 268860927.9463743], [31017, 269021183.98440903], [31031, 268751871.99414754], [31045, 268820735.9800087], [32095, 280918015.90295047], [32109, 280400895.9738364], [32123, 280485119.9761587], [32137, 280444927.9713373], [32151, 280311295.978485], [32165, 280423167.96586275], [32179, 280095743.97941005], [32193, 280484515.69150335], [32207, 281851647.95110714], [32221, 283931989.3136442], [32235, 283798527.92056084], [32249, 283990015.9040003], [32263, 283789107.0784126], [32277, 283037354.6129531], [32305, 284360362.6463895], [32319, 287035050.6453511], [32333, 286860287.99451697], [32347, 287129087.98082924], [32361, 287190271.97763115], [32375, 287042559.9506847], [32389, 287086079.97534764], [32403, 286869503.97806835], [32417, 286889301.3126217], [32431, 287064063.97808325], [32445, 287234047.963494], [32585, 287243605.3175134], [32599, 287422463.9939197], [32613, 287251797.30290747], [32627, 287237119.9945242], [32641, 287182335.997259], [32655, 287359658.64597684], [32851, 288045738.6472568], [32865, 288034042.74140835], [32879, 288070314.6436177], [32893, 288139263.9927218], [32907, 288041983.9787721], [32921, 288012287.99999994], [32991, 287911935.97086406], [33005, 288043007.92719316], [33019, 287633408.0000001], [33033, 288060415.99453986], [33047, 288137216.00000006], [33061, 288290303.9899974], [33075, 288178175.9999999], [33089, 303470079.9874025], [33103, 318810111.6644774], [33117, 319033340.97733283], [33131, 318785023.96792775], [33145, 319170559.98028797], [33159, 319227903.9802914], [33187, 288290815.9927256], [33201, 288330239.96090794], [33215, 287353280.5550952], [33229, 284475503.87413526], [33243, 284466315.5296044], [33271, 280593407.91965586], [33299, 280443903.9943914], [33313, 280820222.05810106], [33327, 281248255.92260516], [33341, 281358843.2523166], [33355, 281584981.08508587], [33369, 281624234.5654407], [33383, 282295637.1115808], [33397, 282629119.94991434], [33411, 282681343.9999999], [33425, 282745855.9443697], [33439, 283803135.66101515], [33453, 279076864.0000001], [33467, 278931436.9759808], [33523, 279000319.64346594], [33537, 279085395.8796301], [33551, 278444362.13568777], [33649, 277748735.9641347], [33705, 277170175.81084263], [33719, 277540863.8706232], [33733, 277466111.97921497], [33747, 277554686.9927976], [33761, 277642195.79163855], [33775, 277554175.8734381], [33803, 277514208.9145477], [33817, 277352959.9102086], [33831, 277337770.52360475], [33845, 277399525.9181351], [34041, 276930559.92427915], [34055, 277147644.77572584], [34069, 276998485.23296386], [34083, 276775935.86551523], [34125, 276855466.5063224], [34139, 276881407.8485163], [34153, 276910762.54172176], [34167, 276849407.89065176]] \ No newline at end of file +[[28511, 269414399.9221588], [29225, 266806271.99410483], [29239, 266723532.79017133], [29253, 266884095.98232004], [29267, 267079167.98920366], [29281, 267007999.97643748], [29295, 266973866.65488267], [29309, 266892287.98036426], [29323, 266929919.9896875], [29337, 267016191.97512808], [29351, 266527743.9770509], [29365, 266443775.96261296], [29379, 266606079.96558094], [29393, 266636287.9744451], [29407, 266459647.9970484], [29421, 266539519.9793474], [29435, 266939733.3150034], [29449, 267047594.63918182], [29463, 266955980.77014047], [29477, 266923007.9941074], [29547, 267031551.99410993], [29561, 267175594.61499545], [29575, 266499071.93114346], [29603, 267771903.97846234], [29617, 267756543.98825365], [29631, 268141567.9628502], [29645, 267952127.9784891], [29659, 267842041.96652088], [29673, 267809791.96410993], [29743, 267807231.96574113], [29757, 267877375.9627976], [29771, 267791155.16631955], [29785, 267910655.97749466], [29799, 267923660.74012288], [29813, 268045055.98288518], [29827, 268147711.9413439], [29841, 267969535.94914114], [29855, 268001279.98434967], [29869, 268220415.9785006], [30009, 268026367.97750434], [30023, 267881471.94128582], [30037, 268116991.97457996], [30051, 268137471.94720715], [30065, 268213247.9628596], [30079, 268178285.64110714], [30093, 268129279.9784912], [30107, 267985578.61579975], [30121, 268217343.93676743], [30135, 268189183.9423307], [30149, 268339711.94626817], [30163, 268467541.31510615], [30177, 268455423.9697307], [30191, 268641791.97853214], [30205, 268606805.3255275], [30219, 268510207.983992], [30233, 268445183.9736427], [30247, 268657919.95363903], [30261, 268551417.7988934], [30513, 268713164.5626], [30527, 268677119.92428076], [30541, 268465151.9459601], [30555, 268434261.2731197], [30569, 268401406.4990343], [30583, 268503039.9375343], [30597, 268523519.9609405], [30625, 268575743.9876384], [30639, 268628991.9628999], [30653, 268539391.95801806], [30667, 268388351.97656843], [30681, 268671658.66666657], [30695, 268577791.96291006], [30709, 268711935.9687699], [30723, 268624895.99414474], [30737, 268664575.9741387], [30751, 268733951.95901525], [30765, 268996949.2923992], [30779, 268693503.96878], [30793, 268678485.26046115], [30807, 268566015.19668317], [30821, 268795391.88391596], [30835, 269119487.99999994], [30849, 268784639.9473342], [30863, 268727807.96975726], [30877, 268813311.9414854], [30891, 268691455.96097463], [30905, 268683263.91414094], [30919, 268585972.70937485], [30933, 268667903.94728506], [30947, 268825087.9853782], [30961, 268749141.301466], [30975, 268795389.3485864], [30989, 268862805.3021434], [31003, 268860927.9463743], [31017, 269021183.98440903], [31031, 268751871.99414754], [31045, 268820735.9800087], [32095, 280918015.90295047], [32109, 280400895.9738364], [32123, 280485119.9761587], [32137, 280444927.9713373], [32151, 280311295.978485], [32165, 280423167.96586275], [32179, 280095743.97941005], [32193, 280484515.69150335], [32207, 281851647.95110714], [32221, 283931989.3136442], [32235, 283798527.92056084], [32249, 283990015.9040003], [32263, 283789107.0784126], [32277, 283037354.6129531], [32305, 284360362.6463895], [32319, 287035050.6453511], [32333, 286860287.99451697], [32347, 287129087.98082924], [32361, 287190271.97763115], [32375, 287042559.9506847], [32389, 287086079.97534764], [32403, 286869503.97806835], [32417, 286889301.3126217], [32431, 287064063.97808325], [32445, 287234047.963494], [32585, 287243605.3175134], [32599, 287422463.9939197], [32613, 287251797.30290747], [32627, 287237119.9945242], [32641, 287182335.997259], [32655, 287359658.64597684], [32851, 288045738.6472568], [32865, 288034042.74140835], [32879, 288070314.6436177], [32893, 288139263.9927218], [32907, 288041983.9787721], [32921, 288012287.99999994], [32991, 287911935.97086406], [33005, 288043007.92719316], [33019, 287633408.0000001], [33033, 288060415.99453986], [33047, 288137216.00000006], [33061, 288290303.9899974], [33075, 288178175.9999999], [33089, 303470079.9874025], [33103, 318810111.6644774], [33117, 319033340.97733283], [33131, 318785023.96792775], [33145, 319170559.98028797], [33159, 319227903.9802914], [33187, 288290815.9927256], [33201, 288330239.96090794], [33215, 287353280.5550952], [33229, 284475503.87413526], [33243, 284466315.5296044], [33271, 280593407.91965586], [33299, 280443903.9943914], [33313, 280820222.05810106], [33327, 281248255.92260516], [33341, 281358843.2523166], [33355, 281584981.08508587], [33369, 281624234.5654407], [33383, 282295637.1115808], [33397, 282629119.94991434], [33411, 282681343.9999999], [33425, 282745855.9443697], [33439, 283803135.66101515], [33453, 279076864.0000001], [33467, 278931436.9759808], [33523, 279000319.64346594], [33537, 279085395.8796301], [33551, 278444362.13568777], [33649, 277748735.9641347], [33705, 277170175.81084263], [33719, 277540863.8706232], [33733, 277466111.97921497], [33747, 277554686.9927976], [33761, 277642195.79163855], [33775, 277554175.8734381], [33803, 277514208.9145477], [33817, 277352959.9102086], [33831, 277337770.52360475], [33845, 277399525.9181351], [34041, 276930559.92427915], [34055, 277147644.77572584], [34069, 276998485.23296386], [34083, 276775935.86551523], [34125, 276855466.5063224], [34139, 276881407.8485163], [34153, 276910762.54172176], [34167, 276823449.4503762]] \ No newline at end of file diff --git a/graphs/summary/svm.SVCBenchmark.peakmem_predict.json b/graphs/summary/svm.SVCBenchmark.peakmem_predict.json index ce46907252..db794e8014 100644 --- a/graphs/summary/svm.SVCBenchmark.peakmem_predict.json +++ b/graphs/summary/svm.SVCBenchmark.peakmem_predict.json @@ -1 +1 @@ -[[28511, 204280856.84670866], [29225, 201773056.0], [29239, 201326591.99999994], [29253, 201648810.66666666], [29267, 201490431.98959178], [29281, 201926655.9896143], [29295, 201627989.32379946], [29309, 201686527.9961036], [29323, 201726638.35182932], [29337, 201690453.32986796], [29351, 200854186.66666672], [29365, 200808446.15168345], [29379, 201383934.99981004], [29393, 201243306.66666666], [29407, 201250815.99999997], [29421, 201044992.0], [29435, 201487701.33333334], [29449, 201576448.0], [29463, 201381478.4], [29477, 201416703.99999994], [29547, 201867264.0], [29561, 201865898.66666663], [29575, 201195519.99999994], [29603, 202047487.99999997], [29617, 202252288.0], [29631, 202457087.99999997], [29645, 202473472.0], [29659, 202479616.0], [29673, 202391552.0], [29743, 202274816.0], [29757, 202459136.0], [29771, 202459545.6], [29785, 202428415.99999997], [29799, 202384998.4], [29813, 202577663.56363416], [29827, 202807295.99999994], [29841, 202571775.99999997], [29855, 202506240.0], [29869, 202889215.99999997], [30009, 202512384.0], [30023, 202493952.0], [30037, 202418517.33074284], [30051, 202395648.0], [30065, 202288127.99222463], [30079, 202476982.85714287], [30093, 202364928.00000006], [30107, 202357418.66666666], [30121, 202579968.0], [30135, 202444800.0], [30149, 202790912.00000003], [30163, 202794324.67150506], [30177, 202969088.00000003], [30191, 202961920.0], [30205, 202966357.33333334], [30219, 202887987.2], [30233, 202598399.99999994], [30247, 203006976.0], [30261, 202801152.0], [30513, 203194368.00000003], [30527, 202978918.4], [30541, 202878634.6640805], [30555, 202742442.3352505], [30569, 202841599.99741256], [30583, 203110400.0], [30597, 202604544.0], [30625, 202995711.99655327], [30639, 203057151.99999997], [30653, 202828458.66666666], [30667, 202926080.00000003], [30681, 202988202.66666672], [30695, 203096064.0], [30709, 202868735.99999997], [30723, 202686464.0], [30737, 203025408.0], [30751, 203118591.99999997], [30765, 203358207.99999997], [30779, 202846207.99999997], [30793, 203074218.66666666], [30807, 203053056.0], [30821, 203194368.0], [30835, 203599872.0], [30849, 203005952.00000003], [30863, 203087872.0], [30877, 203069440.0], [30891, 203247616.00000003], [30905, 203259904.0], [30919, 203087872.0], [30933, 203083776.0], [30947, 202987520.0], [30961, 203102890.66666666], [30975, 203196416.0], [30989, 203123370.66666666], [31003, 203352064.0], [31017, 203186175.99999997], [31031, 203018240.0], [31045, 203039743.99999997], [32095, 214925312.0], [32109, 214562815.99999994], [32123, 214574080.0], [32137, 214439253.33333328], [32151, 214550528.0], [32165, 214567936.0], [32179, 214452223.9902209], [32193, 214758741.33333334], [32207, 215981056.0], [32221, 217930410.66666666], [32235, 218443775.99999997], [32249, 218288127.99999997], [32263, 217958809.6], [32277, 217250474.66666666], [32305, 218667690.66666666], [32319, 221317802.66666666], [32333, 221433856.00000003], [32347, 221266944.0], [32361, 221305856.00000003], [32375, 221212672.00000003], [32389, 221138944.0], [32403, 221040640.0], [32417, 221347840.0], [32431, 221478911.99999994], [32445, 221687808.0], [32585, 221554005.33333334], [32599, 221640021.33333334], [32613, 221626368.0], [32627, 221712384.00000003], [32641, 221693952.0], [32655, 221549908.7269938], [32851, 222126080.0], [32865, 222216192.0], [32879, 222345898.66666666], [32893, 222351359.99999997], [32907, 222340437.33333334], [32921, 222271488.0], [32991, 222400512.0], [33005, 222228480.0], [33019, 222015487.99999997], [33033, 222230528.0], [33047, 222441471.99999997], [33061, 222613504.0], [33075, 222400512.0], [33089, 236883743.38918447], [33103, 251231310.487005], [33117, 251495704.2435841], [33131, 251222789.38452837], [33145, 251045347.32104102], [33159, 251219509.99103463], [33187, 222785536.0], [33201, 222697472.00000006], [33215, 220648930.64061624], [33229, 215040564.6507629], [33243, 215064072.5805254], [33271, 207740928.0], [33299, 207480358.97949752], [33313, 207999995.3608716], [33327, 208648684.1361], [33341, 208570260.33461982], [33355, 208781311.1419743], [33369, 209161200.01057062], [33383, 209337002.02634564], [33397, 209575936.00000006], [33411, 209919998.0820728], [33425, 209800186.18854654], [33439, 210855420.40102875], [33453, 206333938.225512], [33467, 206288657.1299246], [33523, 206350015.37113684], [33537, 206248845.09680247], [33551, 205601449.73734558], [33649, 204615680.00000003], [33705, 204681213.37703863], [33719, 204491511.29928288], [33733, 204541950.03122932], [33747, 204658684.40058523], [33761, 204484607.99999997], [33775, 204275712.00000003], [33803, 204587008.0], [33817, 204755241.05037913], [33831, 204407807.99743888], [33845, 204193792.00000003], [34041, 204316667.8807302], [34055, 204226353.34160927], [34069, 204315300.54436776], [34083, 203947803.0532711], [34125, 204115624.80558762], [34139, 204017664.00000003], [34153, 204025856.0], [34167, 204201972.86724728]] \ No newline at end of file +[[28511, 204280856.84670866], [29225, 201773056.0], [29239, 201326591.99999994], [29253, 201648810.66666666], [29267, 201490431.98959178], [29281, 201926655.9896143], [29295, 201627989.32379946], [29309, 201686527.9961036], [29323, 201726638.35182932], [29337, 201690453.32986796], [29351, 200854186.66666672], [29365, 200808446.15168345], [29379, 201383934.99981004], [29393, 201243306.66666666], [29407, 201250815.99999997], [29421, 201044992.0], [29435, 201487701.33333334], [29449, 201576448.0], [29463, 201381478.4], [29477, 201416703.99999994], [29547, 201867264.0], [29561, 201865898.66666663], [29575, 201195519.99999994], [29603, 202047487.99999997], [29617, 202252288.0], [29631, 202457087.99999997], [29645, 202473472.0], [29659, 202479616.0], [29673, 202391552.0], [29743, 202274816.0], [29757, 202459136.0], [29771, 202459545.6], [29785, 202428415.99999997], [29799, 202384998.4], [29813, 202577663.56363416], [29827, 202807295.99999994], [29841, 202571775.99999997], [29855, 202506240.0], [29869, 202889215.99999997], [30009, 202512384.0], [30023, 202493952.0], [30037, 202418517.33074284], [30051, 202395648.0], [30065, 202288127.99222463], [30079, 202476982.85714287], [30093, 202364928.00000006], [30107, 202357418.66666666], [30121, 202579968.0], [30135, 202444800.0], [30149, 202790912.00000003], [30163, 202794324.67150506], [30177, 202969088.00000003], [30191, 202961920.0], [30205, 202966357.33333334], [30219, 202887987.2], [30233, 202598399.99999994], [30247, 203006976.0], [30261, 202801152.0], [30513, 203194368.00000003], [30527, 202978918.4], [30541, 202878634.6640805], [30555, 202742442.3352505], [30569, 202841599.99741256], [30583, 203110400.0], [30597, 202604544.0], [30625, 202995711.99655327], [30639, 203057151.99999997], [30653, 202828458.66666666], [30667, 202926080.00000003], [30681, 202988202.66666672], [30695, 203096064.0], [30709, 202868735.99999997], [30723, 202686464.0], [30737, 203025408.0], [30751, 203118591.99999997], [30765, 203358207.99999997], [30779, 202846207.99999997], [30793, 203074218.66666666], [30807, 203053056.0], [30821, 203194368.0], [30835, 203599872.0], [30849, 203005952.00000003], [30863, 203087872.0], [30877, 203069440.0], [30891, 203247616.00000003], [30905, 203259904.0], [30919, 203087872.0], [30933, 203083776.0], [30947, 202987520.0], [30961, 203102890.66666666], [30975, 203196416.0], [30989, 203123370.66666666], [31003, 203352064.0], [31017, 203186175.99999997], [31031, 203018240.0], [31045, 203039743.99999997], [32095, 214925312.0], [32109, 214562815.99999994], [32123, 214574080.0], [32137, 214439253.33333328], [32151, 214550528.0], [32165, 214567936.0], [32179, 214452223.9902209], [32193, 214758741.33333334], [32207, 215981056.0], [32221, 217930410.66666666], [32235, 218443775.99999997], [32249, 218288127.99999997], [32263, 217958809.6], [32277, 217250474.66666666], [32305, 218667690.66666666], [32319, 221317802.66666666], [32333, 221433856.00000003], [32347, 221266944.0], [32361, 221305856.00000003], [32375, 221212672.00000003], [32389, 221138944.0], [32403, 221040640.0], [32417, 221347840.0], [32431, 221478911.99999994], [32445, 221687808.0], [32585, 221554005.33333334], [32599, 221640021.33333334], [32613, 221626368.0], [32627, 221712384.00000003], [32641, 221693952.0], [32655, 221549908.7269938], [32851, 222126080.0], [32865, 222216192.0], [32879, 222345898.66666666], [32893, 222351359.99999997], [32907, 222340437.33333334], [32921, 222271488.0], [32991, 222400512.0], [33005, 222228480.0], [33019, 222015487.99999997], [33033, 222230528.0], [33047, 222441471.99999997], [33061, 222613504.0], [33075, 222400512.0], [33089, 236883743.38918447], [33103, 251231310.487005], [33117, 251495704.2435841], [33131, 251222789.38452837], [33145, 251045347.32104102], [33159, 251219509.99103463], [33187, 222785536.0], [33201, 222697472.00000006], [33215, 220648930.64061624], [33229, 215040564.6507629], [33243, 215064072.5805254], [33271, 207740928.0], [33299, 207480358.97949752], [33313, 207999995.3608716], [33327, 208648684.1361], [33341, 208570260.33461982], [33355, 208781311.1419743], [33369, 209161200.01057062], [33383, 209337002.02634564], [33397, 209575936.00000006], [33411, 209919998.0820728], [33425, 209800186.18854654], [33439, 210855420.40102875], [33453, 206333938.225512], [33467, 206288657.1299246], [33523, 206350015.37113684], [33537, 206248845.09680247], [33551, 205601449.73734558], [33649, 204615680.00000003], [33705, 204681213.37703863], [33719, 204491511.29928288], [33733, 204541950.03122932], [33747, 204658684.40058523], [33761, 204484607.99999997], [33775, 204275712.00000003], [33803, 204587008.0], [33817, 204755241.05037913], [33831, 204407807.99743888], [33845, 204193792.00000003], [34041, 204316667.8807302], [34055, 204226353.34160927], [34069, 204315300.54436776], [34083, 203947803.0532711], [34125, 204115624.80558762], [34139, 204017664.00000003], [34153, 204025856.0], [34167, 204202588.01370803]] \ No newline at end of file diff --git a/graphs/summary/svm.SVCBenchmark.time_fit.json b/graphs/summary/svm.SVCBenchmark.time_fit.json index 0e50f3fafe..93beb38c40 100644 --- a/graphs/summary/svm.SVCBenchmark.time_fit.json +++ b/graphs/summary/svm.SVCBenchmark.time_fit.json @@ -1 +1 @@ -[[28511, 0.839487988334965], [29225, 0.9368647044385782], [29239, 0.9687928561351494], [29253, 0.8816301405441923], [29267, 0.8463491592754073], [29281, 0.8018887739853046], [29295, 0.9503587504031987], [29309, 0.9906887448370563], [29323, 0.9401676913316516], [29337, 0.8866873449033736], [29351, 0.9228054673436213], [29365, 0.8868873629787715], [29379, 0.9298473692518295], [29393, 0.8722936168932671], [29407, 0.9568825396174767], [29421, 0.9000877184790559], [29435, 0.9110947026564219], [29449, 0.9250062171789836], [29463, 0.9258958720181605], [29477, 0.9124312253633822], [29547, 0.9675501557520737], [29561, 0.82463762301518], [29575, 0.6726174914018764], [29603, 0.6801788381633096], [29617, 0.6690559544309205], [29631, 0.6737171963719846], [29645, 0.6696126757451227], [29659, 0.669082517842483], [29673, 0.6758935148842639], [29743, 0.6665952555182071], [29757, 0.6855140408626175], [29771, 0.6764947269436715], [29785, 0.9036637836694774], [29799, 0.9471073015887044], [29813, 0.9540145632162005], [29827, 0.9451787790073591], [29841, 0.9507356059746804], [29855, 0.953721079022776], [29869, 0.9242938638614198], [30009, 0.9326247373360713], [30023, 0.9644283172796277], [30037, 0.95715918616283], [30051, 0.9471298792322639], [30065, 0.9366851103070825], [30079, 0.953399342043418], [30093, 0.9559970338898185], [30107, 0.9344185171367462], [30121, 0.9450958529122918], [30135, 0.9764371307243929], [30149, 0.9456118875633053], [30163, 0.9694743503042091], [30177, 0.9360759367076374], [30191, 0.9608524794670342], [30205, 0.9485351726978858], [30219, 0.9581510434665376], [30233, 0.9645306389425208], [30247, 0.9554917255806802], [30261, 0.9673789905935289], [30513, 0.962382107369099], [30527, 0.944520510123118], [30541, 0.927273304149892], [30555, 0.9571820768080657], [30569, 0.9568348441850043], [30583, 0.9549946316531867], [30597, 0.9493282953758021], [30625, 0.9356028858992733], [30639, 0.9704406668537534], [30653, 0.964635960210515], [30667, 0.9383737343907037], [30681, 0.9546258127882812], [30695, 0.9365635127273849], [30709, 0.943026582076163], [30723, 0.9850082120295631], [30737, 0.9521444516370048], [30751, 0.9459922770008915], [30765, 0.9629996030292257], [30779, 0.9407584224327933], [30793, 0.9437995665995492], [30807, 0.9319911306926806], [30821, 0.9181839168154329], [30835, 1.0092854331033676], [30849, 0.921137704651591], [30863, 0.9629256518461184], [30877, 0.9413699371274333], [30891, 0.9699743910096994], [30905, 0.9486269188756611], [30919, 0.9545588178790148], [30933, 0.9583605559358006], [30947, 0.9543131266393774], [30961, 0.9453268838289152], [30975, 0.9364491305006124], [30989, 0.9507660431162508], [31003, 0.9668091603768241], [31017, 0.9428739009076733], [31031, 0.9236333306740581], [31045, 0.9618655802864332], [32095, 0.8934357138394537], [32109, 0.8760646069936555], [32123, 0.911434408793917], [32137, 0.9039047820724558], [32151, 0.9103362399601731], [32165, 0.8991551263148968], [32179, 0.8810999956456746], [32193, 0.9193407903897112], [32207, 0.8878942275836387], [32221, 0.8875572242294963], [32235, 0.8868722930978311], [32249, 0.903383593574899], [32263, 0.9426213807285793], [32277, 0.9532184102687496], [32305, 0.9657789050458039], [32319, 0.9516188640532537], [32333, 0.9353954802345851], [32347, 0.9561051483854702], [32361, 0.9541376167478816], [32375, 0.9639994275217684], [32389, 0.9634192567573301], [32403, 0.9540699340462764], [32417, 0.9482136282372192], [32431, 0.9533059398489963], [32445, 0.9299717448025807], [32585, 0.8357767565258764], [32599, 0.7612630096549049], [32613, 0.7813549058845286], [32627, 0.8210589792053424], [32641, 0.8469633707513782], [32655, 0.7342035846954578], [32851, 0.8852515020182551], [32865, 0.8805662238429097], [32879, 0.875946561369739], [32893, 0.909275863945655], [32907, 0.9118869271321403], [32921, 0.886799078756675], [32991, 0.8880754934732165], [33005, 0.8831640791027281], [33019, 0.8843587656865438], [33033, 0.8865641173746117], [33047, 0.8476747785762262], [33061, 0.8726003720993412], [33075, 0.9080003512220444], [33089, 0.8832639222142085], [33103, 0.9249274460499585], [33117, 0.8929503411597903], [33131, 0.8811234945541913], [33145, 0.898620220840604], [33159, 0.8477276202893256], [33187, 0.84122845798231], [33201, 0.9124455809533769], [33215, 0.9431205895875063], [33229, 1.1813690934994865], [33243, 1.1927659135729338], [33271, 1.6614127887787957], [33299, 1.742588430540128], [33313, 1.5687849452367044], [33327, 1.6537761910006563], [33341, 1.6706320445135134], [33355, 1.6100482912310967], [33369, 1.5679753551203615], [33383, 1.5743237894902364], [33397, 1.5977583951516532], [33411, 1.6454528853519819], [33425, 1.6459396472101746], [33439, 1.5962990186234363], [33453, 1.6767101263210062], [33467, 1.6587382535793571], [33523, 1.5928363563797954], [33537, 1.6438494611102816], [33551, 1.6196212439612332], [33649, 1.5364910968296277], [33705, 1.5120516507608377], [33719, 1.6043723094701063], [33733, 1.6291275057213552], [33747, 1.6496462846545965], [33761, 1.61995895968484], [33775, 1.6701067011864499], [33803, 1.7647407213681436], [33817, 1.7353496628309324], [33831, 1.7418333719952193], [33845, 1.7200494417473697], [34041, 1.7190105870582766], [34055, 1.6648386447075059], [34069, 1.6515039574095576], [34083, 1.65150754329287], [34125, 1.7086492906305129], [34139, 1.713692775087667], [34153, 1.7451106231808915], [34167, 1.7155768916482506]] \ No newline at end of file +[[28511, 0.839487988334965], [29225, 0.9368647044385782], [29239, 0.9687928561351494], [29253, 0.8816301405441923], [29267, 0.8463491592754073], [29281, 0.8018887739853046], [29295, 0.9503587504031987], [29309, 0.9906887448370563], [29323, 0.9401676913316516], [29337, 0.8866873449033736], [29351, 0.9228054673436213], [29365, 0.8868873629787715], [29379, 0.9298473692518295], [29393, 0.8722936168932671], [29407, 0.9568825396174767], [29421, 0.9000877184790559], [29435, 0.9110947026564219], [29449, 0.9250062171789836], [29463, 0.9258958720181605], [29477, 0.9124312253633822], [29547, 0.9675501557520737], [29561, 0.82463762301518], [29575, 0.6726174914018764], [29603, 0.6801788381633096], [29617, 0.6690559544309205], [29631, 0.6737171963719846], [29645, 0.6696126757451227], [29659, 0.669082517842483], [29673, 0.6758935148842639], [29743, 0.6665952555182071], [29757, 0.6855140408626175], [29771, 0.6764947269436715], [29785, 0.9036637836694774], [29799, 0.9471073015887044], [29813, 0.9540145632162005], [29827, 0.9451787790073591], [29841, 0.9507356059746804], [29855, 0.953721079022776], [29869, 0.9242938638614198], [30009, 0.9326247373360713], [30023, 0.9644283172796277], [30037, 0.95715918616283], [30051, 0.9471298792322639], [30065, 0.9366851103070825], [30079, 0.953399342043418], [30093, 0.9559970338898185], [30107, 0.9344185171367462], [30121, 0.9450958529122918], [30135, 0.9764371307243929], [30149, 0.9456118875633053], [30163, 0.9694743503042091], [30177, 0.9360759367076374], [30191, 0.9608524794670342], [30205, 0.9485351726978858], [30219, 0.9581510434665376], [30233, 0.9645306389425208], [30247, 0.9554917255806802], [30261, 0.9673789905935289], [30513, 0.962382107369099], [30527, 0.944520510123118], [30541, 0.927273304149892], [30555, 0.9571820768080657], [30569, 0.9568348441850043], [30583, 0.9549946316531867], [30597, 0.9493282953758021], [30625, 0.9356028858992733], [30639, 0.9704406668537534], [30653, 0.964635960210515], [30667, 0.9383737343907037], [30681, 0.9546258127882812], [30695, 0.9365635127273849], [30709, 0.943026582076163], [30723, 0.9850082120295631], [30737, 0.9521444516370048], [30751, 0.9459922770008915], [30765, 0.9629996030292257], [30779, 0.9407584224327933], [30793, 0.9437995665995492], [30807, 0.9319911306926806], [30821, 0.9181839168154329], [30835, 1.0092854331033676], [30849, 0.921137704651591], [30863, 0.9629256518461184], [30877, 0.9413699371274333], [30891, 0.9699743910096994], [30905, 0.9486269188756611], [30919, 0.9545588178790148], [30933, 0.9583605559358006], [30947, 0.9543131266393774], [30961, 0.9453268838289152], [30975, 0.9364491305006124], [30989, 0.9507660431162508], [31003, 0.9668091603768241], [31017, 0.9428739009076733], [31031, 0.9236333306740581], [31045, 0.9618655802864332], [32095, 0.8934357138394537], [32109, 0.8760646069936555], [32123, 0.911434408793917], [32137, 0.9039047820724558], [32151, 0.9103362399601731], [32165, 0.8991551263148968], [32179, 0.8810999956456746], [32193, 0.9193407903897112], [32207, 0.8878942275836387], [32221, 0.8875572242294963], [32235, 0.8868722930978311], [32249, 0.903383593574899], [32263, 0.9426213807285793], [32277, 0.9532184102687496], [32305, 0.9657789050458039], [32319, 0.9516188640532537], [32333, 0.9353954802345851], [32347, 0.9561051483854702], [32361, 0.9541376167478816], [32375, 0.9639994275217684], [32389, 0.9634192567573301], [32403, 0.9540699340462764], [32417, 0.9482136282372192], [32431, 0.9533059398489963], [32445, 0.9299717448025807], [32585, 0.8357767565258764], [32599, 0.7612630096549049], [32613, 0.7813549058845286], [32627, 0.8210589792053424], [32641, 0.8469633707513782], [32655, 0.7342035846954578], [32851, 0.8852515020182551], [32865, 0.8805662238429097], [32879, 0.875946561369739], [32893, 0.909275863945655], [32907, 0.9118869271321403], [32921, 0.886799078756675], [32991, 0.8880754934732165], [33005, 0.8831640791027281], [33019, 0.8843587656865438], [33033, 0.8865641173746117], [33047, 0.8476747785762262], [33061, 0.8726003720993412], [33075, 0.9080003512220444], [33089, 0.8832639222142085], [33103, 0.9249274460499585], [33117, 0.8929503411597903], [33131, 0.8811234945541913], [33145, 0.898620220840604], [33159, 0.8477276202893256], [33187, 0.84122845798231], [33201, 0.9124455809533769], [33215, 0.9431205895875063], [33229, 1.1813690934994865], [33243, 1.1927659135729338], [33271, 1.6614127887787957], [33299, 1.742588430540128], [33313, 1.5687849452367044], [33327, 1.6537761910006563], [33341, 1.6706320445135134], [33355, 1.6100482912310967], [33369, 1.5679753551203615], [33383, 1.5743237894902364], [33397, 1.5977583951516532], [33411, 1.6454528853519819], [33425, 1.6459396472101746], [33439, 1.5962990186234363], [33453, 1.6767101263210062], [33467, 1.6587382535793571], [33523, 1.5928363563797954], [33537, 1.6438494611102816], [33551, 1.6196212439612332], [33649, 1.5364910968296277], [33705, 1.5120516507608377], [33719, 1.6043723094701063], [33733, 1.6291275057213552], [33747, 1.6496462846545965], [33761, 1.61995895968484], [33775, 1.6701067011864499], [33803, 1.7647407213681436], [33817, 1.7353496628309324], [33831, 1.7418333719952193], [33845, 1.7200494417473697], [34041, 1.7190105870582766], [34055, 1.6648386447075059], [34069, 1.6515039574095576], [34083, 1.65150754329287], [34125, 1.7086492906305129], [34139, 1.713692775087667], [34153, 1.7451106231808915], [34167, 1.7128880372394168]] \ No newline at end of file diff --git a/graphs/summary/svm.SVCBenchmark.time_predict.json b/graphs/summary/svm.SVCBenchmark.time_predict.json index 9e4914e9fd..52af3b1696 100644 --- a/graphs/summary/svm.SVCBenchmark.time_predict.json +++ b/graphs/summary/svm.SVCBenchmark.time_predict.json @@ -1 +1 @@ -[[28511, 1.0287855497980734], [29225, 1.0827822042895963], [29239, 1.103228949714365], [29253, 1.1606310014860013], [29267, 1.1303567271558288], [29281, 1.1814646067149248], [29295, 1.1271442663176925], [29309, 1.1838673150824375], [29323, 1.1669350732181807], [29337, 1.2032566275561514], [29351, 1.211793163822322], [29365, 1.147307170942883], [29379, 1.2517886839761636], [29393, 1.1947398782737215], [29407, 1.2952321720311961], [29421, 1.160367366270388], [29435, 1.1265450675000046], [29449, 1.0503127937810381], [29463, 1.0465136040355256], [29477, 1.0578357143662804], [29547, 1.1537560205734605], [29561, 0.908589113935042], [29575, 0.7067161114558094], [29603, 0.7001817720696197], [29617, 0.6968468490783168], [29631, 0.6917670634954619], [29645, 0.7014163546652752], [29659, 0.6953339815282062], [29673, 0.7012171337827273], [29743, 0.7008873646461726], [29757, 0.7193502424087888], [29771, 0.6920949981831634], [29785, 1.0538862684015724], [29799, 1.0930634115365556], [29813, 1.0924463455153288], [29827, 1.1083162239778686], [29841, 1.0901055917598867], [29855, 1.0956513927016158], [29869, 1.0787006499632867], [30009, 1.0792481169351675], [30023, 1.0896817743009446], [30037, 1.0898575757864466], [30051, 1.0630615513205293], [30065, 1.070855903432493], [30079, 1.0905793406672257], [30093, 1.1099132126618376], [30107, 1.1059749900997502], [30121, 1.1107485165949724], [30135, 1.1153655081857687], [30149, 1.0894812159875036], [30163, 1.0973799448885622], [30177, 1.0690185529901495], [30191, 1.0946996187569884], [30205, 1.093494653548899], [30219, 1.0900547194401486], [30233, 1.105952865978428], [30247, 1.104562444812923], [30261, 1.1026282041942237], [30513, 1.0983746230060845], [30527, 1.0787234262784562], [30541, 1.102363482696864], [30555, 1.085807233053231], [30569, 1.0856177370104807], [30583, 1.113650461325299], [30597, 1.081567722120389], [30625, 1.0933271065670371], [30639, 1.1061272241454778], [30653, 1.1106832666660902], [30667, 1.0769781457042078], [30681, 1.0825151842273686], [30695, 1.0690860472506147], [30709, 1.0971369661658552], [30723, 1.1283593540587649], [30737, 1.0850367919008785], [30751, 1.0956928061694935], [30765, 1.0863115135985504], [30779, 1.0882033670717266], [30793, 1.0873289831823165], [30807, 1.0741638429671498], [30821, 1.0941511833869861], [30835, 1.0993775960699346], [30849, 1.0803324813632078], [30863, 1.1110369671496936], [30877, 1.0687823219539694], [30891, 1.103985670079679], [30905, 1.0666691395189147], [30919, 1.1036622895328023], [30933, 1.0771423684647643], [30947, 1.0874131429333656], [30961, 1.0692568292873001], [30975, 1.0804968150803327], [30989, 1.077265780678516], [31003, 1.1056042807811923], [31017, 1.0684914834389267], [31031, 1.0457112112025748], [31045, 1.0970004010798151], [32095, 1.0611003906684395], [32109, 1.0882420898792802], [32123, 1.0532152703822346], [32137, 1.0304941919694925], [32151, 1.0853226064994046], [32165, 1.070763650272372], [32179, 1.0637676530289368], [32193, 1.0590861056931613], [32207, 1.0493782714272624], [32221, 1.0786959699693213], [32235, 1.0755306811270344], [32249, 1.0545071851711398], [32263, 1.0817753730483728], [32277, 1.0795222996181846], [32305, 1.0967365680956378], [32319, 1.062658373697927], [32333, 1.0887000482498872], [32347, 1.088014103719228], [32361, 1.1039093534310596], [32375, 1.049710900773731], [32389, 1.104420845363494], [32403, 1.1172988229451788], [32417, 1.0999349308776905], [32431, 1.0819480597730333], [32445, 1.0941984140912726], [32585, 1.0000675492133855], [32599, 0.832954741164038], [32613, 0.917584783785485], [32627, 0.9214409933689555], [32641, 0.8964642854275635], [32655, 0.8109871228629846], [32851, 1.0466829230063703], [32865, 1.0218835045469379], [32879, 1.0380131525741179], [32893, 1.0896853174157952], [32907, 1.0223126932862328], [32921, 1.0212435608872905], [32991, 1.084843023372542], [33005, 1.0155761294971808], [33019, 1.0561225775303582], [33033, 1.0314392237109047], [33047, 1.0566983086681572], [33061, 1.0142143229307965], [33075, 1.0500545974612914], [33089, 1.046958328187126], [33103, 1.070776265310077], [33117, 1.0803450174909384], [33131, 1.0589018784205861], [33145, 1.051333175062018], [33159, 1.036385752005654], [33187, 1.0565235808203421], [33201, 1.0954903804097809], [33215, 1.0109701467642094], [33229, 0.9566506511817555], [33243, 0.9446438486025418], [33271, 0.8641286531203501], [33299, 0.8920926319559489], [33313, 0.8210388594423217], [33327, 0.8202520554781279], [33341, 0.8212628355548541], [33355, 0.866670871916371], [33369, 0.824570336016862], [33383, 0.8091499035739412], [33397, 0.805165175444429], [33411, 0.8096967560352559], [33425, 0.8345910686306266], [33439, 0.827141275175716], [33453, 0.8211403936962307], [33467, 0.8695959047447611], [33523, 0.8236082146149721], [33537, 0.8567893895144509], [33551, 0.8147725293143305], [33649, 0.8501813477009367], [33705, 0.8807524978394472], [33719, 0.8302720008489491], [33733, 0.9633088143644836], [33747, 0.8513644557440347], [33761, 0.8486278514166874], [33775, 0.8071162501467466], [33803, 0.8836940309105143], [33817, 0.8462199304535805], [33831, 0.8628297212784158], [33845, 0.8698323878479655], [34041, 0.8166263562499181], [34055, 0.9082545976634983], [34069, 0.8248783000709983], [34083, 0.8429659944749537], [34125, 0.8247148143161893], [34139, 0.8433280725616271], [34153, 0.8645997613181082], [34167, 0.8522375994034741]] \ No newline at end of file +[[28511, 1.0287855497980734], [29225, 1.0827822042895963], [29239, 1.103228949714365], [29253, 1.1606310014860013], [29267, 1.1303567271558288], [29281, 1.1814646067149248], [29295, 1.1271442663176925], [29309, 1.1838673150824375], [29323, 1.1669350732181807], [29337, 1.2032566275561514], [29351, 1.211793163822322], [29365, 1.147307170942883], [29379, 1.2517886839761636], [29393, 1.1947398782737215], [29407, 1.2952321720311961], [29421, 1.160367366270388], [29435, 1.1265450675000046], [29449, 1.0503127937810381], [29463, 1.0465136040355256], [29477, 1.0578357143662804], [29547, 1.1537560205734605], [29561, 0.908589113935042], [29575, 0.7067161114558094], [29603, 0.7001817720696197], [29617, 0.6968468490783168], [29631, 0.6917670634954619], [29645, 0.7014163546652752], [29659, 0.6953339815282062], [29673, 0.7012171337827273], [29743, 0.7008873646461726], [29757, 0.7193502424087888], [29771, 0.6920949981831634], [29785, 1.0538862684015724], [29799, 1.0930634115365556], [29813, 1.0924463455153288], [29827, 1.1083162239778686], [29841, 1.0901055917598867], [29855, 1.0956513927016158], [29869, 1.0787006499632867], [30009, 1.0792481169351675], [30023, 1.0896817743009446], [30037, 1.0898575757864466], [30051, 1.0630615513205293], [30065, 1.070855903432493], [30079, 1.0905793406672257], [30093, 1.1099132126618376], [30107, 1.1059749900997502], [30121, 1.1107485165949724], [30135, 1.1153655081857687], [30149, 1.0894812159875036], [30163, 1.0973799448885622], [30177, 1.0690185529901495], [30191, 1.0946996187569884], [30205, 1.093494653548899], [30219, 1.0900547194401486], [30233, 1.105952865978428], [30247, 1.104562444812923], [30261, 1.1026282041942237], [30513, 1.0983746230060845], [30527, 1.0787234262784562], [30541, 1.102363482696864], [30555, 1.085807233053231], [30569, 1.0856177370104807], [30583, 1.113650461325299], [30597, 1.081567722120389], [30625, 1.0933271065670371], [30639, 1.1061272241454778], [30653, 1.1106832666660902], [30667, 1.0769781457042078], [30681, 1.0825151842273686], [30695, 1.0690860472506147], [30709, 1.0971369661658552], [30723, 1.1283593540587649], [30737, 1.0850367919008785], [30751, 1.0956928061694935], [30765, 1.0863115135985504], [30779, 1.0882033670717266], [30793, 1.0873289831823165], [30807, 1.0741638429671498], [30821, 1.0941511833869861], [30835, 1.0993775960699346], [30849, 1.0803324813632078], [30863, 1.1110369671496936], [30877, 1.0687823219539694], [30891, 1.103985670079679], [30905, 1.0666691395189147], [30919, 1.1036622895328023], [30933, 1.0771423684647643], [30947, 1.0874131429333656], [30961, 1.0692568292873001], [30975, 1.0804968150803327], [30989, 1.077265780678516], [31003, 1.1056042807811923], [31017, 1.0684914834389267], [31031, 1.0457112112025748], [31045, 1.0970004010798151], [32095, 1.0611003906684395], [32109, 1.0882420898792802], [32123, 1.0532152703822346], [32137, 1.0304941919694925], [32151, 1.0853226064994046], [32165, 1.070763650272372], [32179, 1.0637676530289368], [32193, 1.0590861056931613], [32207, 1.0493782714272624], [32221, 1.0786959699693213], [32235, 1.0755306811270344], [32249, 1.0545071851711398], [32263, 1.0817753730483728], [32277, 1.0795222996181846], [32305, 1.0967365680956378], [32319, 1.062658373697927], [32333, 1.0887000482498872], [32347, 1.088014103719228], [32361, 1.1039093534310596], [32375, 1.049710900773731], [32389, 1.104420845363494], [32403, 1.1172988229451788], [32417, 1.0999349308776905], [32431, 1.0819480597730333], [32445, 1.0941984140912726], [32585, 1.0000675492133855], [32599, 0.832954741164038], [32613, 0.917584783785485], [32627, 0.9214409933689555], [32641, 0.8964642854275635], [32655, 0.8109871228629846], [32851, 1.0466829230063703], [32865, 1.0218835045469379], [32879, 1.0380131525741179], [32893, 1.0896853174157952], [32907, 1.0223126932862328], [32921, 1.0212435608872905], [32991, 1.084843023372542], [33005, 1.0155761294971808], [33019, 1.0561225775303582], [33033, 1.0314392237109047], [33047, 1.0566983086681572], [33061, 1.0142143229307965], [33075, 1.0500545974612914], [33089, 1.046958328187126], [33103, 1.070776265310077], [33117, 1.0803450174909384], [33131, 1.0589018784205861], [33145, 1.051333175062018], [33159, 1.036385752005654], [33187, 1.0565235808203421], [33201, 1.0954903804097809], [33215, 1.0109701467642094], [33229, 0.9566506511817555], [33243, 0.9446438486025418], [33271, 0.8641286531203501], [33299, 0.8920926319559489], [33313, 0.8210388594423217], [33327, 0.8202520554781279], [33341, 0.8212628355548541], [33355, 0.866670871916371], [33369, 0.824570336016862], [33383, 0.8091499035739412], [33397, 0.805165175444429], [33411, 0.8096967560352559], [33425, 0.8345910686306266], [33439, 0.827141275175716], [33453, 0.8211403936962307], [33467, 0.8695959047447611], [33523, 0.8236082146149721], [33537, 0.8567893895144509], [33551, 0.8147725293143305], [33649, 0.8501813477009367], [33705, 0.8807524978394472], [33719, 0.8302720008489491], [33733, 0.9633088143644836], [33747, 0.8513644557440347], [33761, 0.8486278514166874], [33775, 0.8071162501467466], [33803, 0.8836940309105143], [33817, 0.8462199304535805], [33831, 0.8628297212784158], [33845, 0.8698323878479655], [34041, 0.8166263562499181], [34055, 0.9082545976634983], [34069, 0.8248783000709983], [34083, 0.8429659944749537], [34125, 0.8247148143161893], [34139, 0.8433280725616271], [34153, 0.8645997613181082], [34167, 0.8597692501827119]] \ No newline at end of file diff --git a/index.json b/index.json index b966cfacfe..ef9fb7f9c3 100644 --- a/index.json +++ b/index.json @@ -1 +1 @@ -{"project": "scikit-learn", "project_url": "scikit-learn.org/", "show_commit_url": "https://github.com/scikit-learn/scikit-learn/commit/", "hash_length": 8, "revision_to_hash": {"382": "e6989efd71a2adddd03979d1fe7a2e82e37ea51f", "395": "8ff9fc895bd6032636e3716f02773fdcd9cdd3d3", "587": "0e1faafec9871df73e875a0aadfcb67ec578c0e5", "590": "a40d325cec40da6cbcff8193a4ab4890823dfc76", "646": "ddc6d8f80dcf0a6cdd606efdefb89211a4dc7e9d", "745": "8a4bc2f03733e530591d6641f266a60670a373f1", "755": "8216797c4b1abca9dafd8de9d65472d32450b389", "811": "c7208c1a43335179ccddafc7748c1d7224e904fc", "813": "47890ac823314f1a9e2920dff7575850af56c273", "826": "b573fc0dcbfc2528807b5f0f8c0bc719c25d36f4", "998": "65d06f830ec6604b44d1a0510255868a8f762e3a", "1016": "9072aa593d76262fe445cf492ffac77e853501ea", "1131": "959e267898090e3c68ee118d5048afad124ff61d", "1207": "c83447b72c4f48ceb8249ea394ebf042618b8a2a", "1288": "f13dba15e3d56455c58867685ec554755a346c32", "1915": "d6b4444bbcc54a241cc955a5ceea80be15e7db2b", "1917": "60589710bd64e1fb2ede4d34d7fbb57e83892c86", "1919": "eba9984f735478d47c956ede42bdefd28aa6f9f6", "1969": "0f148e0011fb873bcd70cb3cc01690e7d621f670", "1977": "dc72677a9c13a656cda8be4b23cd897b56109b4b", "2701": "2c3d9e2fce5d2bae27e10657aa3c7ff45c39b190", "2711": "87741a7c65768464eb15f0976ed4bf6312795e7f", "2743": "03a85c19ac2854f2a33f613f87e81fd5f4560f55", "3102": "c07f9574c902b68744434d7b43f7394e0801d64e", "3151": "8a195624128da773c7d584d9352f65d8241cc92d", "3212": "897201083fd584a310cb8a2870704470dc28474a", "3289": "bdf3332f9694f8ecbdcf7ab0391989e24ac13f88", "3741": "5a1e1f48433ba867fb035b9dc31882f8d90f7744", "3905": "af6ab92b3bc0286e401218631859ee50f8be23f7", "4037": "f7c9f24511d9b32add23e75bbf0a2a6c223d932f", "4054": "8b2aaf069306d6b61b49a29d32123e69991c153b", "4684": "cf5c72eb9dc7696b5fac61466605b2860942946e", "4696": "3b48abd5fb0fa4f87c09f6b21d0d1f0e8b7873e4", "6177": "3e3872cde115550b75bb25c47c109b8bfd070eab", "6225": "3f1ea662ee1b1b08cee63cc31e4e3e36ec532208", "6511": "bfd36aa504078ce58f727f7f37e17349ab290e7d", "7872": "4533aa33daa35dd68c6d433b1d3560ff2b65b252", "7904": "34334f5ce6b1f166efda8652310133f9fc36ed04", "7919": "79749fd2939781e201191ef081143d8a575984e7", "9331": "34c2904a95a707c6e6148480a7e2c86a0f7ad86b", "9349": "73fdf6a9c982758be6da71a932ec4a3613eccbbf", "9357": "4ae44b0fe10b3ddf8390cfa8deae4dec45c40666", "9369": "7eb39fa0dc43ce485d3af2857c587811332eb148", "9799": "114822b1e18c9d7f887c58b8a3b2c279bdce6d35", "10413": "4bc8822c846de0d3b70d006ea32235d4375a575b", "10436": "0fede44fb39d691e873d58a4210452aa93c462a5", "10457": "b9ed384195df7b8d7824eac42f7b1bee58ef321c", "10778": "0dd2e39c1f7aec6830e4348fa63a04939252a0a1", "12368": "3e89aa5f42519d7f0230b99948553a8eb33dc1f4", "12373": "86e8b0d2a3533253a7082591f572d73897c02a2c", "12748": "8075887585b0449b6e87ee54c2ca4dbd56960e1e", "14515": "fc0b766ceca487504b040896124a3d809af2975b", "14698": "d13928cc0653f52de55e22118915b0c5bcba13d7", "14725": "34c4908369968dd0f77897ec9dd8c227e7545478", "16940": "bc8666f60f2c8c9ba16b30fbe0b342c3b94213e6", "17074": "68280fb4254b0781a66a1d2689708068799f0bbe", "17075": "b4e8b3ca4366901998c116540902d2687e0a5450", "17279": "518002955b0d6539f8f5e2710b9cefb178cc8ee2", "17645": "d4906939b1ef86657e6617d8fa078a0fbe0c2472", "17934": "2068ff2fd94abe4f14b0334eb4372a64b268f6b4", "19198": "4cc0235ec1ee654ea85cf465d280d33bcb1db20c", "19199": "09dc09a1e9d9088c2cb783c818980f5509d77a11", "19375": "df9f90cfa8795b6d85056f70177fb783d6ecafda", "19504": "bb39b493ef084a4f362d77163c2ca506790c38b6", "19920": "25082e522c90fa9184789f6bc450278b3e18fdda", "20502": "c0c2c737971b52e04b1f6516dfa1bfb05b30f4fd", "20509": "cd12906cabf3576a8c236a4128e959360037dde0", "20952": "918005fd5441650ae4a49b510bcabff69ae898bf", "20955": "b5383488c4b8b97b000585e61ed4e2178fa84d36", "21113": "da4f480a6adf5fed30a42500fe0e5a21c404ac2a", "21126": "82fb053536803f172def9f64e0d62151529173a0", "21322": "2999a2f544cd56575d940d7ab359819b392cccae", "21323": "3c546fd1226a895f68d317d2430daa71fc13e093", "21601": "ea042f1485d5fe45bcf2475c3070cab4e5ac3381", "21602": "51a765acfa4c5d1ec05fc4b406968ad233c75162", "22265": "4d9fab55b9e14e01a7d13344a2612ed802d0c113", "22268": "b687ab371d990373c4a599399172cf31d2f0c350", "22283": "cef2b62701f80ff50a37528b5337dd9a96f0069e", "22393": "38030a00a7f72a3528bd17f2345f34d1344d6d45", "22702": "a5ab948cbc366d705b1f8db8687c7162f51de22d", "23197": "759f4637f9f9471cf4218b9dffc00b464790485b", "23280": "36bc053a69ac5b9ba5a54cb2bd19adb33dcde50e", "23283": "62523372fc6331fc55df73a94d65bfa48c45c193", "23307": "83816c2a95e2ae3c4b3546912de4f4266e0c230f", "23480": "81ba62fe053d56e228ce097cbca91bc5de2e3f82", "23768": "b661a9c81930429cba4a56af291ce2bf8c59f8c9", "24417": "8c439fbe8c340389d7f9d99884180b2e7b21a79f", "24644": "eb6764936c9558553f7a7203a6aaa0ddc6497875", "24809": "f659f5539f9d36ebec4e1d98538919b55299bba4", "25159": "55bf5d93e5674f13a1134d93a11fd0cd11aabcd1", "25261": "7389dbac82d362f296dc2746f10e43ffa1615660", "25563": "7b136e92acf49d46251479b75c88cba632de1937", "25750": "ee986788cbd3256f0c36d2ddae155d8ca8f7be1c", "25758": "be2f62b2bfb40747a2dab20f29a341879b247a3c", "25766": "60eb00c72541b42697fa017fdfc74935299fc455", "25767": "93b19b04d3c81f9824b23e1b910126d51f3cd342", "25841": "a243d96336cb4f50ca3635b3062a273f3dc5183a", "25874": "b7b4d3e2f1a65bcb6d40431d3b61ed1d563c9dab", "25910": "e8602bc04e5c7ab32e6acb887b68172098f7f1e2", "26278": "1495f69242646d239d89a5713982946b8ffcf9d9", "26284": "bddd9257f39f190fec3d72872cff73c2b3cc2734", "26819": "db6c12fc117500a751799a3082d1503b65183920", "26820": "e36317b50d70453622ac6d0324a700816bad21c1", "26881": "d39134bc77d9f9a5a0316e21ee32ac3f9683da3d", "26890": "f1f765f476c3cb3e0a882324f8ed67763d76ed26", "26944": "0a56df6dbbe4f1a56cb11d132e43641d7358dd7e", "26953": "5f3c3f0378f2f30f3c4340bd9bf1e211e96d5c3c", "27063": "e5698bde9a8b719514bf39e6e5d58f90cfe5bc01", "27300": "4b7331eeb746b3facb4d70e1760c58ebe8b47f2e", "27325": "daefc22f832177dcbb690369058e0ca776944188", "27498": "a1261a7e18c19bb3dfc8d739a6512c6f671d9e79", "27571": "22a7d5bc722b0430908f202e3ea40aa2ba1a0361", "27604": "483cd3eaa3c636a57ebb0dc4765531183b274df0", "27674": "fd237278e895b42abe8d8d09105cbb82dc2cbba7", "27937": "91a0e4041e6a7ec3752b394956473503e87a5924", "28086": "0fb307bf39bbdacd6ed713c00724f8f871d60370", "28255": "d2cd2540418d3ff66b324ec18566dbe0b5991b40", "28261": "ab3dc9fdf31f35854b390168ac68fb304951305f", "28269": "2828a889bb96f3507ae0b38721d1e37b9f3e553c", "28272": "8b68ea165cb11625254d17c73603c4724d0b6d21", "28277": "74b632a1aa880a9c7f855599d16603626edf97fa", "28278": "28d84693b3855e9a1bf02b61392fb9f31055e897", "28284": "54ce4222694819ad52d544ce5cba5da274c34ab7", "28288": "bc39e62e02b9de82c2a266bb47beac4687843b51", "28291": "df61e9ed98b0777cc0962be6e2d161f4c30110fd", "28296": "13bccedeb02fa650a247a8ab6420bf9d44df3424", "28302": "7ed972193590c2a11839e15db87fa4818089de1a", "28306": "21121f50997dba43fffbfecb2f672431cf708363", "28308": "3bb138f87964dde5f25846f4380afba012cf26bc", "28311": "aa4a10dbfaee9fd52af06f0f0c8e8ae77f243ef6", "28314": "f35457f1fc3282d9efa21a6dc0bfe5a5e8a2f40f", "28320": "58451568d3b44ba632d708add02f9c30f356570a", "28326": "f2635e27894e6fc8c15b13284d3b277dfde65d71", "28333": "3b334c5b257465c5253b5a714eda7b34bc046b45", "28339": "193670c2a17c6a76f852e21cfafb954d195c9d29", "28340": "e6555decf8a72958d26d499deb17aabca41a562a", "28345": "fdb9233f72caec3d3f9720e073b2efdc141847ff", "28347": "1f217f33a25e6033bd0160ee22695186e12e7744", "28357": "cd673475bde70e87255ccd9b6f35687ce59b4b67", "28360": "6ca9eab67e1054a1f9508dfa286e0542c8bab5e3", "28361": "5654da026b7f1186b3a840d1cb140b6598b0af61", "28365": "5d5329c473791c90ebc58b4a18a923d1e6c216b9", "28367": "160debe468890e1dd90b610d5505eb118481cbcf", "28371": "d933c20befea779f9bfd35b4d85adaed9c30d684", "28373": "28f61efad3c4ce6536176978aef0fc857a35ff7b", "28376": "f1111be2fa9899a610843c36d203b0fab02f16c3", "28377": "547feabbb02de7da88bbc692e7b81419e373a0cb", "28381": "dccaf4c867c5ba254b1bd576101d30df40c00760", "28390": "aad222316754a072a893c5e735d4f3f6bd792725", "28392": "8471c8389d794309b0b62a353e3af903acd48223", "28396": "38a50f4c7b429dffeb94ed5abb428da06d0ba859", "28397": "fb67c7bb00f4d68ecbc65e8c46af5372442274cd", "28404": "a2728ac8d4dbc241a997899da61cb0fbf4eec96c", "28413": "4d7e61159db3fb59c474674b3d9f9c656d310e49", "28416": "51acc9dda812efca3c28d97ddc380c421c4949db", "28417": "f0e9d298be351eda7eb7302d6e673b097ae79831", "28418": "b5d63e34746ec273c1cbc5992a0477198a22f8be", "28426": "7db70d5b7988e069088f9956a28f1039e799b709", "28428": "b3806f77895d1146e83fbfdd60c6be43d4a7c144", "28429": "f77fb7265ff9425efb355890107d31012b2c8f33", "28435": "8479a74af207d857da4188b75375ce9d24c7ef90", "28439": "f650d9420bc75e70369fd8c5c96f965b58c0b1d0", "28443": "5a8bbf0195236b2e85217f90c363e5e7f975f157", "28449": "84bd4e29680a9a95ca01143a6ba79a42bc6887ef", "28450": "ffcb869d4b4fc2609b123ac7d089d00791c30f5f", "28452": "b4453f126f34447967f52996039d11b0d2fa0090", "28454": "a85430acdd49b7a63a4de110ee437d092d460d70", "28460": "2f09bbb7eb2fffdffcca3667b8fc38990d3b0893", "28462": "5a09d87da357660f8d16abc2eb424c67db5710c5", "28468": "5fb02bb7bfed1a5edbe12ce942bb77cacde8180b", "28469": "35320845c24ee58a21a99a2df044084e0e65f3a4", "28474": "63d2bbf1ef187d026641514cf511648cedf94701", "28476": "9d394c2daab6df104cef115ebd69f802cc327347", "28481": "eaa45c86f74c41828a92db4d4da2eee643cbda02", "28485": "da562b4fa58bdce4a7f3470f733f33d728747a66", "28487": "fa5f1d5fe3e9a354b32a27a0a24cecef7babebb5", "28495": "59f41f03755fa28495f514a795e19154c0273e35", "28497": "255718b4ad9a3490bc99c992d467f85737bd1291", "28499": "e21319fee78d75e47cacb747aa40b5621f5b04cd", "28501": "2c1719e68e243c71c32c98958cf270a49e7a521f", "28502": "7cb6b8fde70bd12501e85be8102c46b8ca48405f", "28505": "4773f3e39d788e734378f32064cf2e5629fbc7aa", "28506": "c9677d6a7d42aa7162a4c448284b8db1cabde0b0", "28507": "8ebb614a8dc09c7baccb45c6a2cd7d087d8e2ed6", "28510": "0937b4ab48136eb161ead4abd4806d0708b1bb4c", "28516": "95128d3e6d9231703517c732dc73ca8c18adb9d0", "28520": "d304331b450344e4660550b15d8174b15fb616c7", "28524": "be4f8a509f1382a9bbd24194bcfd19c6563fcf31", "28527": "2218ec46227c92301ac6837c4a8ae9b8dc5d3960", "28529": "54375d24a423d77fc5fac1071643a588fc98e818", "28532": "6af03a525c929312f26986f68d3866c217a6838b", "28536": "a92ec1b7582b14fc20e57ffe0c9aa2a00f637766", "28541": "45a817933ef51a24f0c5863c1026b4fe664b26fa", "28547": "6b4f82433dc2f219dbff7fe8fa42c10b72379be6", "28550": "5946f8bfed039540c7527a06f2e6e9f1fb2335c3", "28551": "def0e68085a4339490325dcbfc79143f21ca001e", "28554": "e325bf760f55fb1095a66f1223af2cd396685b2f", "28557": "dfc5e16066b3a3bbf34238cc0f67639d0965f1a8", "28561": "cbfe0ede80beca86750ab8113f17c18c8c8042ce", "28565": "266a11b2e17cf86effefe7b498b61ca31217ad31", "28566": "1e46db669318fe20458d7cf135f6107e19e90970", "28567": "34de1b9b2122783601b245450a1885d18558ac81", "28572": "aa1918cecff1161c36fcf06fa0fe4d1c69ece701", "28575": "be4c1d1fee6ee3ec40935283f9e1ab22ebce27cf", "28580": "0e546ebe5b5a97283ce03f915a83f0d2651394e0", "28582": "9b2a3e8ba50804e5cd1e4302097e86aebd2e8464", "28584": "5a63f903ff1d45084c4fd41f241bf5dfdd067680", "28585": "1fca00b0b46e89956f76e118581a4176888344ab", "28588": "28efdcc5a646fbb8da2456a0f4b8ce7968432242", "28625": "c6512929fbee7232949c0f18cfb28cf3b5959df9", "28629": "e4ae68f09a258d9578f640ff74ca6e209ec37dba", "28631": "9183486463c1df3b5b3c7e2357e17533bdd36573", "28633": "364b1e3e13a48446f86e4682bbf09ba4f010903d", "28639": "8c6a045e46abe94e43a971d4f8042728addfd6a7", "28644": "0f0eb522903431b07f6e267b8b0d42ef24659cbf", "28646": "6f32544c51b43d122dfbed8feff5cd2887bcac80", "28653": "e449f9f1be7dcb937ace1327a4b0c6728afafafa", "28659": "0aee596bb32136df8c68371d696770251c7d14a0", "28663": "c86076fbecaac1f6f5f068a5332871f5dd0f8451", "28667": "ff2e52da0c09e8cb2d9a1b62bd4c3ea481187308", "28670": "b94332434d0117e3d86407560a206d1c7bee1c81", "28673": "38e6022e24e1a3c91f932fec87302ffc0610651b", "28674": "88be2abb7b7f7450dc569e0065e672a0676e4130", "28687": "94b81ab2e7f9b0170b2d6ba6d84c1cc913367d8b", "28688": "50d3aaad36fa83f5d43e8177838726dd08f0526b", "28695": "74a37de119d2c7c9ea1cce673c2ee207541a55d2", "28696": "819c43cc7a1d7efab855e982a91e15be7aec7db1", "28697": "23d8761615d0417eef5f52cc796518e44d41ca2a", "28702": "d6bd7bee8799ea41c456c36a8ccf7780105615e8", "28706": "94337993ef1a29146c67d7e4a51e3053a79e92b7", "28712": "86bc6c9858dd1660f5762003a45733f50fc7a748", "28715": "5403e9fdaee6d4982c887ce2ae9a62ccd3955fbb", "28720": "4aff3857bceb1e42af5ff304140bd4d5b7e74e67", "28727": "6959532d4e43f4434993c027c7b2df09ade942ad", "28734": "dac560551c5767d9a8608f86e3f253e706026189", "28737": "b251f3f818e8d3cdb7ef843006d19da87755d444", "28740": "4d60a815d84531ba91bf097e9c814460113a7b72", "28748": "e9c6fcaa17b983858400465fd39a2616c980c3db", "28751": "b5e55f79fdfcb0f41f0cfb279e54a123822bca43", "28753": "70c6ac9d04c396faaf604c2fd1d3945f25e4d6d4", "28761": "26c5530e792c1319ddd3335e23d1f36cf90f6c3d", "28764": "e23dd851476ef54c2153d6178500a3e2345f95b4", "28767": "638b7689bbbfae4bcc4592c6f8a43ce86b571f0b", "28775": "94abe05b4b96de2ca30d998fb9adb2fbd3eb1bde", "28779": "15c2c72e27c6ea18566f4e786506c7a3aef8a5de", "28782": "72db93cc40884f42e05e4290d6ab63713d0075c9", "28786": "28ee486b44f8e7e6440f3439e7315ba1e6d35e43", "28789": "1045d16ec13b1cab7878e7555538573d1884aad3", "28790": "42e90e9ba28fb37c2c9bd3e8aed1ac2387f1d5d5", "28791": "f2773e840a0fcc9dd673cdd0da82dc43299a713b", "28792": "ae3d955c90d03479d4b6a8a3b359fba10826dc2a", "28794": "4beb0c27fc0439c12dad244fe4063e96f8983a52", "28797": "6f180d79f58b42a3fa06055c489b1edf857399ff", "28801": "15fd026963be233d37752f322b5dd484c58e09a8", "28802": "f4e692c0876425ef6afb6f514b54696f3e071c35", "28804": "0c74b8b7d5cdb60dc3a3240cdb36af40b9f40288", "28808": "302106bcac4476ecdd76b8c03fddb454edbcad96", "28811": "b7b510f9dbc87500e79301873852c6247c440a3e", "28817": "04f84c6d082864c208682d27256ff74b7b488734", "28820": "0d7d46f3bef0a2f943ee321f0f979ced165e0477", "28827": "266400e60ddc0bdba1f0de02ed49f45893e5647c", "28829": "3e45aeef901871b84ce59709e62f3d2245463cd8", "28834": "81102146e35c81d7aab16d448f1c2b66d8a67ed9", "28840": "114616d9f6ce9eba7c1aacd3d4a254f868010e25", "28841": "4dfdfb4e1bb3719628753a4ece995a1b2fa5312a", "28851": "f0576399d9cfb41c1f3cd4a0a2332578b1c0b573", "28853": "f47926999d35686ff2190c3940c82d7cc7f3e691", "28855": "c957eb37b5988e6e2a4692c1356e8689294404c5", "28859": "9cfacf1540a991461b91617c779c69753a1ee4c0", "28861": "36c635b77f9744b627248f96f15f3e73e97d3571", "28867": "132627e28b5be807b1e4b7d58bedf42b529d7800", "28878": "3ff1267a7b74259dd0f0fdaf7da88b02e727e7c1", "28879": "b1d686d07559fb83040cb085b752d86ebbb9b3ba", "28883": "c09c654ed4d5833d73f557381f3d10f3d062e5d7", "28890": "7fa2e6e2734b590d96e62d5932c648a9c1002f34", "28893": "138da7ea911274f34d28849337c2768d7e3a7a96", "28895": "2c5ea4e6b3add57588fb35293b7dd25506c5fe06", "28898": "e1f879e8eed85c5018d888c9f87f168bc44085e1", "28905": "0df9efe2c1407f3fb887c22056452c791fd83dc9", "28914": "004b44d007408aa2db1fdaf4428990d0d7b7f85a", "28917": "a67b284f90299989c4cc03f848dc9cc1be57c623", "28920": "c88c89cffd87c34299ebb8db6192c973823bd827", "28922": "2641baf16d9de5191316745ec46120cc8b57a666", "28928": "e4bb9fa86b0df873ad750b6d59090843d9d23d50", "28936": "a45c0c99a38cffca6724cb8fd38b12edd4fb6b35", "29084": "15a949460dbf19e5e196b8ef48f9712b72a3b3c3", "29085": "a9cc0ed86fca1480acbd8aaf211f062ee2abd5b7", "29086": "9c3b402f0082cfc17da3ab9430a203ecc2ac4dfc", "29088": "4023a0f94bde429456f45b983c84c5f35475480f", "29090": "a9ce392f3a58da5caf5ac9bd287205e220082fc5", "29092": "0eb9ad73c53c8f3cc0ea03d33312035853bee29b", "29093": "de1262c35e2aa4ee062d050281ee576ce9e35c94", "29097": "2bd3a4db529d707a9862d69cc1ddbcbe7a6054b8", "29106": "847fc6a27431d96eaef926773608168e8edb9e12", "29108": "48ab1bf71aea9b7036108179e00e0b2e1c3fcf7e", "29109": "f6e6ad2d9e9172c55c778392b27b69c6af87bd98", "29110": "5073d692f04dea88d595252a6cc0382509b6947d", "29111": "d73822f84f2832dcc25f0ff58769f60871a78025", "29113": "053d2d1af477d9dc17e69162b9f2298c0fda5905", "29115": "ca6caa28ab92cbf75a3cc2a411d2a225abd9a4ce", "29119": "1ac047d29a43bd1556d5c90e40376340a08bc3a6", "29121": "c67518350f91072f9d37ed09c5ef7edf555b6cf6", "29123": "36a4dcafedbcbb112e1d96fd04e73ba922523bae", "29125": "aa898de885ed4861a03e4f79b28f92f70914643d", "29126": "5b7136f04068e7dcdf5ae8ec4aa729107ee905c0", "29128": "c1cc67dd06d31a9b110377afe0c94b0cd50848d5", "29131": "7c873713df056a9554dd545b0d5f0be93630219b", "29138": "c9d223ccc58e2569b8e67f1d0217dd57a93ec07f", "29142": "deda6e2a5a01ad22096862bded5f66e9578cc39e", "29146": "7bb3e22b3c454a59619a56c314be04b4b303e09a", "29156": "6850c04186b88e88e9c8cd6eb673721af806e3da", "29157": "5d25ce13ae0fa8f1f9e02d046d1820b6dcfd6155", "29164": "1038024a438e2bc76e7e48edde7b7ca732dc506b", "29180": "1cd282d600088d2547d827af72a99e036106417a", "29185": "038c5cd04558e572b6a4dea7383a515ff10090e5", "29189": "9a13bdfaf1a47188d2e1262f0308f317e6662e8d", "29190": "b5e5db4a43e9f79d877a0d88ba94392925981b31", "29203": "0eeebb1e3d59f739f6eb9319ceb254a8486493d5", "29215": "dc2b5875d0465e30fe9a8181a0e07d85d15e66f8", "29225": "0ad2b5b0a9fdc010ff92dd536b102e865ac3c512", "29227": "617ff6ef72f28b7964f2b7fbedaeff7b24d8c2f9", "29228": "bb6117b228e2940cada2627dce86b49d0662220c", "29229": "c3a3b1e602d819e0b2a7b90a344580902be7ce0e", "29231": "572c2cb1c8ebc5ccf5b16573b7199f67912ff87e", "29233": "bd966fb7e43691918669db4533488d7596c1cd69", "29235": "36cc933f41d5eba5df154db57d2597d5bf421024", "29240": "7b715111bff01e836fcd3413851381c6a1057ca4", "29245": "1e2c899aa94526c9e0e916f1fe2463ecd30a35f7", "29246": "509b9ffbca2f73e2724cf073ac564238fae60b4b", "29258": "2a67d88258264eb2b6dfad221be8f8d61684dcba", "29262": "3a57efe45ef7ad3b32f3c3e2813f65316391b668", "29279": "daae053f7e9afc1dac24ce9ecce87f1356b96b03", "29286": "bf7a60a6a217c85620844b083c3935235b3aa177", "29293": "0d343bb2d296ece7205f9e230d98e3ad68ac4472", "29294": "e4ef854d031854932b7165d55bfd04a400af6b85", "29295": "18eef9adf9a0f8995ea8aee0bc4a94afc7aa5698", "29296": "c871c062f1bfb10bcd2cf39c25d233fb614eeff4", "29313": "5a879f4a024d499c74da65f0343b535be4aa096e", "29318": "f2a6e109f7be6f0d554e44cb4cb48b41081dc259", "29319": "d66b42708a5912039740cd08f747229433e579b5", "29322": "f72f1df4b03f63a027e738f644958e062f294503", "29325": "5c499942e0ade18fc1abb9669bd04462256bee73", "29327": "ed3642014be412b0bda13d1ec756baeabb0dcbfe", "29328": "1bd007fe0d5758d48829ea339f06206261fb2477", "29340": "85b0b54285471fd3af5f27ac4d25a6508263a79a", "29344": "cd8201b7fbdf6876719b44ec0abac85a6da583d2", "29349": "f081f5829182529eb1ab666f79c9b917b0b07f09", "29364": "ded59b5713bcbfcaa27d7d9d1de704c96817870c", "29371": "cf286be4f3f5bb9b604efd068aaa87dc303bb4ac", "29376": "57daa2de792121a6a22556f978234192b778e308", "29381": "238451d55ed57c3d16bc42f6a74f5f0126a7c700", "29383": "b41cb296ff137f28c3d100298b507ccb9e63a3bb", "29387": "2844f592be6eba36d952a4a1ad68cc41e2845c27", "29401": "df20e8156fdc06a89ba85952b8b5a32b47ee9004", "29404": "01a28e962ad203b552bd968e5a3564d4b7e2155c", "29409": "4797222cc4547451df8ecdadf2ec29488703b593", "29414": "daec880bff4217f1dd05484ebfcd912377652873", "29415": "86476347b362c8f2f0b6bd5cc9dfcfcec979f07d", "29420": "6b2d5a973a0b35453bb163fda72930dc4791945e", "29421": "81165cabad383db2ff7fd856e467041eea9b55dc", "29425": "cdc486a91affd19b603e8090b46eb5ca262f3569", "29429": "f812e2a27619650463cb12d765f1b443b47c0828", "29435": "416eef462df1a9bbf8e99b91dac58324f8a3f498", "29443": "4b0d291fb30d057980a9bf64331c398f7c425fed", "29446": "5088a402253a275249dbd52fef97d8e58628d28a", "29453": "4b8cd880397f279200b8faf9c75df13801cb45b7", "29454": "73174161931ac283499aaae2e45ec4605c895ddc", "29455": "21eb4686c5a53401b10e815d2f08ef8f090283e1", "29457": "8cf87a30bbd5cbd6444c6f3ed380a3d2b5f67461", "29458": "e648c4cb919151161202130b2e4aea6413329900", "29469": "d6735f4851d828984a0517de954b9b88c74919fe", "29541": "fac31e727947ad53f2ed107f58a10b56b165cee7", "29548": "f46190846c5d8c0bd898d1447a2a07fc50fcee2a", "29550": "9061ff9e58425789338f68563df1bcfd386d93fc", "29551": "cb7271339e56631fe47a22e259c98716f14f6894", "29572": "c0e5d1bc746069e6087d499dffc707d94df09237", "29586": "c21491f05e9ac58ef4b4a7f0c3ec0e9c06b4a05a", "29591": "89d66b39a0949c01beee5eb9739e192b8bcac7bd", "29598": "40e1f895b172b9941fdcdefffd5a2aa8556ed227", "29609": "047cc2ec0cf71cd7233a7163a847b197e3a4acf6", "29611": "517b38ad30f36c6fe9eaca2c4a496ac1c63b3f50", "29621": "597df0ad17fa75d7a6832f71e7859fcb1925e29c", "29636": "e00e000c9a96b1f2173f352769d8c590ce6e0113", "29638": "f309ffb2a6c7638f25eda75873578c948a2bdecc", "29644": "5f6abe6f7d64fb5e1fa7dccc0aaf4ec2e217cdc4", "29648": "8fc351656a44789893bd8b092ea12fbbf5b803ca", "29652": "f71c0313142c4e5f2f35a0021c36075cf8dba611", "29656": "efa7f7c8753aa84b4b001d699aa6c70a2929813d", "29657": "6c566da8c99b4908a549aeb659cd4b1124bc2448", "29662": "6c068e2c75b551c72d3f551e68d7c5a76b6fd7a1", "29665": "47f888239c507358fc7bab7f832101db648b9461", "29667": "0d1e63366c6e361ba89b8588ccc26b01c47a5563", "29733": "9b033758ec681e8fd7433a8bb35d9777acd4f8ba", "29735": "2eabb45d3588bd0bb3422e1b3c2c6189268b3b1e", "29742": "f33fb0af65380e3360cfc9dd7f291ab59e2ef63b", "29750": "2e3c32dcc1e99ad753dff4a9aa26657073883158", "29753": "9cb4e761f530e7a0708059b1312921753d056cbe", "29757": "6d5774f6895aa84a8ec74762bcb29fc7e5173d41", "29761": "e7fb5b8c8dd2cd4d7ccd6f9f9ad6c1d206c43a33", "29765": "4b8888bf864322af1a1ae664d8d39c37b928ac6f", "29766": "d152b1e6e2a02e5bf725b41ecd63884d7d957cee", "29768": "23afd5d95c18915c55070cecaecf9f3030ae9bbb", "29776": "d3429c138a1eab162f3627e14c6ac26f49d59a16", "29783": "8ad7c3f02daae525ee83231fbd33fb65e8e05288", "29788": "8b18d4cbfc3a10ce85decec292d30470c69f40d7", "29789": "b2ee0f4ed1265a2147a6c470373de2990074fa23", "29790": "2f2364de6f6b61a24cefb8a18369f0811f721886", "29795": "682bd050be056e2104b4f9c2df4931bb642e7946", "29798": "57658ba4ba1a8bb00e8bcfa17cba028588ecf47f", "29805": "5f6e17c084c36e9eaee55a7e05f4b2f43be21a25", "29806": "47a49c51d14b7b648be6a4918c1441cb29c96a9e", "29807": "034ee98eae76f2fc5d9ab3b6e52740728821465d", "29808": "2ec028d2e8c34e332c851311e8cf330128081a1c", "29813": "a343963d961225be25468ca64b54896dcba48e87", "29815": "958ccc5bb1d43594eafe825e387e3e9876ac8893", "29828": "9b210ae8ffdc40e210f30f24656779ac690b899a", "29839": "e34b64c7ac57c9e6bfee3e26f27d6d74a9bd913a", "29844": "d4d5f8c7e02cfaced76757fbf38e21c5b28b67b0", "29858": "4c9bf8bbae7cd10baa754ba2bd5631329180fe09", "29865": "ec1248ae8af8e5fe53655f0269d5f4e178c21b70", "29997": "0d378913be6d7e485b792ea36e9268be31ed52d0", "29999": "8955057049c5c8cc5a7d8380e236f6a5efcf1c05", "30002": "f7ecaee36fbcf1847943e122504a4ab7c585bd90", "30010": "d4129527d3e86e34e898885ee8640e2c65900f47", "30013": "bd871537415a80b0505daabeaa8bfe4dd5f30e6d", "30023": "01551ad8db01230c1bb7ae94803f48e337f4db88", "30028": "d5e045fd600bf7f3edd984fe7f8599124a67f7f6", "30035": "8cfbc38ab8864b68f9a504f96857bb2e527c9bbb", "30046": "f8728dfc07af5bb47d97459b78c6729d76f076de", "30053": "9b605b498c6b1ac6b2713432d75d14854a2481ae", "30066": "74bf394b872d9ed9a91a949f04dbcf2239c558e7", "30068": "48e83df4509bb2ae1c1d74570a9efed7b61bdede", "30070": "8aa0ac006ce87cf8a7bf12c40380b14af6ae2a10", "30074": "f2231993675134ca7d01b1b8ebfd6d082372272e", "30076": "d63405f1bb6e4e6f56f59cb947a51ffd48cba895", "30077": "793e90b344aeee90432b47515410c5666097f0e6", "30078": "1b9de7b8b6a1a535b80505db1039ad19b3cc3738", "30085": "016df3326c48e0a78f9efb5871473bff4a09f0e3", "30086": "2368132b70559de2e890d7f16ec10f6247c9d5a2", "30096": "6077d52b706d118c0d9fb1e69c254bc67e15b078", "30104": "7bfa9ccd7c4a6d73bb2b0a99baf6f9515e681951", "30106": "00d7e59d1e4555f68c4e2bd005fa30048c2e3be5", "30112": "432ae47beeaf611547aafb69131834f151fe1136", "30116": "6cdffd860c49d30d3b9fa72c5fc1174e8eeaa35e", "30118": "248f6cf3156f6a48333b4074aac4c12e2c15155c", "30123": "a278f2a2ce49bdd55ccb73bb67e35b9c2ada12e7", "30128": "73d0b4f2d1aad5884738eeaac1aab2c3135fc471", "30135": "f8f77b4acca401904f6e7332bea55067f9d1e797", "30145": "bacc91cf1d4531bcc91aa60893fdf7df319485ec", "30155": "35af6dc808c8d317eb7017d1b16e271c9c8bba77", "30156": "b1a5d3c40ce0664978e41305cfd1e616a8d3dfd2", "30157": "832513a7fb6570c41f3c8bf4bf7cbaf110da300e", "30165": "7c7666c9b9f894e3220f52dfc98d95d658e042b0", "30174": "80ebe21ec280892df98a02d8fdd61cbf3988ccd6", "30179": "3e0f49b62339941722d0dfbcb90f5af0ad1b2e6c", "30185": "3f8868072c1eb7b37ade0a131db37303817ab5c4", "30189": "4035b63f7ff9437e389b720db45f73ef66566ce9", "30190": "b1202af3b379e698539a2719f2b1e28706ce5388", "30198": "5f3d1e57a91e7c89fe3485971188f1ecd335f2c1", "30202": "02b41de8fca096d92aea6a5336fce372b842c5c7", "30203": "77fbdd1c46c2931fb06b373786efd03da90d3e78", "30208": "63a1a31a17f9bd9cdf617b2cf04bfaf2f32f0a17", "30212": "01109213520eccbb9d5a51ed2930e7763c3386c4", "30213": "056f993b411c1fa5cf6a2ced8e51de03617b25b4", "30215": "39782b71b03d180bb2fe2ac321b6bab87a43746a", "30218": "dce9782a0d174d317c89ad52124348fa3bfb4e47", "30225": "845b1fac9e8bcfc146e7b38119ce6c500e00a10b", "30227": "f21f1d7539134fabc93e57309dd3a4717d00c7f3", "30233": "b84d67751753cd7ee81b3ede8d3d16951ddc4cef", "30235": "cece90e57c2b64e56367ddc1bad7edacd4f29e26", "30238": "2fc9187879424556726d9345a6656884fa9fbc20", "30244": "e5cc0b80714223c709d48b832e32fa73bae323a4", "30248": "3e460e8b7e4c6d9eb2041d793a339dddc000b3f3", "30254": "304a14783ffa4eaad738aede0e12a76ae44df076", "30259": "78a941aa73756595baff805fd390a0590262ac97", "30260": "c72ace8cd652309963ecdd6c01e33fa3c58c9161", "30500": "7e1e6d09bcc2eaeba98f7e737aac2ac782f0e5f1", "30501": "9aff4def9890819556e3d32c8ca6b2f27b528c22", "30502": "5dfa5d979a3acb87ba028d0e9e72e3e73bf1657f", "30506": "b242b9dd200cbb3f60247e523adae43a303d8122", "30507": "ed865d7a3363a92846d7955a9bdedae2ad29542e", "30510": "42a34e81a2efd64ddd7b40b433765e7c361cb51e", "30515": "585f4f11bca4c5a4cd2949ebd4ba9aecb9f3dc31", "30519": "5d86281723891c3dda755509f67a524da94ea07a", "30520": "1c24595c74e0bea246737b19f8fdfc8a1ffa2282", "30524": "26e2c38a961a27a9e53ce7814bf27f840510b237", "30525": "49588ff1e677d3d6fddf8798603a06f06fdb6e61", "30529": "ff09c8a579b116500deade618f93c4dc0d5750bd", "30533": "4e974e0d5e0b9e4aeaf83ab5b2f6381c5e122c6f", "30538": "7f61186cbcbc43cd6ccd717abd097f638b786984", "30542": "8d6217107f02d6f52d2f8c8908958fe82778c7cc", "30543": "9daed7f8970c25afaa54f671815afd75605acf26", "30544": "1d1aadd0711b87d2a11c80aad15df6f8cf156712", "30545": "0c65bbfe8ce816a181780d2a249c94dd653e115a", "30550": "ab08e4dba5f1f87b8c3395f32469a6ddb5e34f89", "30552": "9816b35d05e139f1fcc1a5541a1398205280d75a", "30556": "330881a21ca48c543cc8a67aa0d4e4c1dc1001ab", "30561": "08e02167843d857c0fb205479ae32183a887bac6", "30564": "6145cae3d1cefaeffcb49b3080233022bcd1368d", "30565": "cdf0d69c9c0cd2ce400dd79176ed4457a7730d67", "30577": "203caeae4c90331fdd7e087ee27b54a8541bfe03", "30581": "1e4ac040eef6bc8c43c77122bbfdd5d83cb8365a", "30586": "26e1930abf5ad637e44573a152dadbd45fb5db0b", "30593": "755d10a7fcfc44656bbed8d7f00f9e06e505732a", "30615": "254ea8c453cd2100ade07644648f1f00392611a6", "30621": "46d914349dd4027bdb1a69eed4d73694d0b37fad", "30622": "0dfaaadfe2d0e0b4fd9d2ba22a75b7b1b1903049", "30629": "b0067e0e7e0ae095592bc3a9a8cb7ba9e200c1be", "30635": "9f96d42e3966ec0ac778132bf1192ba36f413006", "30639": "581a66316af6b57e6d455b5517c543932f857f0b", "30640": "9f85c9d44965b764f40169ef2917e5f7a798684f", "30643": "fc05d2b1d9e815aabc9f1436a8dabd281d08b0e1", "30646": "77bc7f921c9039f917456d81b0a9db9926b987ab", "30647": "6440856fbb0e1c0a048316befbf6df4e0a5765c1", "30650": "b80138fccb025ec1f8944e1b17d08b5fc2e9d1cb", "30657": "34f4465466028ccb3f7c42d71d97f7158281d6ff", "30665": "bdb7db524a5cb584d975b3bb1823494bcd5eb92f", "30670": "6c09bab585acc708b099acf383fefe6ffe50ca89", "30675": "0cb06ea33ead6bc191e6721942606a6b17ecc01a", "30679": "f9d046766f590af3c181cb2d994ab1ea125d1216", "30694": "3786daf7dc5c301478d489b0756f90d0ac5d010f", "30704": "abbee570f31a91243c22b1892e42056bb915c056", "30708": "e11c4d21a4579f0d49f414a4b76e386f80f0f074", "30718": "111c78214cb92d8a21c95734c6dd0e76d5398db2", "30723": "26d218cfeb80908a52bbfc302dc5f43cef4b5181", "30729": "998e8f2068c7d9f43a30d997b63e4875688d0b1a", "30730": "5c7dac0131eb2318ccd4afad1e2e646e7b83b5ff", "30734": "691972a7cf04e7a8918b907556b4e9904f82bd0c", "30739": "e0ebc7839153da72e091f385ee4e6d4df51f96ef", "30744": "a1a55886a0f615b4e87659af489369a9e66e40bc", "30748": "70eebb992e8a799cbc3d7f1fbfddd104c0908c66", "30750": "34d39c7da61499c7a0e5a57dbb8b02e31a914ac0", "30754": "7a2a0f74ca7b9e452c94ee6de3146ef879dfe41c", "30761": "9ced5ec0b123bbe47179cffff02844ba659a752e", "30762": "c83c6fc83d504b08bd6aab4f12c45d10cf0e9ffa", "30777": "b19c748adb30d8ac1af94dc296dcd424d4631ccf", "30782": "578e3eb532d8ab5396d5579ff06e46604818e750", "30785": "269bdb94898b9944b10de2db6b17fffe7b69a432", "30787": "742d39ca38f713027091324c4555f9b4e1b9da05", "30794": "7d9f1cae7f49ff6bca4e474a4c9e8f4e7b88a357", "30804": "692225dd2cb5058bc006716270c1d48c59172f95", "30812": "d6984db4f2c8ff8c0b29413b40d53903f2123ce7", "30817": "5afd5e160bb731a0445c960fd94740080a44ebd7", "30821": "ee1b6d217f0566115dec706c6256fd81c4087833", "30838": "f6d37b85d551051ab26e04135db5e6db623dd955", "30849": "bbdb2eff9b877c0ae00ed9854099b92119504f62", "30861": "fb4dbfd837483ac3daf06dfc28871bfcfb65c4ab", "30868": "751c5cd05ff545c20ad0b09ac491c07f31e4cd56", "30872": "142e388fa004e3367fdfc0be4a194be0d0c61c8c", "30890": "0b2f4ead15a8b069222c4bd538499c9c739a8f96", "30904": "99262c06c02375ce9579638d0f37ee1ce61807c8", "30907": "7116165f493998cde7989a29458f36bdfb0a9ab5", "30908": "ee5a1b69d1dfa99635a10f0a5b54ec263cedf866", "30917": "2a4b40a0a46b1e6b1271a89fdb466d1c7dfae6ea", "30928": "26eedbd1f453435b7d8f62d151ba23c22a567d88", "30931": "e5736afb316038c43301d2c53ce39f9a89b64495", "30938": "f89a40bd92004368dee38ea76a1b9eaddaff4d7a", "30945": "cb547ae5d1484d6332ea7891ec7d7ac742342741", "30949": "5b901fe5734d1f3900bd8f13534718b007012c4a", "30955": "2c5058e0d6cc4f5c627d2ee256f4735fd5ba4a39", "30957": "d14fd82cf423c21ab6d01f7d0430083f9d7026be", "30967": "fab022e2edf98d745f2ceaf3048e0ca6bc3b86f1", "30974": "86c62cff7121b218f7bd7007bd6880e206561019", "30978": "7811a3a4789f5a252e99708e7bd45445f78839e4", "30987": "59428da95751fa92d46687850932f8f6ab1b4f3d", "30988": "b4da3b406379b241bf5e81d0f60bbcddd424625b", "30994": "dded6761c53a433a8f72b40aef33bf7c2f76e425", "30997": "9858fdd9a34a630499cf34c0b5c4900d6f81d55b", "31009": "41b8f84f1f1eb5930c0ec60598ca1748005a1f75", "31019": "adb47e7c142ce6d699cc5927925d448cb2c1ab91", "31031": "df692c03c1a6003878c6fc4d2f9f222d304dcee3", "31039": "bd9336db0c23b4bb8725cbea34fc9c43cdec70b2", "31040": "aeeac1c1d634dc80abc93fb30b3fe48e1d709b64", "31041": "e275d9df3da36352605f4e68b14593bf9f435c9b", "31120": "c987b5ca84610bf5251ea8fa33b48c5826942a0d", "31184": "16625450b58f555dc3955d223f0c3b64a5686984", "31297": "80598905e517759b4696c74ecc35c6e2eb508cff", "31927": "6cb2c52375a812ff509c00f4eed1da232e7a8932", "32088": "b4f51fd1569a0b90d56061f678f2f4fa7b04bf5e", "32090": "5436818d8bfc7e6499c07f4225aba377899a687d", "32101": "29f80b058fd037c8c4a22ad0638ca7d833aa264e", "32104": "f3f3a804d7386e80003655c44d0a9faa707a618f", "32112": "20bb279d1f7602acdba4c13853b3c7d086aaf8db", "32115": "53acd0fe52cb5d8c6f5a86a1fc1352809240b68d", "32116": "189d2f304c73a40dd2d2d38f6203ff9d41cbd48e", "32120": "ad91259f20529306efe445f5a1da4dccc8c81b5a", "32130": "ee5d4ce151c633499b02abc85a0cbb863f3254f8", "32131": "2f8b8e7f1aa628289b92cfc5bdfc7907688962b1", "32132": "15599753b63f10748ffb374aacd37dbb37806a37", "32138": "bfe68b4641cd918f9f4d9f1a60f2f3e27fd707c8", "32148": "ae943bd7a02fe6ad93df619cce61cbad1a694c57", "32152": "ae6bf39b310ed5bb46349c831a05f55bba921dcc", "32156": "0bf24792d69ebc2024821adafd63ee37d0110cd3", "32157": "b4f17015ceba5dde8b720cb03992cbe6186604dc", "32163": "257757755b1c2bea22f3b78da392df07b809788f", "32174": "b22f7fa552c03aa7f6b9b4d661470d0173f8db5d", "32181": "681ab94222a9ba5f7b39f768f0ab92873905541a", "32186": "21829b5ddb8f50292dd302fff5c9aad1c4b1998a", "32187": "d2c713bce62974f7a17aab3e556d0bf14eebab3c", "32193": "df626e43ac3c99da2aeb005709d77395bd717e6a", "32197": "0c22fa1da475531aa31b5c67f427b5e1461835b5", "32198": "14684bbae31918a394d61c75c23edee42d6c9761", "32204": "8694eb00f8a3c0dede331fe60c0415bfaafef631", "32213": "4ee3fdd85c8d78da24c166a4127e8bc7bc8dd469", "32218": "b0b7c154ae5691310d56ea6c738a6b14c6692224", "32220": "5ceb8a6a031ddff26a7ede413db1b53edb64166a", "32224": "93c7306836aef3cb62e3cc25efeeae1a8dc8bbde", "32241": "0c8820b6e4f9c49f55e96fcbb297073a887eb37b", "32249": "8610e14f8a9acd488253444b8e551fb3e0d60ef7", "32252": "625650fa69c312f6d9b712eb41baf33dac1be3de", "32256": "1dc23d7a1a798151a45ce1d72954821d61728411", "32259": "3e6a39a73c2ca39e073e4b58117f59e92b3b2313", "32261": "7c2a58d51f4528827e9bfe9c43d06c5c1716bfb8", "32265": "0a4811677ee378c07a17062cedfbdcf3f9f40975", "32270": "ff9344f3d8d11d38fa3a2497199113e5bac9537c", "32274": "0e4e418eb2d34001724923b83111d5bb92edb4d1", "32291": "ffc0f66676b4835eb1bdd3f3ecab025e9c1be9fe", "32292": "86c7599d996368899898349185df068c4e2c5bd7", "32294": "53234c5b6bae7827fed9c74072cb059d33c476ba", "32303": "083ab6fcb6bfe2b4f454befcb1c585267b39e5fc", "32305": "af930a9aa4f55361a66051ac9ef151cda3742bf8", "32308": "80d21c37672dbb4b2439fbfb19b8d5e28d7f20ab", "32312": "b4ffba9e225971b9abe59aa28146197eb9910cb0", "32331": "239e16319116ab7445c0557bb08783ab2d60673d", "32339": "76511995f7804727c6f0494ca05e6e3f4d4f5430", "32340": "aee7f594f5d82ba75bcb8d720066ce18c727d0d1", "32342": "2e481f114169396660f0051eee1bcf6bcddfd556", "32343": "3e47fa91b6ed73f358105f2a1c6501e14f633bba", "32348": "64432e1cf65fc87c763737aa6422bb92d3573786", "32349": "e947074f63c6602ae15cd57b1fa4f6658040cff7", "32354": "7ec1bfc2ab7425bcd984d631b5bfeb9082ce11bf", "32358": "70442b9ee3753a6d63a9b2bfd35e3e51cadce230", "32361": "dbde1da1954be91b9a0a12c9a109c17cd109bc76", "32378": "c4d221ddcb9171f5bb05f7fe0dd0b96f7d532331", "32387": "86301acc28bb70f0e18f4be0e0b2d1e694e897ef", "32397": "85574f9cb847f39124816e6bf8a02fbf9550bd32", "32408": "9c9c8582dff9f4563aa130ef89f155bad0051493", "32409": "b728b2e8b192857f3522007328fa66909ed68787", "32411": "75db1bc2dbd716016170241d8daae97624d01252", "32420": "a7698a8bd853f1f32281ef635c7d4a827383d5fd", "32424": "3eb00d83ca40b458065d2739c0a7d60098e05701", "32432": "433600e68fbb12e72d8c5e0707916f5603bb7057", "32454": "c7d5f58d490e19680a4dc3d530f969baab033f2f", "32499": "dc580a8ef5ee2a8aea80498388690e2213118efd", "32569": "affaa62b1d053f3349e766aee91f397267a72656", "32572": "2cce02414d4a7161f0d105450c196d94b1182220", "32576": "96a0bc861ad2ba3c63db0326b42b41ddabeb2aff", "32580": "ce00ba817e7592c8e14f7610dd1f13ad694a3e5d", "32588": "e411c29625e66f7e440f1acce4069e01201cf122", "32591": "62a017efa047e9581ae7df8bbaa62cf4c0544ee4", "32597": "ba1d23d13e402367c6401e07256867fdd5a4a0bf", "32600": "9e08ed2279c80407f1d4c92a27279f73a2d08bb2", "32605": "bc00bdce93d6cbd4441d3427a65464fadbaaacbe", "32607": "a0a6ea744f355ed078e491eadf49d1b9c1a17cda", "32619": "52e89a4e17b8b27dbc8dc41592d354f65e179260", "32629": "dc7ef61d0d58be84355b965481032d59f8f41e2e", "32640": "f7eea978097085a6781a0e92fc14ba7712a52d75", "32646": "bf03a6354670414695ef483de8187135aeec6cbd", "32649": "d5fcb20b39c9b283d9485a9dcb4b2d554422e269", "32651": "71a647f8bcc4c0ec8e4b8ce76f5f566f0513a222", "32770": "e58f36c73bd524ad87b05126a4e5b50dc4b24fcc", "32838": "4ff92e03d78db5f6eb9abd87594b491cebc80bf9", "32841": "22336afec6384e85366d94dab7a108fd2a0b64fc", "32848": "677a4cfef679313cd437c6af9e0398a22df73ab6", "32852": "d4e7158bcaa6f91a42e8afba21b7803bf82c3813", "32853": "d9cfe3f6b1c58dd253dc87cb676ce5171ff1f8a1", "32854": "0c42159547d000dba29cf7d5d47bc251bdf0fd52", "32856": "6adb209acd63825affc884abcd85381f148fb1b0", "32869": "7b595569b26f4aa65a74a971ef428f4f071f48c4", "32870": "1042757565b85960c42e97ef4a21d9943e7cb48e", "32871": "e6b46675318950fd5138aaf29ba76f6ce2fd91b8", "32879": "b4afbeeebeefe253bdc12db2820f5eef5639c8b1", "32880": "ae4a1b1a780e50d07ca68c15a1876c618d8fd19f", "32881": "de67a4420f1713058070802ad593cbcd2ee2d5f3", "32895": "fabe1606daa8cc275222935769d855050cb8061d", "32898": "2c867b8f822eb7a684f0d5c4359e4426e1c9cfe0", "32900": "4180b079f7709fe5ab8d32a11438116dc8957715", "32914": "20ad9cd62cbef744eb28b29ab8a33fc3b51f8a3e", "32919": "7e8d3c505baafa45bd94d9e28ee3d35141ff91c4", "32984": "9aaed498795f68e5956ea762fef9c440ca9eb239", "32986": "a70954d8298965cbad25a337b08e1a765b736555", "32997": "c991e30c96ace1565604b429de22e36ed6b1e7bd", "33009": "30bf6f39a7126a351db8971d24aa865fa5605569", "33021": "fd9bff1fd20b129f516d4675b24aeacfdd3bac56", "33031": "ab7e3d19c16011d9ed4bd80f867336d8a741216a", "33040": "b397b8f2d952a26344cc062ff912c663f4afa6d5", "33050": "9260f510abcc9574f2383fc01e02ca7e677d6cb7", "33057": "e3e880f9a749df95727a9c3102feb755387d33bb", "33066": "3043ea6cf96571da0787252401abdb62ee04612f", "33075": "e3d1f9ac39e4bf0f31430e779acc50fb05fe1b64", "33086": "18af5508013d8497b0449c059b9a794c9643735a", "33090": "49a937e974190b4ab20c7506052ce8a67c129da1", "33095": "01b9050b690ebb07870454720f5f67ac235348e4", "33096": "545cc809e16005fb5f5ee401b19cf69e9874d58b", "33103": "10dbc142bd17ccf7bd38eec2ac04b52ce0d1009e", "33109": "ec8a2a63b3e02bb955079c2af26d95af6a407242", "33120": "70c489f1273a5ff877e61750b3a69590bc002b6f", "33127": "c3bfe86b45577a9405a4680d9971efa9594a0657", "33131": "1ac10736135a62b0dce02c2529f73cd049c31296", "33148": "7f1e15d5c253d5dfdc8c55b5f1c6139e9bcd1de3", "33179": "cf3573ee90c541c82d22b80d57c9dec7d99fc58d", "33189": "1834cd6b76f63156b786e3e63cc48604532505c1", "33194": "97327c75b3c77babc5a97d367c7512b19c07cffb", "33208": "66a4d9639e27bc04c21bac4eb259fe28b1dad4af", "33209": "667dc564848bf3cfd3bda47367ff1202ad7fa9bf", "33211": "463d1665e628628e837d11b323d86cadaae27081", "33213": "5a332e77a10a44107276843d8532ef79f239c8f3", "33225": "cec09e20910e3eb970310732c40ec63b35b5cd35", "33228": "a1877586bbe5eaa90bdd8aa5714b0a05efab750c", "33229": "66a39055412b5c1d0c5740be7e2849ef8b040fa1", "33259": "ae35ce83679ccef74932fbfe554d1e1ea63ff6fa", "33279": "28d65c55332350a85f84c0ad45a306a6e90b68e4", "33285": "a2b85716728da2596ee2275cbea939497af9146d", "33291": "ea046f024694b9a558c882b8c2610c52dad95e29", "33294": "f5ec34e0f76277ba6d0a77d3033db0af83899b64", "33295": "86541f2b3bc8a96264e265cb810cf79858544340", "33296": "6d356dda608e01537a53e20d4c5e80220297eb24", "33302": "f034f57b1ad7bc5a7a5dd342543cea30c85e74ff", "33309": "689efe2f25356aa674bd0090f44b0914aae4d3a3", "33310": "4ccf41beeb9618129ddf89200e6d9540ada7f96c", "33311": "42d235924efa64987a19e945035c85414c53d4f0", "33315": "41b0bd82ffa90c00778c6b69f400d8ddf5775eb2", "33323": "c8f79e234e99733bd2e9c52b97684cd924aa73e4", "33332": "295397890f26a21f5901108a94f2b80eb94e5705", "33333": "849c2f10f56b908abd9abbbffca8941494cc0bb0", "33337": "314f7babcda8fd5e6813b8a6ed31d87af0efdc62", "33338": "e5c65906ee7fdab81c2950fab0fe4d04ed7ad522", "33341": "4f89e717570e76650ca6f73e25c5151f8902dad5", "33346": "092b7f3f6721cb076c40aa4cc74b128ff3990f21", "33351": "99c9f41c774b6b3d4f36f515b06f5b20838d0771", "33358": "0e253d96f89eb507476a6c498f0972c1b426e8da", "33359": "1e8a5b833d1b58f3ab84099c4582239af854b23a", "33361": "18cf8d01ea67d44739d18dbb7c9452e5aa8c9b79", "33370": "8cac52f9d1a393f7809801405013b5e0d2785499", "33373": "21312644df0a6b4c6f3c27a74ac9d26cf49c2304", "33376": "9ea0ec40f8b2753ab1bb4d97407c9b05a883f0f1", "33380": "20be4dfb50e015ca62c11bc3f4c73ffe4d74c36f", "33386": "180e059b1b329dfb9b304a12a1506fc7e0fc20ff", "33393": "cb233674ddffeb1f75f63309f94e4f90d0a2bdf8", "33400": "33a1f1690e7a7007633f59b6bee32017f4229864", "33414": "ceec2fa696e51b8303f5475c3b263f68a856ab8b", "33424": "9cbcc1f205e8be4dad1f383239e98381abb28bd0", "33428": "ee5d94e0a05da11272a4af1cd731f9822565048e", "33437": "d2b9c802844a5bbd81687fbe6b43fc80a79c8ffa", "33444": "d9212debbce3513310c1e06709ab735d426850e9", "33453": "309a8b63ca4f127149140c0cfa0e0e0f417da436", "33504": "7f9bad99d6e0a3e8ddf92a7e5561245224dab102", "33516": "0a45f93418d2724e496b39c2d260a2ae047ec334", "33517": "b88b53985d9ddf8cec60414934c55a5745e8b958", "33518": "483fafe5d1a27446a8f05a0d9bb3762de47b1618", "33520": "14995509a996ff5575c032fb7aead25bf6bb595c", "33524": "27c3549b3dfa8a50e2753d825118588ea2923f2c", "33533": "34446739dfbe5cb61d2ddccb1f4fcfaa1efd7a9b", "33536": "3a291fce9b1db5f8b408de9dc8e0d6a2d6b93496", "33537": "d5a354605ab9dcdac5a05ffc692d962ad2bb0dac", "33543": "fe26a08c5c0902db80667bed2d72a506826417ab", "33546": "dbad41e58d6010cf1ab0f93eacb5fee652e91136", "33551": "dfd299b19e1e4a167023cac76c8e1c57c01341a9", "33648": "b35cd21530d9a97deba3a6fe70ba14d1d8d2afa6", "33704": "372b957ae3bdd5ec4758db1e58b2496532d53b78", "33707": "989d29946a197eedde3c30f71ea4498e6642ec05", "33708": "6f9c6629e505c5892ded725efa86f91c8fb986e4", "33712": "a05eb6bbe30bc40904274c87afb4ac93bcd60168", "33715": "8ed0270b99344cee9bb253cbfa1d986561ea6cd7", "33722": "cb15a82e6439feda50b0605d70ce6d06c2eac7fd", "33733": "c634b8abbb5d96e0089b593aa04fb5ac80a047ec", "33734": "bbc73cfd7f5a85f6ac63432d3294abecdcb81d2a", "33756": "611cffe181d7dc8b744947c6be801203f92f0f8d", "33766": "a823012281a6c7f3b2f92cddc048b9be82e98cf2", "33802": "0a03293a89895729eb6c8f0dcdd7db86142b92c5", "33808": "0d701e8fef043b3604008868bcd94a96d1217f4b", "33813": "8faa92011e76bace1df02230bce83ee3a5e083b0", "33818": "b7169fd060e10a9328cf985a5ac8440932f25fee", "33820": "3c9495cc64b738ce402103bb685afeb01543971d", "33826": "3b35ad03d348658cd85ba4b3647873fae5f75a48", "33833": "89ea028ebdb605bd75f48f59de3e0bf770d3b8a4", "34030": "55a65a2fa5653257225d7e184da3d0c00ff852b1", "34031": "ba7d86956da03aa4fd230b1bbe8df57b63cf2dc0", "34034": "20dad5851e77836a01aea710de3f965fe9384576", "34046": "f86f41d80bff882689fc16bd7da1fef4a805b464", "34049": "457b02c61a2f3cd353d2997929b67a3ef890bf60", "34052": "38a1e64bbe42a7b66a77835e46e5f7725bccd18b", "34058": "2a548da593ab7a8f1c7b0af8985de8935bc3be98", "34065": "bdf66d048c2113e94397b11ff17b7b5c03938ab7", "34068": "9f6592f714cf1b0fb6f2d8fb636d9e458fad41d5", "34075": "04e39db499afab852e4e2603807384a402a871a9", "34079": "286f0c9d17019e52f532d63b5ace9f8e1beb5fe5", "34113": "ebe4c7ea999a32bafc9044ebe75b4901f92037a0", "34115": "b470ba1bd5c5b4955016f509a6baeb06ffbbafe9", "34120": "65923a7850cb7aa128c2422205a1bcad732db54e", "34126": "b93f80badd1873bf7db9c703879163a9b7aab6c4", "34139": "fb6b9f59469a4ffcffee2999f531f4bb4c2128fd", "34140": "b22c706c700ce4ac24ee26e21fbce8a24ef799a6", "34141": "c6d0d29b1903e40c9947c5aa1a2f420fb7f4f004", "34152": "093e0cf14aff026cca6097e8c42f83b735d26358", "34155": "1f1329f7ecb001eda2ff8e6d6a68bc2054c4962f", "34158": "e9c74a3f0a5944b1420158d36b1bfed836234b97", "34160": "5c85b581b858c5c99b9f90c6a5fd049f0ad85a4b", "34162": "dcebbc4c5c97f886a57b0684a5e943f94db1bd58"}, "revision_to_date": {"382": 1264603663000, "395": 1265024295000, "587": 1269007740000, "590": 1269244318000, "646": 1270698297000, "745": 1272878771000, "755": 1272909852000, "811": 1273294444000, "813": 1273337313000, "826": 1273550555000, "998": 1277561666000, "1016": 1277824675000, "1131": 1279558872000, "1207": 1280235748000, "1288": 1281104090000, "1915": 1286358759000, "1917": 1286371631000, "1919": 1286373337000, "1969": 1286782666000, "1977": 1286812002000, "2701": 1292596297000, "2711": 1292968871000, "2743": 1294669325000, "3102": 1298808434000, "3151": 1299078131000, "3212": 1299680572000, "3289": 1300670714000, "3741": 1302729559000, "3905": 1304345121000, "4037": 1305108339000, "4054": 1305126138000, "4684": 1309505367000, "4696": 1309545528000, "6177": 1316527045000, "6225": 1316642399000, "6511": 1318977607000, "7872": 1326216418000, "7904": 1326287141000, "7919": 1326426441000, "9331": 1336328405000, "9349": 1336407543000, "9357": 1336426836000, "9369": 1336524866000, "9799": 1341415689000, "10413": 1346780365000, "10436": 1346788092000, "10457": 1346981442000, "10778": 1349734773000, "12368": 1358801181000, "12373": 1358806382000, "12748": 1361636276000, "14515": 1375060310000, "14698": 1375915741000, "14725": 1375972053000, "16940": 1401972588000, "17074": 1404172403000, "17075": 1404240383000, "17279": 1405354512000, "17645": 1406899808000, "17934": 1409835738000, "19198": 1425667359000, "19199": 1425681522000, "19375": 1427396256000, "19504": 1429027572000, "19920": 1436588422000, "20502": 1445007457000, "20509": 1445013082000, "20952": 1445953225000, "20955": 1445958667000, "21113": 1446753465000, "21126": 1446818031000, "21322": 1450749753000, "21323": 1450761225000, "21601": 1455802186000, "21602": 1455802246000, "22265": 1473791605000, "22268": 1473799038000, "22283": 1473882154000, "22393": 1475007587000, "22702": 1478902517000, "23197": 1497903977000, "23280": 1499947923000, "23283": 1499952302000, "23307": 1500281648000, "23480": 1502470027000, "23768": 1505921382000, "24417": 1531668719000, "24644": 1535551327000, "24809": 1537887812000, "25159": 1542875805000, "25261": 1545209521000, "25563": 1551431215000, "25750": 1556378170000, "25758": 1556603560000, "25766": 1556634531000, "25767": 1556635319000, "25841": 1557442357000, "25874": 1557893876000, "25910": 1558616196000, "26278": 1564406958000, "26284": 1558572641000, "26819": 1573637668000, "26820": 1573476950000, "26881": 1574093837000, "26890": 1574244189000, "26944": 1574933073000, "26953": 1575301264000, "27063": 1577976510000, "27300": 1582908441000, "27325": 1583315487000, "27498": 1588010313000, "27571": 1588689638000, "27604": 1589270282000, "27674": 1589872045000, "27937": 1593854670000, "28086": 1592994930000, "28255": 1599747257000, "28261": 1600274505000, "28269": 1600378277000, "28272": 1600458232000, "28277": 1600722669000, "28278": 1600789062000, "28284": 1600865667000, "28288": 1600968970000, "28291": 1601106935000, "28296": 1601326769000, "28302": 1601415150000, "28306": 1601462345000, "28308": 1601589341000, "28311": 1601660413000, "28314": 1601930618000, "28320": 1602017230000, "28326": 1602089300000, "28333": 1602190160000, "28339": 1602263563000, "28340": 1602436405000, "28345": 1602536302000, "28347": 1602591864000, "28357": 1602693776000, "28360": 1602796581000, "28361": 1602859901000, "28365": 1603135307000, "28367": 1603210848000, "28371": 1603296704000, "28373": 1603378269000, "28376": 1603484187000, "28377": 1603729650000, "28381": 1603813015000, "28390": 1603918365000, "28392": 1603993849000, "28396": 1604082959000, "28397": 1604157689000, "28404": 1604266317000, "28413": 1604338820000, "28416": 1604443088000, "28417": 1604518746000, "28418": 1604585464000, "28426": 1604687645000, "28428": 1604867994000, "28429": 1604916743000, "28435": 1605029333000, "28439": 1605135329000, "28443": 1605211856000, "28449": 1605292115000, "28450": 1605376572000, "28452": 1605564612000, "28454": 1605628238000, "28460": 1605722026000, "28462": 1605822301000, "28468": 1605911343000, "28469": 1606015242000, "28474": 1606161074000, "28476": 1606336705000, "28481": 1606416080000, "28485": 1606497935000, "28487": 1606765444000, "28495": 1606821855000, "28497": 1606904333000, "28499": 1606925797000, "28501": 1606931617000, "28502": 1607004204000, "28505": 1607116223000, "28506": 1607613543000, "28507": 1607723835000, "28510": 1607961058000, "28516": 1608059116000, "28520": 1608136519000, "28524": 1608242770000, "28527": 1608307759000, "28529": 1608395895000, "28532": 1608486943000, "28536": 1608587907000, "28541": 1608647213000, "28547": 1608676289000, "28550": 1609623728000, "28551": 1609698314000, "28554": 1609772780000, "28557": 1609840352000, "28561": 1609944537000, "28565": 1610128553000, "28566": 1610214433000, "28567": 1610304129000, "28572": 1610387413000, "28575": 1610461836000, "28580": 1610553773000, "28582": 1610641692000, "28584": 1610821727000, "28585": 1610915313000, "28588": 1610996785000, "28625": 1611052138000, "28629": 1611096802000, "28631": 1611164131000, "28633": 1611255467000, "28639": 1611341861000, "28644": 1611414840000, "28646": 1611487810000, "28653": 1611614513000, "28659": 1611689734000, "28663": 1611786407000, "28667": 1611868041000, "28670": 1611929245000, "28673": 1612010107000, "28674": 1612054336000, "28687": 1612217026000, "28688": 1612286029000, "28695": 1612393433000, "28696": 1612446975000, "28697": 1612514236000, "28702": 1612635631000, "28706": 1612696745000, "28712": 1612872626000, "28715": 1612885946000, "28720": 1612981796000, "28727": 1613076767000, "28734": 1613159543000, "28737": 1613400754000, "28740": 1613569280000, "28748": 1613674543000, "28751": 1613731449000, "28753": 1613840479000, "28761": 1614025369000, "28764": 1614104321000, "28767": 1614147824000, "28775": 1614262574000, "28779": 1614447340000, "28782": 1614618476000, "28786": 1614683996000, "28789": 1614793397000, "28790": 1615128856000, "28791": 1615226636000, "28792": 1615308357000, "28794": 1615382782000, "28797": 1615484044000, "28801": 1615590149000, "28802": 1615592700000, "28804": 1615733031000, "28808": 1615834814000, "28811": 1615930546000, "28817": 1615992780000, "28820": 1616089367000, "28827": 1616186648000, "28829": 1616249229000, "28834": 1616353572000, "28840": 1616519345000, "28841": 1616701156000, "28851": 1617400845000, "28853": 1617566024000, "28855": 1617640124000, "28859": 1617737608000, "28861": 1617832061000, "28867": 1617916880000, "28878": 1617992344000, "28879": 1618175593000, "28883": 1618257581000, "28890": 1618347639000, "28893": 1618413717000, "28895": 1618490002000, "28898": 1618600033000, "28905": 1618868919000, "28914": 1618954142000, "28917": 1619040868000, "28920": 1619110246000, "28922": 1619178650000, "28928": 1619467448000, "28936": 1619544136000, "29084": 1619600857000, "29085": 1619617061000, "29086": 1619725616000, "29088": 1619739533000, "29090": 1620050725000, "29092": 1620244799000, "29093": 1620265097000, "29097": 1620677421000, "29106": 1620770403000, "29108": 1620920636000, "29109": 1621006227000, "29110": 1621032016000, "29111": 1621172982000, "29113": 1621241554000, "29115": 1621364951000, "29119": 1621431262000, "29121": 1621520828000, "29123": 1621605580000, "29125": 1621709722000, "29126": 1621878405000, "29128": 1621944157000, "29131": 1622043901000, "29138": 1622124056000, "29142": 1622233878000, "29146": 1622489783000, "29156": 1622582567000, "29157": 1622648501000, "29164": 1622728054000, "29180": 1623250683000, "29185": 1623445015000, "29189": 1623510849000, "29190": 1623544407000, "29203": 1623793687000, "29215": 1623965080000, "29225": 1624040252000, "29227": 1624091050000, "29228": 1624219173000, "29229": 1624304793000, "29231": 1624373201000, "29233": 1624376492000, "29235": 1624391134000, "29240": 1624465784000, "29245": 1624562451000, "29246": 1624606131000, "29258": 1624736650000, "29262": 1624805941000, "29279": 1624903928000, "29286": 1624992439000, "29293": 1625090236000, "29294": 1625105021000, "29295": 1625431412000, "29296": 1625491027000, "29313": 1625595144000, "29318": 1625657660000, "29319": 1625751948000, "29322": 1625848516000, "29325": 1625952066000, "29327": 1626010586000, "29328": 1626111448000, "29340": 1626196541000, "29344": 1626363236000, "29349": 1626711194000, "29364": 1626810193000, "29371": 1626899379000, "29376": 1626986049000, "29381": 1627065892000, "29383": 1627161489000, "29387": 1627314805000, "29401": 1627418844000, "29404": 1627489158000, "29409": 1627574925000, "29414": 1627660909000, "29415": 1627719890000, "29420": 1627906614000, "29421": 1627974960000, "29425": 1628111422000, "29429": 1628181136000, "29435": 1628283892000, "29443": 1628368786000, "29446": 1628440292000, "29453": 1628538236000, "29454": 1628605886000, "29455": 1628675255000, "29457": 1628892021000, "29458": 1629060700000, "29469": 1629148355000, "29541": 1630592131000, "29548": 1630682386000, "29550": 1630790223000, "29551": 1630863632000, "29572": 1630935898000, "29586": 1631009128000, "29591": 1631035486000, "29598": 1631116383000, "29609": 1631193014000, "29611": 1631268037000, "29621": 1631548012000, "29636": 1631623921000, "29638": 1631647186000, "29644": 1631721222000, "29648": 1631796656000, "29652": 1631898294000, "29656": 1631979808000, "29657": 1632053184000, "29662": 1632171877000, "29665": 1632243233000, "29667": 1632346710000, "29733": 1632414516000, "29735": 1632423037000, "29742": 1632516259000, "29750": 1632746318000, "29753": 1632820895000, "29757": 1632916788000, "29761": 1632994638000, "29765": 1633110693000, "29766": 1633193599000, "29768": 1633355552000, "29776": 1633467847000, "29783": 1633621378000, "29788": 1633724151000, "29789": 1633749561000, "29790": 1633835632000, "29795": 1634072187000, "29798": 1634142184000, "29805": 1634230269000, "29806": 1634295072000, "29807": 1634399117000, "29808": 1634426648000, "29813": 1634558965000, "29815": 1634655567000, "29828": 1634761299000, "29839": 1634850335000, "29844": 1634909602000, "29858": 1635021251000, "29865": 1635104837000, "29997": 1635154787000, "29999": 1635179228000, "30002": 1635285319000, "30010": 1635365351000, "30013": 1635455200000, "30023": 1635527737000, "30028": 1635604153000, "30035": 1635850978000, "30046": 1635966997000, "30053": 1636041350000, "30066": 1636132510000, "30068": 1636189566000, "30070": 1636288882000, "30074": 1636385531000, "30076": 1636488027000, "30077": 1636582028000, "30078": 1636658652000, "30085": 1636756391000, "30086": 1636838462000, "30096": 1636999437000, "30104": 1637085139000, "30106": 1637168632000, "30112": 1637262498000, "30116": 1637319488000, "30118": 1637418893000, "30123": 1637618997000, "30128": 1637705763000, "30135": 1637777927000, "30145": 1637864181000, "30155": 1637956585000, "30156": 1638018624000, "30157": 1638057062000, "30165": 1638220668000, "30174": 1638310769000, "30179": 1638381381000, "30185": 1638476003000, "30189": 1638563225000, "30190": 1638654791000, "30198": 1638819086000, "30202": 1638888185000, "30203": 1638968646000, "30208": 1639082235000, "30212": 1639163319000, "30213": 1639179354000, "30215": 1639419807000, "30218": 1639518773000, "30225": 1639584547000, "30227": 1639692819000, "30233": 1639777744000, "30235": 1639934505000, "30238": 1640020199000, "30244": 1640116258000, "30248": 1640200222000, "30254": 1640294413000, "30259": 1640364531000, "30260": 1640431291000, "30500": 1640431648000, "30501": 1640701470000, "30502": 1640863001000, "30506": 1640982697000, "30507": 1641153417000, "30510": 1641224916000, "30515": 1641333323000, "30519": 1641416619000, "30520": 1641492764000, "30524": 1641589783000, "30525": 1641673299000, "30529": 1641854947000, "30533": 1641931361000, "30538": 1642009315000, "30542": 1642112955000, "30543": 1642155901000, "30544": 1642210241000, "30545": 1642433763000, "30550": 1642536525000, "30552": 1642593136000, "30556": 1642716792000, "30561": 1642787468000, "30564": 1642877522000, "30565": 1642958675000, "30577": 1643053590000, "30581": 1643130258000, "30586": 1643221209000, "30593": 1643294500000, "30615": 1643402974000, "30621": 1643494622000, "30622": 1643560106000, "30629": 1643638950000, "30635": 1643753378000, "30639": 1643824343000, "30640": 1643884968000, "30643": 1644011254000, "30646": 1644076710000, "30647": 1644187621000, "30650": 1644265942000, "30657": 1644357039000, "30665": 1644436807000, "30670": 1644533900000, "30675": 1644596303000, "30679": 1644699640000, "30694": 1644873503000, "30704": 1644958366000, "30708": 1645027501000, "30718": 1645117746000, "30723": 1645215955000, "30729": 1645306485000, "30730": 1645459454000, "30734": 1645557198000, "30739": 1645623865000, "30744": 1645739513000, "30748": 1645808094000, "30750": 1645892531000, "30754": 1645969117000, "30761": 1646084810000, "30762": 1646160183000, "30777": 1646262003000, "30782": 1646300512000, "30785": 1646416299000, "30787": 1646496694000, "30794": 1646682100000, "30804": 1646768999000, "30812": 1646859477000, "30817": 1646942986000, "30821": 1647030828000, "30838": 1647109345000, "30849": 1647209663000, "30861": 1647285454000, "30868": 1647371949000, "30872": 1647451140000, "30890": 1647557283000, "30904": 1647634447000, "30907": 1647727404000, "30908": 1647800199000, "30917": 1647896133000, "30928": 1647984962000, "30931": 1648054763000, "30938": 1648160658000, "30945": 1648243671000, "30949": 1648319349000, "30955": 1648406260000, "30957": 1648483673000, "30967": 1648581286000, "30974": 1648672004000, "30978": 1648748734000, "30987": 1648847676000, "30988": 1648901247000, "30994": 1649106907000, "30997": 1649150463000, "31009": 1649273792000, "31019": 1649350287000, "31031": 1649449476000, "31039": 1649539600000, "31040": 1649611192000, "31041": 1649689094000, "31120": 1651052569000, "31184": 1652277602000, "31297": 1652962489000, "31927": 1659704464000, "32088": 1662650106000, "32090": 1662708913000, "32101": 1662737945000, "32104": 1662814977000, "32112": 1663007356000, "32115": 1663074696000, "32116": 1663145605000, "32120": 1663256210000, "32130": 1663340845000, "32131": 1663401075000, "32132": 1663530485000, "32138": 1663598489000, "32148": 1663772127000, "32152": 1663870025000, "32156": 1663946749000, "32157": 1663986725000, "32163": 1664140855000, "32174": 1664229269000, "32181": 1664287910000, "32186": 1664388499000, "32187": 1664461587000, "32193": 1664562847000, "32197": 1664805604000, "32198": 1664868848000, "32204": 1665078930000, "32213": 1665164580000, "32218": 1665423832000, "32220": 1665524925000, "32224": 1665593694000, "32241": 1665696739000, "32249": 1665764076000, "32252": 1666028219000, "32256": 1666128017000, "32259": 1666180465000, "32261": 1666275645000, "32265": 1666549553000, "32270": 1666642605000, "32274": 1666714923000, "32291": 1666790709000, "32292": 1666777887000, "32294": 1666859255000, "32303": 1666971913000, "32305": 1667251255000, "32308": 1667319103000, "32312": 1667425048000, "32331": 1667500962000, "32339": 1667597404000, "32340": 1667655643000, "32342": 1667827735000, "32343": 1667920232000, "32348": 1668096180000, "32349": 1668161431000, "32354": 1668247510000, "32358": 1668370218000, "32361": 1668450346000, "32378": 1668542987000, "32387": 1668615570000, "32397": 1668712662000, "32408": 1668796144000, "32409": 1668967067000, "32411": 1669028816000, "32420": 1669155628000, "32424": 1669229533000, "32432": 1669314024000, "32454": 1669652459000, "32499": 1670501069000, "32569": 1672253566000, "32572": 1672335295000, "32576": 1672502364000, "32580": 1672681312000, "32588": 1672782103000, "32591": 1672846504000, "32597": 1672939907000, "32600": 1673017687000, "32605": 1673261378000, "32607": 1673369231000, "32619": 1673465204000, "32629": 1673554076000, "32640": 1673647527000, "32646": 1673714356000, "32649": 1673878111000, "32651": 1673989150000, "32770": 1674567494000, "32838": 1676412451000, "32841": 1676667117000, "32848": 1676831129000, "32852": 1676924601000, "32853": 1677007953000, "32854": 1677060631000, "32856": 1677174739000, "32869": 1677242387000, "32870": 1677318985000, "32871": 1677433403000, "32879": 1677533692000, "32880": 1677579308000, "32881": 1677582108000, "32895": 1677624245000, "32898": 1677758469000, "32900": 1677852228000, "32914": 1678142018000, "32919": 1678230083000, "32984": 1678293098000, "32986": 1678300766000, "32997": 1678376309000, "33009": 1678470836000, "33021": 1678726711000, "33031": 1678822655000, "33040": 1678919037000, "33050": 1679001183000, "33057": 1679069398000, "33066": 1679352540000, "33075": 1679412211000, "33086": 1679509889000, "33090": 1679586734000, "33095": 1679678108000, "33096": 1679772347000, "33103": 1679950288000, "33109": 1680037895000, "33120": 1680104936000, "33127": 1680197441000, "33131": 1680447506000, "33148": 1680547438000, "33179": 1681241666000, "33189": 1681315114000, "33194": 1681387148000, "33208": 1681509837000, "33209": 1681654063000, "33211": 1681751116000, "33213": 1681854133000, "33225": 1681925606000, "33228": 1682005553000, "33229": 1682068409000, "33259": 1683056233000, "33279": 1683705315000, "33285": 1684243870000, "33291": 1684328444000, "33294": 1684348796000, "33295": 1684455041000, "33296": 1684767724000, "33302": 1684848919000, "33309": 1684945115000, "33310": 1685003210000, "33311": 1685116374000, "33315": 1685468792000, "33323": 1685549169000, "33332": 1685636762000, "33333": 1685696112000, "33337": 1685775923000, "33338": 1685970274000, "33341": 1686060207000, "33346": 1686164484000, "33351": 1686223118000, "33358": 1686331783000, "33359": 1686562004000, "33361": 1686677411000, "33370": 1686762523000, "33373": 1686822807000, "33376": 1686837859000, "33380": 1686921372000, "33386": 1687195456000, "33393": 1687280423000, "33400": 1687362667000, "33414": 1687454936000, "33424": 1687533193000, "33428": 1687797870000, "33437": 1687889014000, "33444": 1687970808000, "33453": 1688059673000, "33504": 1688049596000, "33516": 1688140195000, "33517": 1688211972000, "33518": 1688408245000, "33520": 1688420112000, "33524": 1688567545000, "33533": 1688654566000, "33536": 1688738244000, "33537": 1688764635000, "33543": 1689015102000, "33546": 1689105785000, "33551": 1689179641000, "33648": 1692199567000, "33704": 1693312776000, "33707": 1693402216000, "33708": 1693497411000, "33712": 1693574690000, "33715": 1693915368000, "33722": 1694012791000, "33733": 1694116492000, "33734": 1694366006000, "33756": 1694455478000, "33766": 1694542477000, "33802": 1694634394000, "33808": 1694689715000, "33813": 1694807049000, "33818": 1694874439000, "33820": 1694956547000, "33826": 1695059234000, "33833": 1695143438000, "34030": 1695204060000, "34031": 1695224738000, "34034": 1695308063000, "34046": 1695653805000, "34049": 1695740821000, "34052": 1695830869000, "34058": 1695899976000, "34065": 1696007297000, "34068": 1696024508000, "34075": 1696265713000, "34079": 1696357529000, "34113": 1697533319000, "34115": 1697561306000, "34120": 1697643038000, "34126": 1697716358000, "34139": 1697824316000, "34140": 1697879383000, "34141": 1697997241000, "34152": 1698055850000, "34155": 1698081283000, "34158": 1698155592000, "34160": 1698235049000, "34162": 1698326139000}, "params": {"arch": ["x86_64"], "cpu": ["Intel Core Processor (Haswell, no TSX)"], "machine": ["sklearn-benchmark"], "num_cpu": ["8"], "os": ["Linux 4.15.0-20-generic"], "ram": ["16424684"], "python": ["3.11", "3.8"], "numpy": ["", "1.25.2"], "scipy": ["", "1.11.2"], "cython": ["", "0.29.36", "3.0.2", "3.0.3"], "joblib": ["", "1.3.2"], "threadpoolctl": ["", "3.2.0"], "pandas": ["", "2.1.0", null], "branch": ["main"]}, "graph_param_list": [{"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.8", "numpy": "", "scipy": "", "cython": "", "joblib": "", "threadpoolctl": "", "pandas": "", "branch": "main"}, {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.8", "numpy": "", "scipy": "", "cython": "", "joblib": "", "threadpoolctl": "", "branch": "main", "pandas": null}, {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.11", "numpy": "", "scipy": "", "cython": "", "joblib": "", "threadpoolctl": "", "pandas": "", "branch": "main"}, {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.11", "numpy": "1.25.2", "scipy": "1.11.2", "cython": "3.0.3", "joblib": "1.3.2", "threadpoolctl": "3.2.0", "pandas": "2.1.0", "branch": "main"}, {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.11", "numpy": "1.25.2", "scipy": "1.11.2", "cython": "0.29.36", "joblib": "1.3.2", "threadpoolctl": "3.2.0", "pandas": "2.1.0", "branch": "main"}, {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.11", "numpy": "1.25.2", "scipy": "1.11.2", "cython": "3.0.2", "joblib": "1.3.2", "threadpoolctl": "3.2.0", "pandas": "2.1.0", "branch": "main"}], "benchmarks": {"cluster.KMeansBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.KMeansBenchmark.peakmem_fit", "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "a9d893de2d92e56e4dbeab4d7b7b4d5e00add3f4e993b164664b7ebbdd036dc7"}, "cluster.KMeansBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.KMeansBenchmark.peakmem_predict", "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "0f7d945338d774baae43a82dff7fe9f0db16ff6d1481b5afd437048b544396fc"}, "cluster.KMeansBenchmark.peakmem_transform": {"code": "class Transformer:\n def peakmem_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.KMeansBenchmark.peakmem_transform", "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "576d76cb6e3aa82315e3d3dc6a2e8b7e58cb38bdd510df6801ab645465f4eb70"}, "cluster.KMeansBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.KMeansBenchmark.time_fit", "number": 0, "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "a8dbf56b4b6365cb1e3c23b71c7df95ae011632c95124496f8fd1c30430154ec", "warmup_time": 1}, "cluster.KMeansBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.KMeansBenchmark.time_predict", "number": 0, "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "611589f0c08131355c37720106ea132a2653a100660cd34884455259325b9c83", "warmup_time": 1}, "cluster.KMeansBenchmark.time_transform": {"code": "class Transformer:\n def time_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.KMeansBenchmark.time_transform", "number": 0, "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "8a02da09ca430e84b11161256032a2d4c08df103e4626718278e8b69b90acb0c", "warmup_time": 1}, "cluster.KMeansBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.KMeansBenchmark.track_test_score", "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:16", "timeout": 500, "type": "track", "unit": "unit", "version": "67ff12752edbc7e4055ec0bddc293f22d59aec0eaa675c166f502a008bc22c59"}, "cluster.KMeansBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.KMeansBenchmark.track_train_score", "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:16", "timeout": 500, "type": "track", "unit": "unit", "version": "a5e07140ef3dd16920358a4c08c2f9f81d0e21f40bf5d8990b8a37b6a07c64e9"}, "cluster.MiniBatchKMeansBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit", "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:65", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "42f5ccf79079b60ff9fa8b0220a6b1fb951f46d27574d343f6e6b4b69dd8f1f0"}, "cluster.MiniBatchKMeansBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict", "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:65", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "03ee5b059682250c4b3d0793edf5a4978efb06c760148550f068e82dcb71e75f"}, "cluster.MiniBatchKMeansBenchmark.peakmem_transform": {"code": "class Transformer:\n def peakmem_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform", "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:65", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "f844a68fb0292b177c459487189f905d1afb89d79ab35a0539f9f4217b445ff2"}, "cluster.MiniBatchKMeansBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.MiniBatchKMeansBenchmark.time_fit", "number": 0, "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:65", "timeout": 500, "type": "time", "unit": "seconds", "version": "40617ec6fdd94e3a650dba98f8204c9779e63ae7803343b23e7368f7b068f26e", "warmup_time": 1}, "cluster.MiniBatchKMeansBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.MiniBatchKMeansBenchmark.time_predict", "number": 0, "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:65", "timeout": 500, "type": "time", "unit": "seconds", "version": "561b80fa4780c86ee698a0efd05c5d6c1bce24014006c5ec9096c2f3a960b9fe", "warmup_time": 1}, "cluster.MiniBatchKMeansBenchmark.time_transform": {"code": "class Transformer:\n def time_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.MiniBatchKMeansBenchmark.time_transform", "number": 0, "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:65", "timeout": 500, "type": "time", "unit": "seconds", "version": "2cf7a764c9fa1511ff1e1dee921060dc33eb0608e1cee96b782dc7b5d3f91f89", "warmup_time": 1}, "cluster.MiniBatchKMeansBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.MiniBatchKMeansBenchmark.track_test_score", "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:65", "timeout": 500, "type": "track", "unit": "unit", "version": "7aeb8a20f66080e18e15f92e245fd1dd8de235e2f53d355596424dc7c30ae295"}, "cluster.MiniBatchKMeansBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.MiniBatchKMeansBenchmark.track_train_score", "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:65", "timeout": 500, "type": "track", "unit": "unit", "version": "b0c324767051682ea0bfc17c991f3de50e4876d683b1167c11ae8d4f2349b9c9"}, "decomposition.DictionaryLearningBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.DictionaryLearningBenchmark.peakmem_fit", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:41", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "8c3205268eade479bfda221734bf6129ab2a7b2bf4c59a8e6e855469f519672a"}, "decomposition.DictionaryLearningBenchmark.peakmem_transform": {"code": "class Transformer:\n def peakmem_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.DictionaryLearningBenchmark.peakmem_transform", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:41", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "b2c047a9e4d9d9cc6dd2d41a3738c21c183facbf5d609e8bfb354499f0b38ee4"}, "decomposition.DictionaryLearningBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.DictionaryLearningBenchmark.time_fit", "number": 0, "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:41", "timeout": 500, "type": "time", "unit": "seconds", "version": "9f6c61216a35b8b5a205dbce3e4f541613c2e1df4cda9f85b16a7a41a02a9e02", "warmup_time": 1}, "decomposition.DictionaryLearningBenchmark.time_transform": {"code": "class Transformer:\n def time_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.DictionaryLearningBenchmark.time_transform", "number": 0, "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:41", "timeout": 500, "type": "time", "unit": "seconds", "version": "a9786d7edfa47d44fb49632ba092edb63068a33298968990f071b58ad312e45a", "warmup_time": 1}, "decomposition.DictionaryLearningBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.DictionaryLearningBenchmark.track_test_score", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:41", "timeout": 500, "type": "track", "unit": "unit", "version": "022cecb50e5ba330d0728d08afbca34a130f0e74529bce6c8c93aca80a4bcae5"}, "decomposition.DictionaryLearningBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.DictionaryLearningBenchmark.track_train_score", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:41", "timeout": 500, "type": "track", "unit": "unit", "version": "6ed8ae7b04c1c5b4be0a5847795321be4c50195958c72642e1ca9367d838649d"}, "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:75", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "cf54cbec149e048235b388e434462754421fc5f8593697b431e17bd01f79cbe1"}, "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform": {"code": "class Transformer:\n def peakmem_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:75", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "c9e62449ea399590080c790df85e63df815e88ceaa029196f9ea925d3acfecd7"}, "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit", "number": 0, "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:75", "timeout": 500, "type": "time", "unit": "seconds", "version": "48d290a4fd2b0a9ecdd1a7add3b7e7b231d8df63e32889758ec0bbd8c1cb37ef", "warmup_time": 1}, "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform": {"code": "class Transformer:\n def time_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform", "number": 0, "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:75", "timeout": 500, "type": "time", "unit": "seconds", "version": "3ac7bfb8060c67e6dd13c37f1901d3f4274b8b0edfaf3d6a575d4e20ecbaf45e", "warmup_time": 1}, "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:75", "timeout": 500, "type": "track", "unit": "unit", "version": "a0774d6e8f922842e4b916076deab0ed00f152a84632f732cec174d5d619192f"}, "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:75", "timeout": 500, "type": "track", "unit": "unit", "version": "13436574eaa40a2dd7b58fbef029cd2171941b963cec765dff95a1889f6a157a"}, "decomposition.PCABenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.PCABenchmark.peakmem_fit", "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "setup_cache_key": "decomposition:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "1dc803fc882e472d9bc70274b900eb03304281cd2dff33ec3e3c039fffbb74a4"}, "decomposition.PCABenchmark.peakmem_transform": {"code": "class Transformer:\n def peakmem_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.PCABenchmark.peakmem_transform", "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "setup_cache_key": "decomposition:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "2b31c7c4510aca17a679729f995ba0b7d6548de119b989f414876912bc7851ff"}, "decomposition.PCABenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.PCABenchmark.time_fit", "number": 0, "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "4a753451bb0c872008db51c421599cf8badfcb691aab39aaa7822dad561241dc", "warmup_time": 1}, "decomposition.PCABenchmark.time_transform": {"code": "class Transformer:\n def time_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.PCABenchmark.time_transform", "number": 0, "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "1f73bed6685d54963e63f4de9713d472d0ab242d57c6a0cfa54fac7d1e1e83ef", "warmup_time": 1}, "decomposition.PCABenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.PCABenchmark.track_test_score", "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "setup_cache_key": "decomposition:16", "timeout": 500, "type": "track", "unit": "unit", "version": "2bf9b85b93e81f43bf6e2e900a8ef13fb83b9b9298c32d0808bda654eb57c0c3"}, "decomposition.PCABenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.PCABenchmark.track_train_score", "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "setup_cache_key": "decomposition:16", "timeout": 500, "type": "track", "unit": "unit", "version": "16881c7fae4abaa9923123fc258e6542b0b3aa0c232d2db206548668bced23bb"}, "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "ensemble:64", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "0bed7eba4859779600e1b1cb03539724eddad1419ad1332e897185f93bd3d6df"}, "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "ensemble:64", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "5f65eed561196ec366996fc83d2258f891bbe9608480b00948108fa794a3c81e"}, "ensemble.GradientBoostingClassifierBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.GradientBoostingClassifierBenchmark.time_fit", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:64", "timeout": 500, "type": "time", "unit": "seconds", "version": "5702f67868717f5884d82ed22b8940f7ff2b626a2b46e2a4b6e1173c83db484f", "warmup_time": 1}, "ensemble.GradientBoostingClassifierBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.GradientBoostingClassifierBenchmark.time_predict", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:64", "timeout": 500, "type": "time", "unit": "seconds", "version": "17e3a4098ef2254174162a060b1286418984a4be5438aefd71301bf6a8f4c13d", "warmup_time": 1}, "ensemble.GradientBoostingClassifierBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.GradientBoostingClassifierBenchmark.track_test_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "ensemble:64", "timeout": 500, "type": "track", "unit": "unit", "version": "55092be1f965aa51752829bda24b944bdb1222a6b8e5fdf0d4026c9580953dea"}, "ensemble.GradientBoostingClassifierBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.GradientBoostingClassifierBenchmark.track_train_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "ensemble:64", "timeout": 500, "type": "track", "unit": "unit", "version": "cd78924c15421dcfc8b45a7d26a8b035a1e441c45612ee6ae169b9155e5a631b"}, "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit", "param_names": [], "params": [], "setup_cache_key": "ensemble:103", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "733ac3d039d12bcb9c7f00c745fad3c3723c29f21f67e444aabac276cbc3a916"}, "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict", "param_names": [], "params": [], "setup_cache_key": "ensemble:103", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "ef8fbc52879ef0add38e7cec975a52bd207c7003e688e265dcc4839b0bcaa3a8"}, "ensemble.HistGradientBoostingClassifierBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.HistGradientBoostingClassifierBenchmark.time_fit", "number": 0, "param_names": [], "params": [], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:103", "timeout": 500, "type": "time", "unit": "seconds", "version": "6840b9adeccbde7fc736aae2aa37f9b118d3fa9a78f2e0b2f0a4f09503e1a48d", "warmup_time": 1}, "ensemble.HistGradientBoostingClassifierBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.HistGradientBoostingClassifierBenchmark.time_predict", "number": 0, "param_names": [], "params": [], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:103", "timeout": 500, "type": "time", "unit": "seconds", "version": "ce65e5d6c62eebe1e73935285f56bc6c7ecebde97fb73fb4b9370c9b5979288a", "warmup_time": 1}, "ensemble.HistGradientBoostingClassifierBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.HistGradientBoostingClassifierBenchmark.track_test_score", "param_names": [], "params": [], "setup_cache_key": "ensemble:103", "timeout": 500, "type": "track", "unit": "unit", "version": "8c9a915f4dd669a61ceb38728602e43f84a976ebb06628f8026837eb7a5d30f6"}, "ensemble.HistGradientBoostingClassifierBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.HistGradientBoostingClassifierBenchmark.track_train_score", "param_names": [], "params": [], "setup_cache_key": "ensemble:103", "timeout": 500, "type": "track", "unit": "unit", "version": "43f6c225874e5193533ad56bdd398f471c7caa0f0f8c9a8ebb5486e10a2bec7f"}, "ensemble.RandomForestClassifierBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit", "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "setup_cache_key": "ensemble:24", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "14ca8ab81b54b4f2775c94fd794a13b049f48b9927979b964b90acc22ebf08a8"}, "ensemble.RandomForestClassifierBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict", "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "setup_cache_key": "ensemble:24", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "3febfd0d8977731921e7d366e6a585c8e405c0520f9a94415b96c6c334ed1c2f"}, "ensemble.RandomForestClassifierBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.RandomForestClassifierBenchmark.time_fit", "number": 0, "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:24", "timeout": 500, "type": "time", "unit": "seconds", "version": "7f77f2ea22b57af3ff27a86843c654c08e6aa926896f2c421666fd31d95ce65f", "warmup_time": 1}, "ensemble.RandomForestClassifierBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.RandomForestClassifierBenchmark.time_predict", "number": 0, "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:24", "timeout": 500, "type": "time", "unit": "seconds", "version": "6a93ee4dfb1d21e994eb8d7568e75ee99e0f416c9711bb2b45d1c022a27f0746", "warmup_time": 1}, "ensemble.RandomForestClassifierBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.RandomForestClassifierBenchmark.track_test_score", "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "setup_cache_key": "ensemble:24", "timeout": 500, "type": "track", "unit": "unit", "version": "a3b01d5f39647a3a6d6bfac31a005a5fdc82ad531a1b71f249ae2f4e98dc44c9"}, "ensemble.RandomForestClassifierBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.RandomForestClassifierBenchmark.track_train_score", "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "setup_cache_key": "ensemble:24", "timeout": 500, "type": "track", "unit": "unit", "version": "42daa18fec647c7415a78ff56b84cf07b2253222c89f24baf5f12238463b9400"}, "linear_model.ElasticNetBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.ElasticNetBenchmark.peakmem_fit", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:187", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "aeb53df9e9543a762cf297b5697780eafb3cfbf2a7e750ad0f079ea50ff3d051"}, "linear_model.ElasticNetBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.ElasticNetBenchmark.peakmem_predict", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:187", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "27f5ef6022a3a4cdd5a0854b9428349a5e461bf638a76337760251639c9d7f02"}, "linear_model.ElasticNetBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.ElasticNetBenchmark.time_fit", "number": 0, "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:187", "timeout": 500, "type": "time", "unit": "seconds", "version": "02947c3221cd53cf645dab6e61c787646637d66474795a722ec537ff85976c8c", "warmup_time": 1}, "linear_model.ElasticNetBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.ElasticNetBenchmark.time_predict", "number": 0, "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:187", "timeout": 500, "type": "time", "unit": "seconds", "version": "4140a00f540d4dea5268a3813730d6fbb270e40b74285dbf046b3e26069f1287", "warmup_time": 1}, "linear_model.ElasticNetBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.ElasticNetBenchmark.track_test_score", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:187", "timeout": 500, "type": "track", "unit": "unit", "version": "1c0c2170cd23de65b973498cfc8dff584d9983a7513d2ead27d49594b092a280"}, "linear_model.ElasticNetBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.ElasticNetBenchmark.track_train_score", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:187", "timeout": 500, "type": "track", "unit": "unit", "version": "6cff911c1163f327c86117f3dc306d62cdba87d9ea8068cc68977b61d151da78"}, "linear_model.LassoBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LassoBenchmark.peakmem_fit", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:228", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "8fa5824a898ff683065f60683a1805ae55dfdde209f22eb520e3dddac3b02688"}, "linear_model.LassoBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LassoBenchmark.peakmem_predict", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:228", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "2fd8dcd052ba7edddc85213c847b8fd149f36b0b9c0b058b88adae232e1fe0c6"}, "linear_model.LassoBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LassoBenchmark.time_fit", "number": 0, "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:228", "timeout": 500, "type": "time", "unit": "seconds", "version": "d0f2ce5dce5564f0fc096b1e4ee47c583962a62baf6a13edf150b4edaf353e05", "warmup_time": 1}, "linear_model.LassoBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LassoBenchmark.time_predict", "number": 0, "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:228", "timeout": 500, "type": "time", "unit": "seconds", "version": "9adfa14dab87a3a8a4de49d179ab5891f08045e1b81194ae39643622cb6487c9", "warmup_time": 1}, "linear_model.LassoBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LassoBenchmark.track_test_score", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:228", "timeout": 500, "type": "track", "unit": "unit", "version": "b56564a7b1756eeff8bbe981fa28bfb58f992c09069c2672ae87e637ba91f565"}, "linear_model.LassoBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LassoBenchmark.track_train_score", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:228", "timeout": 500, "type": "track", "unit": "unit", "version": "97c0e5ecdddd2ee7c31046ec01b6d29119975ffd6774712a778a26f8499350c4"}, "linear_model.LinearRegressionBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LinearRegressionBenchmark.peakmem_fit", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:119", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "a905fac8878f96b0ccc05296ca1cbb10654937aa04579453c79a4255ec7865f1"}, "linear_model.LinearRegressionBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LinearRegressionBenchmark.peakmem_predict", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:119", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "759535a8913b60467ef240fed4181399ff149efa33bea0eb69eed231df3f8876"}, "linear_model.LinearRegressionBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LinearRegressionBenchmark.time_fit", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:119", "timeout": 500, "type": "time", "unit": "seconds", "version": "e5dbbebbcad57689afbefadad2fb87cb71161a32a9d6caa162975a5b419f0f97", "warmup_time": 1}, "linear_model.LinearRegressionBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LinearRegressionBenchmark.time_predict", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:119", "timeout": 500, "type": "time", "unit": "seconds", "version": "ba279c28dffebbb04b7b173dee9e976b48b05ffbada322dd53d9a2de22ff70f6", "warmup_time": 1}, "linear_model.LinearRegressionBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LinearRegressionBenchmark.track_test_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:119", "timeout": 500, "type": "track", "unit": "unit", "version": "0641fe07389de5e5b9811f51f186e4a4a96a856eb50c8810c62734a593513594"}, "linear_model.LinearRegressionBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LinearRegressionBenchmark.track_train_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:119", "timeout": 500, "type": "track", "unit": "unit", "version": "5853e8435e7eba58f2264852c35444debdedaa05b29cccd9fef895ce848a5f06"}, "linear_model.LogisticRegressionBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "setup_cache_key": "linear_model:28", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "3b211361ab927e53d5697c6b9e81013a7575a9ce103d21adeb68544ea7a4e5dc"}, "linear_model.LogisticRegressionBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "setup_cache_key": "linear_model:28", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "be6101aa74d4f94ec846334788b859094ed4b1d36ca92bf7d693b3043a8d39da"}, "linear_model.LogisticRegressionBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LogisticRegressionBenchmark.time_fit", "number": 0, "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:28", "timeout": 500, "type": "time", "unit": "seconds", "version": "7cd42b119dd9bf6c8bf33ee70890f7ebaf0b159e0c0c8cd5b299c3f632725f21", "warmup_time": 1}, "linear_model.LogisticRegressionBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LogisticRegressionBenchmark.time_predict", "number": 0, "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:28", "timeout": 500, "type": "time", "unit": "seconds", "version": "b9dd34b6a7b894f6afbd6e27f4d0cfe829c1b0e4af4f7203e56269b873ee049b", "warmup_time": 1}, "linear_model.LogisticRegressionBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LogisticRegressionBenchmark.track_test_score", "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "setup_cache_key": "linear_model:28", "timeout": 500, "type": "track", "unit": "unit", "version": "37e537f82f54da1d89003018c8370da6ac290d672b6343a457ee49dd444e3c9f"}, "linear_model.LogisticRegressionBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LogisticRegressionBenchmark.track_train_score", "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "setup_cache_key": "linear_model:28", "timeout": 500, "type": "track", "unit": "unit", "version": "5647f2df8db098461a973d60cb900515f403287ed3e109a99151c94309e568f1"}, "linear_model.RidgeBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.RidgeBenchmark.peakmem_fit", "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "setup_cache_key": "linear_model:78", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "d06a93be5cf39a0df663d696943713376c4ba4abb2568ebc0bc97fd2a2fd5173"}, "linear_model.RidgeBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.RidgeBenchmark.peakmem_predict", "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "setup_cache_key": "linear_model:78", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "24e4dc55ce8e6b9311d26ca2936364cad3ddb0b8827b656a81886db508e69866"}, "linear_model.RidgeBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.RidgeBenchmark.time_fit", "number": 0, "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:78", "timeout": 500, "type": "time", "unit": "seconds", "version": "6ebbadd5cfeeb543e69ca73d777ab88bff49391965e0c0e3270868f1fa6bb385", "warmup_time": 1}, "linear_model.RidgeBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.RidgeBenchmark.time_predict", "number": 0, "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:78", "timeout": 500, "type": "time", "unit": "seconds", "version": "f41e9813a5f8239fbb0ef5e81982549e297ff18f751b7e4b42982972851b7cd0", "warmup_time": 1}, "linear_model.RidgeBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.RidgeBenchmark.track_test_score", "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "setup_cache_key": "linear_model:78", "timeout": 500, "type": "track", "unit": "unit", "version": "663c821271fbdb18d0252832535191137787f37ad6d6397624c92edd96dc6f3f"}, "linear_model.RidgeBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.RidgeBenchmark.track_train_score", "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "setup_cache_key": "linear_model:78", "timeout": 500, "type": "track", "unit": "unit", "version": "92bfe13d8da10b255d1c72982a3a88f70985b864b39584e51a184ea88116f35d"}, "linear_model.SGDRegressorBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.SGDRegressorBenchmark.peakmem_fit", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:151", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "d81ea5fe5efd3e1ec085f0a2c66d712cfec7e2c4e03b19b7a50ab79dfd661f77"}, "linear_model.SGDRegressorBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.SGDRegressorBenchmark.peakmem_predict", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:151", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "cf12939ffeb2f97f86ada7e454920a994d254a98a02eac5e34ea687f8ec11ad0"}, "linear_model.SGDRegressorBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.SGDRegressorBenchmark.time_fit", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:151", "timeout": 500, "type": "time", "unit": "seconds", "version": "cc477ee1fcfc2e853f5113072b49c7dc80acf8f2e19f83518368e1efe8dd5374", "warmup_time": 1}, "linear_model.SGDRegressorBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.SGDRegressorBenchmark.time_predict", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:151", "timeout": 500, "type": "time", "unit": "seconds", "version": "fcd01e3604428cf2063cbbfe4e708974618533d55ec0784a787b8bb838a2ece9", "warmup_time": 1}, "linear_model.SGDRegressorBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.SGDRegressorBenchmark.track_test_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:151", "timeout": 500, "type": "track", "unit": "unit", "version": "5c184c0b957ec177b911999a0cc2cd3996407b726efe5d7adeaeddea222a16d0"}, "linear_model.SGDRegressorBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.SGDRegressorBenchmark.track_train_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:151", "timeout": 500, "type": "track", "unit": "unit", "version": "84040f29c546fcb4fb3fed1db35c198a88607a920f0d1aad43ae542738470257"}, "manifold.TSNEBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass TSNEBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "manifold.TSNEBenchmark.peakmem_fit", "param_names": ["method"], "params": [["'exact'", "'barnes_hut'"]], "setup_cache_key": "manifold:15", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "5b07ad9c3bf4af00ff4022361ced135ee0591fe9a613dddb484f0142685497c4"}, "manifold.TSNEBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass TSNEBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "manifold.TSNEBenchmark.time_fit", "number": 0, "param_names": ["method"], "params": [["'exact'", "'barnes_hut'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "manifold:15", "timeout": 500, "type": "time", "unit": "seconds", "version": "d7906ea0d1e8bee6103afdb924f0c5471c1c3e392feb7dbcc411b9e3f3535e6a", "warmup_time": 1}, "manifold.TSNEBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass TSNEBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "manifold.TSNEBenchmark.track_test_score", "param_names": ["method"], "params": [["'exact'", "'barnes_hut'"]], "setup_cache_key": "manifold:15", "timeout": 500, "type": "track", "unit": "unit", "version": "7c865f9e53f16c8492cb36db3b656646d6585227ebfbf097102fda1e83f5e953"}, "manifold.TSNEBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass TSNEBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "manifold.TSNEBenchmark.track_train_score", "param_names": ["method"], "params": [["'exact'", "'barnes_hut'"]], "setup_cache_key": "manifold:15", "timeout": 500, "type": "track", "unit": "unit", "version": "92a5fc587f972e63dad98657097b1bcd64a743dfce5f07b3e1847ed8b720d46d"}, "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances": {"code": "class PairwiseDistancesBenchmark:\n def peakmem_pairwise_distances(self, *args):\n pairwise_distances(self.X, **self.pdist_params)\n\n def setup(self, *params):\n representation, metric, n_jobs = params\n \n if representation == \"sparse\" and metric == \"correlation\":\n raise NotImplementedError\n \n if Benchmark.data_size == \"large\":\n if metric in (\"manhattan\", \"correlation\"):\n n_samples = 8000\n else:\n n_samples = 24000\n else:\n if metric in (\"manhattan\", \"correlation\"):\n n_samples = 4000\n else:\n n_samples = 12000\n \n data = _random_dataset(n_samples=n_samples, representation=representation)\n self.X, self.X_val, self.y, self.y_val = data\n \n self.pdist_params = {\"metric\": metric, \"n_jobs\": n_jobs}", "name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "param_names": ["representation", "metric", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'cosine'", "'euclidean'", "'manhattan'", "'correlation'"], ["1", "4"]], "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "f982061fc53163362f863b2455a1f2f660861c4a4357be712dcacab0682833db"}, "metrics.PairwiseDistancesBenchmark.time_pairwise_distances": {"code": "class PairwiseDistancesBenchmark:\n def time_pairwise_distances(self, *args):\n pairwise_distances(self.X, **self.pdist_params)\n\n def setup(self, *params):\n representation, metric, n_jobs = params\n \n if representation == \"sparse\" and metric == \"correlation\":\n raise NotImplementedError\n \n if Benchmark.data_size == \"large\":\n if metric in (\"manhattan\", \"correlation\"):\n n_samples = 8000\n else:\n n_samples = 24000\n else:\n if metric in (\"manhattan\", \"correlation\"):\n n_samples = 4000\n else:\n n_samples = 12000\n \n data = _random_dataset(n_samples=n_samples, representation=representation)\n self.X, self.X_val, self.y, self.y_val = data\n \n self.pdist_params = {\"metric\": metric, \"n_jobs\": n_jobs}", "min_run_count": 2, "name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "number": 0, "param_names": ["representation", "metric", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'cosine'", "'euclidean'", "'manhattan'", "'correlation'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "timeout": 500, "type": "time", "unit": "seconds", "version": "968c4646f4f823e76e062ccbbe50249793691ae13e472124d1ebd2642c86b5e0", "warmup_time": 1}, "model_selection.CrossValidationBenchmark.peakmem_crossval": {"code": "class CrossValidationBenchmark:\n def peakmem_crossval(self, *args):\n cross_val_score(self.clf, self.X, self.y, **self.cv_params)\n\n def setup(self, *params):\n (n_jobs,) = params\n \n data = _synth_classification_dataset(n_samples=50000, n_features=100)\n self.X, self.X_val, self.y, self.y_val = data\n \n self.clf = RandomForestClassifier(n_estimators=50, max_depth=10, random_state=0)\n \n cv = 16 if Benchmark.data_size == \"large\" else 4\n \n self.cv_params = {\"n_jobs\": n_jobs, \"cv\": cv}", "name": "model_selection.CrossValidationBenchmark.peakmem_crossval", "param_names": ["n_jobs"], "params": [["1", "4"]], "timeout": 20000, "type": "peakmemory", "unit": "bytes", "version": "4b6fc20c55d0bbbf2b9b56117a6725d0351eec991f183d04b136f1ce4552e0c7"}, "model_selection.CrossValidationBenchmark.time_crossval": {"code": "class CrossValidationBenchmark:\n def time_crossval(self, *args):\n cross_val_score(self.clf, self.X, self.y, **self.cv_params)\n\n def setup(self, *params):\n (n_jobs,) = params\n \n data = _synth_classification_dataset(n_samples=50000, n_features=100)\n self.X, self.X_val, self.y, self.y_val = data\n \n self.clf = RandomForestClassifier(n_estimators=50, max_depth=10, random_state=0)\n \n cv = 16 if Benchmark.data_size == \"large\" else 4\n \n self.cv_params = {\"n_jobs\": n_jobs, \"cv\": cv}", "min_run_count": 2, "name": "model_selection.CrossValidationBenchmark.time_crossval", "number": 0, "param_names": ["n_jobs"], "params": [["1", "4"]], "rounds": 1, "sample_time": 0.01, "timeout": 20000, "type": "time", "unit": "seconds", "version": "9959454181a0ddb22a0ce5727c352955d47bf0ce97d2189ff73d567981c64587", "warmup_time": 1}, "model_selection.CrossValidationBenchmark.track_crossval": {"code": "class CrossValidationBenchmark:\n def track_crossval(self, *args):\n return float(cross_val_score(self.clf, self.X, self.y, **self.cv_params).mean())\n\n def setup(self, *params):\n (n_jobs,) = params\n \n data = _synth_classification_dataset(n_samples=50000, n_features=100)\n self.X, self.X_val, self.y, self.y_val = data\n \n self.clf = RandomForestClassifier(n_estimators=50, max_depth=10, random_state=0)\n \n cv = 16 if Benchmark.data_size == \"large\" else 4\n \n self.cv_params = {\"n_jobs\": n_jobs, \"cv\": cv}", "name": "model_selection.CrossValidationBenchmark.track_crossval", "param_names": ["n_jobs"], "params": [["1", "4"]], "timeout": 20000, "type": "track", "unit": "unit", "version": "5e7e6b0e0116bbc68953414ce4e0eec203cc51c80a71d897dd599172b82aeedd"}, "model_selection.GridSearchBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "model_selection.GridSearchBenchmark.peakmem_fit", "param_names": ["n_jobs"], "params": [["1", "4"]], "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "peakmemory", "unit": "bytes", "version": "95b48fd99a9327cc7b96fbaf3fb68de0488e277098c5f71aa31f5bcc0af0aa35"}, "model_selection.GridSearchBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "model_selection.GridSearchBenchmark.peakmem_predict", "param_names": ["n_jobs"], "params": [["1", "4"]], "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "peakmemory", "unit": "bytes", "version": "c892cd859a96073eba53d60e549a73d8202c9d0e97f5469f5e0333d949ce8dce"}, "model_selection.GridSearchBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "model_selection.GridSearchBenchmark.time_fit", "number": 0, "param_names": ["n_jobs"], "params": [["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "time", "unit": "seconds", "version": "ce048ba169bd01fc98abe0f363fcaafc41dfc6d88ae4658795602e37fd0bd003", "warmup_time": 1}, "model_selection.GridSearchBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "model_selection.GridSearchBenchmark.time_predict", "number": 0, "param_names": ["n_jobs"], "params": [["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "time", "unit": "seconds", "version": "acfeae20f02fb4775c69f3a23452a495e43a2abb0e684954a33824913f37e3eb", "warmup_time": 1}, "model_selection.GridSearchBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "model_selection.GridSearchBenchmark.track_test_score", "param_names": ["n_jobs"], "params": [["1", "4"]], "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "track", "unit": "unit", "version": "ec63718f94ff0beda5889deafa3b1f1f3ff7750bf6254fce002cadda537bee4b"}, "model_selection.GridSearchBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "model_selection.GridSearchBenchmark.track_train_score", "param_names": ["n_jobs"], "params": [["1", "4"]], "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "track", "unit": "unit", "version": "51575cdf87b95c5096592cecfc1f386cff2b52230b19a7bd6b1afee2fb55910c"}, "neighbors.KNeighborsClassifierBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "setup_cache_key": "neighbors:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "66acb7f2ea52ea49f9a5239c437782b0ac7cd030f150166dff686727e06ae1f5"}, "neighbors.KNeighborsClassifierBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "setup_cache_key": "neighbors:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "e7fb64f5f61911736101d3ca625806937a6bb4fc75b64a8ed0c9be1f37e0f10f"}, "neighbors.KNeighborsClassifierBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "number": 0, "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "neighbors:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "455e6017e69db76a36673f135b8300f5288867804ae588240ef238340de7bc82", "warmup_time": 1}, "neighbors.KNeighborsClassifierBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "number": 0, "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "neighbors:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "6611e4000bd5b1d8935eb7407c10355bf476dfef925640b9a8445912b72c8183", "warmup_time": 1}, "neighbors.KNeighborsClassifierBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "setup_cache_key": "neighbors:16", "timeout": 500, "type": "track", "unit": "unit", "version": "95d25638754fb5c021b379d6f4f51868a7303bedb4868e52cac2a036eb0bc248"}, "neighbors.KNeighborsClassifierBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "setup_cache_key": "neighbors:16", "timeout": 500, "type": "track", "unit": "unit", "version": "1e1b6891a1563cf0c8ae446c751cfd6dec48cc2fcc4d0157f30a7189f05e938a"}, "svm.SVCBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "svm.SVCBenchmark.peakmem_fit", "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "setup_cache_key": "svm:14", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "b5099e172031e9a0f7b7706ec386c5bf36f9bd427f7d47274c66c6c39f5bf730"}, "svm.SVCBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "svm.SVCBenchmark.peakmem_predict", "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "setup_cache_key": "svm:14", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "4a6611919a2e5a6cbd1f6c211b23857b3912da5e1484da897bf70155d62b7980"}, "svm.SVCBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "svm.SVCBenchmark.time_fit", "number": 0, "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "svm:14", "timeout": 500, "type": "time", "unit": "seconds", "version": "60f69bb46f97b00f249209ee47574d1508b9e81a8ba3ec0a8a3a430eb6aa719d", "warmup_time": 1}, "svm.SVCBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "svm.SVCBenchmark.time_predict", "number": 0, "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "svm:14", "timeout": 500, "type": "time", "unit": "seconds", "version": "ab64f47e62b03803ca9ee0734d6a0734af8278b39121b069d9abdf86a8e79285", "warmup_time": 1}, "svm.SVCBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "svm.SVCBenchmark.track_test_score", "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "setup_cache_key": "svm:14", "timeout": 500, "type": "track", "unit": "unit", "version": "f04be6a642a0b71d7bb27a3b184c53cf61aa01dead2ec4bbc68bf22ea78b68b3"}, "svm.SVCBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "svm.SVCBenchmark.track_train_score", "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "setup_cache_key": "svm:14", "timeout": 500, "type": "track", "unit": "unit", "version": "30dfcaa0d1c48f402d28bf241f4c7c013ac533fbb528d470c427a34c237993f7"}}, "machines": {"sklearn-benchmark": {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "version": 1}}, "tags": {"0.10": 7904, "0.10-branching": 7872, "0.11": 9357, "0.11-beta": 9331, "0.11-branching": 9349, "0.12": 10436, "0.12-branching": 10413, "0.12.1": 10778, "0.13": 12373, "0.13-branching": 12368, "0.13.1": 12748, "0.14.1": 14725, "0.14a1": 14515, "0.15-branching": 17074, "0.15.0b1": 16940, "0.15.1": 17645, "0.16-branching": 19198, "0.16.0": 19375, "0.16.1": 19504, "0.16b1": 19199, "0.17-branching": 20502, "0.17.1": 21601, "0.17.1-1": 21602, "0.17b1": 20509, "0.18": 22393, "0.18.1": 22702, "0.18.2": 23197, "0.18rc": 22265, "0.18rc1": 22268, "0.18rc2": 22283, "0.19-branching": 23280, "0.19.1": 23768, "0.19.2": 24417, "0.20.0": 24809, "0.20.1": 25159, "0.20.2": 25261, "0.20.3": 25563, "0.20.4": 26284, "0.20rc1": 24644, "0.21.0": 25841, "0.21.1": 25874, "0.21.2": 25910, "0.21.3": 26278, "0.21b2": 25766, "0.21rc1": 25758, "0.21rc2": 25767, "0.22.1": 27063, "0.3": 745, "0.5": 1969, "0.5.rc": 1915, "0.5.rc2": 1917, "0.5.rc3": 1919, "0.6-rc": 2701, "0.6.0": 2711, "0.7": 3151, "0.7-branching": 3102, "0.7.1": 3212, "0.8": 4037, "0.8-branching": 3905, "0.8.1": 4684, "0.9": 6225, "0.9-branching": 6177, "1.0.1": 29997, "1.1.1": 31297, "1.3.1": 34030, "1.3.2": 34152, "sprint01": 1207, "0.2": 590, "0.1": 395, "0.2-beta": 587, "0.1-beta": 382, "debian/0.2+svn625-1": 646, "debian/0.3-1": 755, "debian/0.4-3": 1288, "debian/0.3-2": 811, "debian/0.3-3": 813, "debian/0.4-2": 1131, "debian/0.4-1": 1016, "debian/0.3-4": 826, "0.4": 998, "debian/0.5-1": 1977, "debian/0.6.0.dfsg-1": 2743, "debian/0.7.1.dfsg-1": 3289, "debian/0.7.1.dfsg-3": 3741, "debian/0.8.0.dfsg-1": 4054, "debian/0.8.1.dfsg-1": 4696, "debian/0.9.0.dfsg-1": 6511, "debian/0.10.0-1": 7919, "debian/0.11.0-1": 9369, "debian/0.11.0-2": 9799, "debian/0.12.0-1": 10457, "0.14": 14698, "0.15.0b2": 17075, "0.15.0": 17279, "0.15.2": 17934, "debian/0.16.1-2": 19920, "debian/0.17.0_b1-1": 20952, "debian/0.17.0_b1+git14-g4e6829c-1": 20955, "0.17": 21113, "debian/0.17.0-1": 21126, "debian/0.17.0-3": 21322, "debian/0.17.0-4": 21323, "0.19b1": 23283, "0.19b2": 23307, "0.19.0": 23480, "0.22rc1": 26820, "0.22rc2": 26881, "0.22rc2.post1": 26890, "0.22rc3": 26944, "0.22": 26953, "0.22.2": 27300, "0.22.2.post1": 27325, "0.23.0rc1": 27571, "0.23.0": 27604, "0.23.1": 27674, "0.23.2": 28086, "0.24.0rc1": 28501, "0.24.0": 28541, "0.24.1": 28625, "0.24.2": 29084, "1.0.rc1": 29586, "1.0.rc2": 29636, "1.0": 29733, "1.0.2": 30500, "1.1.0rc1": 31120, "1.1.0": 31184, "1.1.2": 31927, "1.1.3": 32291, "1.2.0rc1": 32454, "1.2.0": 32499, "1.2.1": 32770, "1.2.2": 32984, "1.3.0rc1": 33376, "1.3.0": 33504}, "pages": [["", "Grid view", "Display as a agrid"], ["summarylist", "List view", "Display as a list"], ["regressions", "Show regressions", "Display information about recent regressions"]]} \ No newline at end of file +{"project": "scikit-learn", "project_url": "scikit-learn.org/", "show_commit_url": "https://github.com/scikit-learn/scikit-learn/commit/", "hash_length": 8, "revision_to_hash": {"382": "e6989efd71a2adddd03979d1fe7a2e82e37ea51f", "395": "8ff9fc895bd6032636e3716f02773fdcd9cdd3d3", "587": "0e1faafec9871df73e875a0aadfcb67ec578c0e5", "590": "a40d325cec40da6cbcff8193a4ab4890823dfc76", "646": "ddc6d8f80dcf0a6cdd606efdefb89211a4dc7e9d", "745": "8a4bc2f03733e530591d6641f266a60670a373f1", "755": "8216797c4b1abca9dafd8de9d65472d32450b389", "811": "c7208c1a43335179ccddafc7748c1d7224e904fc", "813": "47890ac823314f1a9e2920dff7575850af56c273", "826": "b573fc0dcbfc2528807b5f0f8c0bc719c25d36f4", "998": "65d06f830ec6604b44d1a0510255868a8f762e3a", "1016": "9072aa593d76262fe445cf492ffac77e853501ea", "1131": "959e267898090e3c68ee118d5048afad124ff61d", "1207": "c83447b72c4f48ceb8249ea394ebf042618b8a2a", "1288": "f13dba15e3d56455c58867685ec554755a346c32", "1915": "d6b4444bbcc54a241cc955a5ceea80be15e7db2b", "1917": "60589710bd64e1fb2ede4d34d7fbb57e83892c86", "1919": "eba9984f735478d47c956ede42bdefd28aa6f9f6", "1969": "0f148e0011fb873bcd70cb3cc01690e7d621f670", "1977": "dc72677a9c13a656cda8be4b23cd897b56109b4b", "2701": "2c3d9e2fce5d2bae27e10657aa3c7ff45c39b190", "2711": "87741a7c65768464eb15f0976ed4bf6312795e7f", "2743": "03a85c19ac2854f2a33f613f87e81fd5f4560f55", "3102": "c07f9574c902b68744434d7b43f7394e0801d64e", "3151": "8a195624128da773c7d584d9352f65d8241cc92d", "3212": "897201083fd584a310cb8a2870704470dc28474a", "3289": "bdf3332f9694f8ecbdcf7ab0391989e24ac13f88", "3741": "5a1e1f48433ba867fb035b9dc31882f8d90f7744", "3905": "af6ab92b3bc0286e401218631859ee50f8be23f7", "4037": "f7c9f24511d9b32add23e75bbf0a2a6c223d932f", "4054": "8b2aaf069306d6b61b49a29d32123e69991c153b", "4684": "cf5c72eb9dc7696b5fac61466605b2860942946e", "4696": "3b48abd5fb0fa4f87c09f6b21d0d1f0e8b7873e4", "6177": "3e3872cde115550b75bb25c47c109b8bfd070eab", "6225": "3f1ea662ee1b1b08cee63cc31e4e3e36ec532208", "6511": "bfd36aa504078ce58f727f7f37e17349ab290e7d", "7872": "4533aa33daa35dd68c6d433b1d3560ff2b65b252", "7904": "34334f5ce6b1f166efda8652310133f9fc36ed04", "7919": "79749fd2939781e201191ef081143d8a575984e7", "9331": "34c2904a95a707c6e6148480a7e2c86a0f7ad86b", "9349": "73fdf6a9c982758be6da71a932ec4a3613eccbbf", "9357": "4ae44b0fe10b3ddf8390cfa8deae4dec45c40666", "9369": "7eb39fa0dc43ce485d3af2857c587811332eb148", "9799": "114822b1e18c9d7f887c58b8a3b2c279bdce6d35", "10413": "4bc8822c846de0d3b70d006ea32235d4375a575b", "10436": "0fede44fb39d691e873d58a4210452aa93c462a5", "10457": "b9ed384195df7b8d7824eac42f7b1bee58ef321c", "10778": "0dd2e39c1f7aec6830e4348fa63a04939252a0a1", "12368": "3e89aa5f42519d7f0230b99948553a8eb33dc1f4", "12373": "86e8b0d2a3533253a7082591f572d73897c02a2c", "12748": "8075887585b0449b6e87ee54c2ca4dbd56960e1e", "14515": "fc0b766ceca487504b040896124a3d809af2975b", "14698": "d13928cc0653f52de55e22118915b0c5bcba13d7", "14725": "34c4908369968dd0f77897ec9dd8c227e7545478", "16940": "bc8666f60f2c8c9ba16b30fbe0b342c3b94213e6", "17074": "68280fb4254b0781a66a1d2689708068799f0bbe", "17075": "b4e8b3ca4366901998c116540902d2687e0a5450", "17279": "518002955b0d6539f8f5e2710b9cefb178cc8ee2", "17645": "d4906939b1ef86657e6617d8fa078a0fbe0c2472", "17934": "2068ff2fd94abe4f14b0334eb4372a64b268f6b4", "19198": "4cc0235ec1ee654ea85cf465d280d33bcb1db20c", "19199": "09dc09a1e9d9088c2cb783c818980f5509d77a11", "19375": "df9f90cfa8795b6d85056f70177fb783d6ecafda", "19504": "bb39b493ef084a4f362d77163c2ca506790c38b6", "19920": "25082e522c90fa9184789f6bc450278b3e18fdda", "20502": "c0c2c737971b52e04b1f6516dfa1bfb05b30f4fd", "20509": "cd12906cabf3576a8c236a4128e959360037dde0", "20952": "918005fd5441650ae4a49b510bcabff69ae898bf", "20955": "b5383488c4b8b97b000585e61ed4e2178fa84d36", "21113": "da4f480a6adf5fed30a42500fe0e5a21c404ac2a", "21126": "82fb053536803f172def9f64e0d62151529173a0", "21322": "2999a2f544cd56575d940d7ab359819b392cccae", "21323": "3c546fd1226a895f68d317d2430daa71fc13e093", "21601": "ea042f1485d5fe45bcf2475c3070cab4e5ac3381", "21602": "51a765acfa4c5d1ec05fc4b406968ad233c75162", "22265": "4d9fab55b9e14e01a7d13344a2612ed802d0c113", "22268": "b687ab371d990373c4a599399172cf31d2f0c350", "22283": "cef2b62701f80ff50a37528b5337dd9a96f0069e", "22393": "38030a00a7f72a3528bd17f2345f34d1344d6d45", "22702": "a5ab948cbc366d705b1f8db8687c7162f51de22d", "23197": "759f4637f9f9471cf4218b9dffc00b464790485b", "23280": "36bc053a69ac5b9ba5a54cb2bd19adb33dcde50e", "23283": "62523372fc6331fc55df73a94d65bfa48c45c193", "23307": "83816c2a95e2ae3c4b3546912de4f4266e0c230f", "23480": "81ba62fe053d56e228ce097cbca91bc5de2e3f82", "23768": "b661a9c81930429cba4a56af291ce2bf8c59f8c9", "24417": "8c439fbe8c340389d7f9d99884180b2e7b21a79f", "24644": "eb6764936c9558553f7a7203a6aaa0ddc6497875", "24809": "f659f5539f9d36ebec4e1d98538919b55299bba4", "25159": "55bf5d93e5674f13a1134d93a11fd0cd11aabcd1", "25261": "7389dbac82d362f296dc2746f10e43ffa1615660", "25563": "7b136e92acf49d46251479b75c88cba632de1937", "25750": "ee986788cbd3256f0c36d2ddae155d8ca8f7be1c", "25758": "be2f62b2bfb40747a2dab20f29a341879b247a3c", "25766": "60eb00c72541b42697fa017fdfc74935299fc455", "25767": "93b19b04d3c81f9824b23e1b910126d51f3cd342", "25841": "a243d96336cb4f50ca3635b3062a273f3dc5183a", "25874": "b7b4d3e2f1a65bcb6d40431d3b61ed1d563c9dab", "25910": "e8602bc04e5c7ab32e6acb887b68172098f7f1e2", "26278": "1495f69242646d239d89a5713982946b8ffcf9d9", "26284": "bddd9257f39f190fec3d72872cff73c2b3cc2734", "26819": "db6c12fc117500a751799a3082d1503b65183920", "26820": "e36317b50d70453622ac6d0324a700816bad21c1", "26881": "d39134bc77d9f9a5a0316e21ee32ac3f9683da3d", "26890": "f1f765f476c3cb3e0a882324f8ed67763d76ed26", "26944": "0a56df6dbbe4f1a56cb11d132e43641d7358dd7e", "26953": "5f3c3f0378f2f30f3c4340bd9bf1e211e96d5c3c", "27063": "e5698bde9a8b719514bf39e6e5d58f90cfe5bc01", "27300": "4b7331eeb746b3facb4d70e1760c58ebe8b47f2e", "27325": "daefc22f832177dcbb690369058e0ca776944188", "27498": "a1261a7e18c19bb3dfc8d739a6512c6f671d9e79", "27571": "22a7d5bc722b0430908f202e3ea40aa2ba1a0361", "27604": "483cd3eaa3c636a57ebb0dc4765531183b274df0", "27674": "fd237278e895b42abe8d8d09105cbb82dc2cbba7", "27937": "91a0e4041e6a7ec3752b394956473503e87a5924", "28086": "0fb307bf39bbdacd6ed713c00724f8f871d60370", "28255": "d2cd2540418d3ff66b324ec18566dbe0b5991b40", "28261": "ab3dc9fdf31f35854b390168ac68fb304951305f", "28269": "2828a889bb96f3507ae0b38721d1e37b9f3e553c", "28272": "8b68ea165cb11625254d17c73603c4724d0b6d21", "28277": "74b632a1aa880a9c7f855599d16603626edf97fa", "28278": "28d84693b3855e9a1bf02b61392fb9f31055e897", "28284": "54ce4222694819ad52d544ce5cba5da274c34ab7", "28288": "bc39e62e02b9de82c2a266bb47beac4687843b51", "28291": "df61e9ed98b0777cc0962be6e2d161f4c30110fd", "28296": "13bccedeb02fa650a247a8ab6420bf9d44df3424", "28302": "7ed972193590c2a11839e15db87fa4818089de1a", "28306": "21121f50997dba43fffbfecb2f672431cf708363", "28308": "3bb138f87964dde5f25846f4380afba012cf26bc", "28311": "aa4a10dbfaee9fd52af06f0f0c8e8ae77f243ef6", "28314": "f35457f1fc3282d9efa21a6dc0bfe5a5e8a2f40f", "28320": "58451568d3b44ba632d708add02f9c30f356570a", "28326": "f2635e27894e6fc8c15b13284d3b277dfde65d71", "28333": "3b334c5b257465c5253b5a714eda7b34bc046b45", "28339": "193670c2a17c6a76f852e21cfafb954d195c9d29", "28340": "e6555decf8a72958d26d499deb17aabca41a562a", "28345": "fdb9233f72caec3d3f9720e073b2efdc141847ff", "28347": "1f217f33a25e6033bd0160ee22695186e12e7744", "28357": "cd673475bde70e87255ccd9b6f35687ce59b4b67", "28360": "6ca9eab67e1054a1f9508dfa286e0542c8bab5e3", "28361": "5654da026b7f1186b3a840d1cb140b6598b0af61", "28365": "5d5329c473791c90ebc58b4a18a923d1e6c216b9", "28367": "160debe468890e1dd90b610d5505eb118481cbcf", "28371": "d933c20befea779f9bfd35b4d85adaed9c30d684", "28373": "28f61efad3c4ce6536176978aef0fc857a35ff7b", "28376": "f1111be2fa9899a610843c36d203b0fab02f16c3", "28377": "547feabbb02de7da88bbc692e7b81419e373a0cb", "28381": "dccaf4c867c5ba254b1bd576101d30df40c00760", "28390": "aad222316754a072a893c5e735d4f3f6bd792725", "28392": "8471c8389d794309b0b62a353e3af903acd48223", "28396": "38a50f4c7b429dffeb94ed5abb428da06d0ba859", "28397": "fb67c7bb00f4d68ecbc65e8c46af5372442274cd", "28404": "a2728ac8d4dbc241a997899da61cb0fbf4eec96c", "28413": "4d7e61159db3fb59c474674b3d9f9c656d310e49", "28416": "51acc9dda812efca3c28d97ddc380c421c4949db", "28417": "f0e9d298be351eda7eb7302d6e673b097ae79831", "28418": "b5d63e34746ec273c1cbc5992a0477198a22f8be", "28426": "7db70d5b7988e069088f9956a28f1039e799b709", "28428": "b3806f77895d1146e83fbfdd60c6be43d4a7c144", "28429": "f77fb7265ff9425efb355890107d31012b2c8f33", "28435": "8479a74af207d857da4188b75375ce9d24c7ef90", "28439": "f650d9420bc75e70369fd8c5c96f965b58c0b1d0", "28443": "5a8bbf0195236b2e85217f90c363e5e7f975f157", "28449": "84bd4e29680a9a95ca01143a6ba79a42bc6887ef", "28450": "ffcb869d4b4fc2609b123ac7d089d00791c30f5f", "28452": "b4453f126f34447967f52996039d11b0d2fa0090", "28454": "a85430acdd49b7a63a4de110ee437d092d460d70", "28460": "2f09bbb7eb2fffdffcca3667b8fc38990d3b0893", "28462": "5a09d87da357660f8d16abc2eb424c67db5710c5", "28468": "5fb02bb7bfed1a5edbe12ce942bb77cacde8180b", "28469": "35320845c24ee58a21a99a2df044084e0e65f3a4", "28474": "63d2bbf1ef187d026641514cf511648cedf94701", "28476": "9d394c2daab6df104cef115ebd69f802cc327347", "28481": "eaa45c86f74c41828a92db4d4da2eee643cbda02", "28485": "da562b4fa58bdce4a7f3470f733f33d728747a66", "28487": "fa5f1d5fe3e9a354b32a27a0a24cecef7babebb5", "28495": "59f41f03755fa28495f514a795e19154c0273e35", "28497": "255718b4ad9a3490bc99c992d467f85737bd1291", "28499": "e21319fee78d75e47cacb747aa40b5621f5b04cd", "28501": "2c1719e68e243c71c32c98958cf270a49e7a521f", "28502": "7cb6b8fde70bd12501e85be8102c46b8ca48405f", "28505": "4773f3e39d788e734378f32064cf2e5629fbc7aa", "28506": "c9677d6a7d42aa7162a4c448284b8db1cabde0b0", "28507": "8ebb614a8dc09c7baccb45c6a2cd7d087d8e2ed6", "28510": "0937b4ab48136eb161ead4abd4806d0708b1bb4c", "28516": "95128d3e6d9231703517c732dc73ca8c18adb9d0", "28520": "d304331b450344e4660550b15d8174b15fb616c7", "28524": "be4f8a509f1382a9bbd24194bcfd19c6563fcf31", "28527": "2218ec46227c92301ac6837c4a8ae9b8dc5d3960", "28529": "54375d24a423d77fc5fac1071643a588fc98e818", "28532": "6af03a525c929312f26986f68d3866c217a6838b", "28536": "a92ec1b7582b14fc20e57ffe0c9aa2a00f637766", "28541": "45a817933ef51a24f0c5863c1026b4fe664b26fa", "28547": "6b4f82433dc2f219dbff7fe8fa42c10b72379be6", "28550": "5946f8bfed039540c7527a06f2e6e9f1fb2335c3", "28551": "def0e68085a4339490325dcbfc79143f21ca001e", "28554": "e325bf760f55fb1095a66f1223af2cd396685b2f", "28557": "dfc5e16066b3a3bbf34238cc0f67639d0965f1a8", "28561": "cbfe0ede80beca86750ab8113f17c18c8c8042ce", "28565": "266a11b2e17cf86effefe7b498b61ca31217ad31", "28566": "1e46db669318fe20458d7cf135f6107e19e90970", "28567": "34de1b9b2122783601b245450a1885d18558ac81", "28572": "aa1918cecff1161c36fcf06fa0fe4d1c69ece701", "28575": "be4c1d1fee6ee3ec40935283f9e1ab22ebce27cf", "28580": "0e546ebe5b5a97283ce03f915a83f0d2651394e0", "28582": "9b2a3e8ba50804e5cd1e4302097e86aebd2e8464", "28584": "5a63f903ff1d45084c4fd41f241bf5dfdd067680", "28585": "1fca00b0b46e89956f76e118581a4176888344ab", "28588": "28efdcc5a646fbb8da2456a0f4b8ce7968432242", "28625": "c6512929fbee7232949c0f18cfb28cf3b5959df9", "28629": "e4ae68f09a258d9578f640ff74ca6e209ec37dba", "28631": "9183486463c1df3b5b3c7e2357e17533bdd36573", "28633": "364b1e3e13a48446f86e4682bbf09ba4f010903d", "28639": "8c6a045e46abe94e43a971d4f8042728addfd6a7", "28644": "0f0eb522903431b07f6e267b8b0d42ef24659cbf", "28646": "6f32544c51b43d122dfbed8feff5cd2887bcac80", "28653": "e449f9f1be7dcb937ace1327a4b0c6728afafafa", "28659": "0aee596bb32136df8c68371d696770251c7d14a0", "28663": "c86076fbecaac1f6f5f068a5332871f5dd0f8451", "28667": "ff2e52da0c09e8cb2d9a1b62bd4c3ea481187308", "28670": "b94332434d0117e3d86407560a206d1c7bee1c81", "28673": "38e6022e24e1a3c91f932fec87302ffc0610651b", "28674": "88be2abb7b7f7450dc569e0065e672a0676e4130", "28687": "94b81ab2e7f9b0170b2d6ba6d84c1cc913367d8b", "28688": "50d3aaad36fa83f5d43e8177838726dd08f0526b", "28695": "74a37de119d2c7c9ea1cce673c2ee207541a55d2", "28696": "819c43cc7a1d7efab855e982a91e15be7aec7db1", "28697": "23d8761615d0417eef5f52cc796518e44d41ca2a", "28702": "d6bd7bee8799ea41c456c36a8ccf7780105615e8", "28706": "94337993ef1a29146c67d7e4a51e3053a79e92b7", "28712": "86bc6c9858dd1660f5762003a45733f50fc7a748", "28715": "5403e9fdaee6d4982c887ce2ae9a62ccd3955fbb", "28720": "4aff3857bceb1e42af5ff304140bd4d5b7e74e67", "28727": "6959532d4e43f4434993c027c7b2df09ade942ad", "28734": "dac560551c5767d9a8608f86e3f253e706026189", "28737": "b251f3f818e8d3cdb7ef843006d19da87755d444", "28740": "4d60a815d84531ba91bf097e9c814460113a7b72", "28748": "e9c6fcaa17b983858400465fd39a2616c980c3db", "28751": "b5e55f79fdfcb0f41f0cfb279e54a123822bca43", "28753": "70c6ac9d04c396faaf604c2fd1d3945f25e4d6d4", "28761": "26c5530e792c1319ddd3335e23d1f36cf90f6c3d", "28764": "e23dd851476ef54c2153d6178500a3e2345f95b4", "28767": "638b7689bbbfae4bcc4592c6f8a43ce86b571f0b", "28775": "94abe05b4b96de2ca30d998fb9adb2fbd3eb1bde", "28779": "15c2c72e27c6ea18566f4e786506c7a3aef8a5de", "28782": "72db93cc40884f42e05e4290d6ab63713d0075c9", "28786": "28ee486b44f8e7e6440f3439e7315ba1e6d35e43", "28789": "1045d16ec13b1cab7878e7555538573d1884aad3", "28790": "42e90e9ba28fb37c2c9bd3e8aed1ac2387f1d5d5", "28791": "f2773e840a0fcc9dd673cdd0da82dc43299a713b", "28792": "ae3d955c90d03479d4b6a8a3b359fba10826dc2a", "28794": "4beb0c27fc0439c12dad244fe4063e96f8983a52", "28797": "6f180d79f58b42a3fa06055c489b1edf857399ff", "28801": "15fd026963be233d37752f322b5dd484c58e09a8", "28802": "f4e692c0876425ef6afb6f514b54696f3e071c35", "28804": "0c74b8b7d5cdb60dc3a3240cdb36af40b9f40288", "28808": "302106bcac4476ecdd76b8c03fddb454edbcad96", "28811": "b7b510f9dbc87500e79301873852c6247c440a3e", "28817": "04f84c6d082864c208682d27256ff74b7b488734", "28820": "0d7d46f3bef0a2f943ee321f0f979ced165e0477", "28827": "266400e60ddc0bdba1f0de02ed49f45893e5647c", "28829": "3e45aeef901871b84ce59709e62f3d2245463cd8", "28834": "81102146e35c81d7aab16d448f1c2b66d8a67ed9", "28840": "114616d9f6ce9eba7c1aacd3d4a254f868010e25", "28841": "4dfdfb4e1bb3719628753a4ece995a1b2fa5312a", "28851": "f0576399d9cfb41c1f3cd4a0a2332578b1c0b573", "28853": "f47926999d35686ff2190c3940c82d7cc7f3e691", "28855": "c957eb37b5988e6e2a4692c1356e8689294404c5", "28859": "9cfacf1540a991461b91617c779c69753a1ee4c0", "28861": "36c635b77f9744b627248f96f15f3e73e97d3571", "28867": "132627e28b5be807b1e4b7d58bedf42b529d7800", "28878": "3ff1267a7b74259dd0f0fdaf7da88b02e727e7c1", "28879": "b1d686d07559fb83040cb085b752d86ebbb9b3ba", "28883": "c09c654ed4d5833d73f557381f3d10f3d062e5d7", "28890": "7fa2e6e2734b590d96e62d5932c648a9c1002f34", "28893": "138da7ea911274f34d28849337c2768d7e3a7a96", "28895": "2c5ea4e6b3add57588fb35293b7dd25506c5fe06", "28898": "e1f879e8eed85c5018d888c9f87f168bc44085e1", "28905": "0df9efe2c1407f3fb887c22056452c791fd83dc9", "28914": "004b44d007408aa2db1fdaf4428990d0d7b7f85a", "28917": "a67b284f90299989c4cc03f848dc9cc1be57c623", "28920": "c88c89cffd87c34299ebb8db6192c973823bd827", "28922": "2641baf16d9de5191316745ec46120cc8b57a666", "28928": "e4bb9fa86b0df873ad750b6d59090843d9d23d50", "28936": "a45c0c99a38cffca6724cb8fd38b12edd4fb6b35", "29084": "15a949460dbf19e5e196b8ef48f9712b72a3b3c3", "29085": "a9cc0ed86fca1480acbd8aaf211f062ee2abd5b7", "29086": "9c3b402f0082cfc17da3ab9430a203ecc2ac4dfc", "29088": "4023a0f94bde429456f45b983c84c5f35475480f", "29090": "a9ce392f3a58da5caf5ac9bd287205e220082fc5", "29092": "0eb9ad73c53c8f3cc0ea03d33312035853bee29b", "29093": "de1262c35e2aa4ee062d050281ee576ce9e35c94", "29097": "2bd3a4db529d707a9862d69cc1ddbcbe7a6054b8", "29106": "847fc6a27431d96eaef926773608168e8edb9e12", "29108": "48ab1bf71aea9b7036108179e00e0b2e1c3fcf7e", "29109": "f6e6ad2d9e9172c55c778392b27b69c6af87bd98", "29110": "5073d692f04dea88d595252a6cc0382509b6947d", "29111": "d73822f84f2832dcc25f0ff58769f60871a78025", "29113": "053d2d1af477d9dc17e69162b9f2298c0fda5905", "29115": "ca6caa28ab92cbf75a3cc2a411d2a225abd9a4ce", "29119": "1ac047d29a43bd1556d5c90e40376340a08bc3a6", "29121": "c67518350f91072f9d37ed09c5ef7edf555b6cf6", "29123": "36a4dcafedbcbb112e1d96fd04e73ba922523bae", "29125": "aa898de885ed4861a03e4f79b28f92f70914643d", "29126": "5b7136f04068e7dcdf5ae8ec4aa729107ee905c0", "29128": "c1cc67dd06d31a9b110377afe0c94b0cd50848d5", "29131": "7c873713df056a9554dd545b0d5f0be93630219b", "29138": "c9d223ccc58e2569b8e67f1d0217dd57a93ec07f", "29142": "deda6e2a5a01ad22096862bded5f66e9578cc39e", "29146": "7bb3e22b3c454a59619a56c314be04b4b303e09a", "29156": "6850c04186b88e88e9c8cd6eb673721af806e3da", "29157": "5d25ce13ae0fa8f1f9e02d046d1820b6dcfd6155", "29164": "1038024a438e2bc76e7e48edde7b7ca732dc506b", "29180": "1cd282d600088d2547d827af72a99e036106417a", "29185": "038c5cd04558e572b6a4dea7383a515ff10090e5", "29189": "9a13bdfaf1a47188d2e1262f0308f317e6662e8d", "29190": "b5e5db4a43e9f79d877a0d88ba94392925981b31", "29203": "0eeebb1e3d59f739f6eb9319ceb254a8486493d5", "29215": "dc2b5875d0465e30fe9a8181a0e07d85d15e66f8", "29225": "0ad2b5b0a9fdc010ff92dd536b102e865ac3c512", "29227": "617ff6ef72f28b7964f2b7fbedaeff7b24d8c2f9", "29228": "bb6117b228e2940cada2627dce86b49d0662220c", "29229": "c3a3b1e602d819e0b2a7b90a344580902be7ce0e", "29231": "572c2cb1c8ebc5ccf5b16573b7199f67912ff87e", "29233": "bd966fb7e43691918669db4533488d7596c1cd69", "29235": "36cc933f41d5eba5df154db57d2597d5bf421024", "29240": "7b715111bff01e836fcd3413851381c6a1057ca4", "29245": "1e2c899aa94526c9e0e916f1fe2463ecd30a35f7", "29246": "509b9ffbca2f73e2724cf073ac564238fae60b4b", "29258": "2a67d88258264eb2b6dfad221be8f8d61684dcba", "29262": "3a57efe45ef7ad3b32f3c3e2813f65316391b668", "29279": "daae053f7e9afc1dac24ce9ecce87f1356b96b03", "29286": "bf7a60a6a217c85620844b083c3935235b3aa177", "29293": "0d343bb2d296ece7205f9e230d98e3ad68ac4472", "29294": "e4ef854d031854932b7165d55bfd04a400af6b85", "29295": "18eef9adf9a0f8995ea8aee0bc4a94afc7aa5698", "29296": "c871c062f1bfb10bcd2cf39c25d233fb614eeff4", "29313": "5a879f4a024d499c74da65f0343b535be4aa096e", "29318": "f2a6e109f7be6f0d554e44cb4cb48b41081dc259", "29319": "d66b42708a5912039740cd08f747229433e579b5", "29322": "f72f1df4b03f63a027e738f644958e062f294503", "29325": "5c499942e0ade18fc1abb9669bd04462256bee73", "29327": "ed3642014be412b0bda13d1ec756baeabb0dcbfe", "29328": "1bd007fe0d5758d48829ea339f06206261fb2477", "29340": "85b0b54285471fd3af5f27ac4d25a6508263a79a", "29344": "cd8201b7fbdf6876719b44ec0abac85a6da583d2", "29349": "f081f5829182529eb1ab666f79c9b917b0b07f09", "29364": "ded59b5713bcbfcaa27d7d9d1de704c96817870c", "29371": "cf286be4f3f5bb9b604efd068aaa87dc303bb4ac", "29376": "57daa2de792121a6a22556f978234192b778e308", "29381": "238451d55ed57c3d16bc42f6a74f5f0126a7c700", "29383": "b41cb296ff137f28c3d100298b507ccb9e63a3bb", "29387": "2844f592be6eba36d952a4a1ad68cc41e2845c27", "29401": "df20e8156fdc06a89ba85952b8b5a32b47ee9004", "29404": "01a28e962ad203b552bd968e5a3564d4b7e2155c", "29409": "4797222cc4547451df8ecdadf2ec29488703b593", "29414": "daec880bff4217f1dd05484ebfcd912377652873", "29415": "86476347b362c8f2f0b6bd5cc9dfcfcec979f07d", "29420": "6b2d5a973a0b35453bb163fda72930dc4791945e", "29421": "81165cabad383db2ff7fd856e467041eea9b55dc", "29425": "cdc486a91affd19b603e8090b46eb5ca262f3569", "29429": "f812e2a27619650463cb12d765f1b443b47c0828", "29435": "416eef462df1a9bbf8e99b91dac58324f8a3f498", "29443": "4b0d291fb30d057980a9bf64331c398f7c425fed", "29446": "5088a402253a275249dbd52fef97d8e58628d28a", "29453": "4b8cd880397f279200b8faf9c75df13801cb45b7", "29454": "73174161931ac283499aaae2e45ec4605c895ddc", "29455": "21eb4686c5a53401b10e815d2f08ef8f090283e1", "29457": "8cf87a30bbd5cbd6444c6f3ed380a3d2b5f67461", "29458": "e648c4cb919151161202130b2e4aea6413329900", "29469": "d6735f4851d828984a0517de954b9b88c74919fe", "29541": "fac31e727947ad53f2ed107f58a10b56b165cee7", "29548": "f46190846c5d8c0bd898d1447a2a07fc50fcee2a", "29550": "9061ff9e58425789338f68563df1bcfd386d93fc", "29551": "cb7271339e56631fe47a22e259c98716f14f6894", "29572": "c0e5d1bc746069e6087d499dffc707d94df09237", "29586": "c21491f05e9ac58ef4b4a7f0c3ec0e9c06b4a05a", "29591": "89d66b39a0949c01beee5eb9739e192b8bcac7bd", "29598": "40e1f895b172b9941fdcdefffd5a2aa8556ed227", "29609": "047cc2ec0cf71cd7233a7163a847b197e3a4acf6", "29611": "517b38ad30f36c6fe9eaca2c4a496ac1c63b3f50", "29621": "597df0ad17fa75d7a6832f71e7859fcb1925e29c", "29636": "e00e000c9a96b1f2173f352769d8c590ce6e0113", "29638": "f309ffb2a6c7638f25eda75873578c948a2bdecc", "29644": "5f6abe6f7d64fb5e1fa7dccc0aaf4ec2e217cdc4", "29648": "8fc351656a44789893bd8b092ea12fbbf5b803ca", "29652": "f71c0313142c4e5f2f35a0021c36075cf8dba611", "29656": "efa7f7c8753aa84b4b001d699aa6c70a2929813d", "29657": "6c566da8c99b4908a549aeb659cd4b1124bc2448", "29662": "6c068e2c75b551c72d3f551e68d7c5a76b6fd7a1", "29665": "47f888239c507358fc7bab7f832101db648b9461", "29667": "0d1e63366c6e361ba89b8588ccc26b01c47a5563", "29733": "9b033758ec681e8fd7433a8bb35d9777acd4f8ba", "29735": "2eabb45d3588bd0bb3422e1b3c2c6189268b3b1e", "29742": "f33fb0af65380e3360cfc9dd7f291ab59e2ef63b", "29750": "2e3c32dcc1e99ad753dff4a9aa26657073883158", "29753": "9cb4e761f530e7a0708059b1312921753d056cbe", "29757": "6d5774f6895aa84a8ec74762bcb29fc7e5173d41", "29761": "e7fb5b8c8dd2cd4d7ccd6f9f9ad6c1d206c43a33", "29765": "4b8888bf864322af1a1ae664d8d39c37b928ac6f", "29766": "d152b1e6e2a02e5bf725b41ecd63884d7d957cee", "29768": "23afd5d95c18915c55070cecaecf9f3030ae9bbb", "29776": "d3429c138a1eab162f3627e14c6ac26f49d59a16", "29783": "8ad7c3f02daae525ee83231fbd33fb65e8e05288", "29788": "8b18d4cbfc3a10ce85decec292d30470c69f40d7", "29789": "b2ee0f4ed1265a2147a6c470373de2990074fa23", "29790": "2f2364de6f6b61a24cefb8a18369f0811f721886", "29795": "682bd050be056e2104b4f9c2df4931bb642e7946", "29798": "57658ba4ba1a8bb00e8bcfa17cba028588ecf47f", "29805": "5f6e17c084c36e9eaee55a7e05f4b2f43be21a25", "29806": "47a49c51d14b7b648be6a4918c1441cb29c96a9e", "29807": "034ee98eae76f2fc5d9ab3b6e52740728821465d", "29808": "2ec028d2e8c34e332c851311e8cf330128081a1c", "29813": "a343963d961225be25468ca64b54896dcba48e87", "29815": "958ccc5bb1d43594eafe825e387e3e9876ac8893", "29828": "9b210ae8ffdc40e210f30f24656779ac690b899a", "29839": "e34b64c7ac57c9e6bfee3e26f27d6d74a9bd913a", "29844": "d4d5f8c7e02cfaced76757fbf38e21c5b28b67b0", "29858": "4c9bf8bbae7cd10baa754ba2bd5631329180fe09", "29865": "ec1248ae8af8e5fe53655f0269d5f4e178c21b70", "29997": "0d378913be6d7e485b792ea36e9268be31ed52d0", "29999": "8955057049c5c8cc5a7d8380e236f6a5efcf1c05", "30002": "f7ecaee36fbcf1847943e122504a4ab7c585bd90", "30010": "d4129527d3e86e34e898885ee8640e2c65900f47", "30013": "bd871537415a80b0505daabeaa8bfe4dd5f30e6d", "30023": "01551ad8db01230c1bb7ae94803f48e337f4db88", "30028": "d5e045fd600bf7f3edd984fe7f8599124a67f7f6", "30035": "8cfbc38ab8864b68f9a504f96857bb2e527c9bbb", "30046": "f8728dfc07af5bb47d97459b78c6729d76f076de", "30053": "9b605b498c6b1ac6b2713432d75d14854a2481ae", "30066": "74bf394b872d9ed9a91a949f04dbcf2239c558e7", "30068": "48e83df4509bb2ae1c1d74570a9efed7b61bdede", "30070": "8aa0ac006ce87cf8a7bf12c40380b14af6ae2a10", "30074": "f2231993675134ca7d01b1b8ebfd6d082372272e", "30076": "d63405f1bb6e4e6f56f59cb947a51ffd48cba895", "30077": "793e90b344aeee90432b47515410c5666097f0e6", "30078": "1b9de7b8b6a1a535b80505db1039ad19b3cc3738", "30085": "016df3326c48e0a78f9efb5871473bff4a09f0e3", "30086": "2368132b70559de2e890d7f16ec10f6247c9d5a2", "30096": "6077d52b706d118c0d9fb1e69c254bc67e15b078", "30104": "7bfa9ccd7c4a6d73bb2b0a99baf6f9515e681951", "30106": "00d7e59d1e4555f68c4e2bd005fa30048c2e3be5", "30112": "432ae47beeaf611547aafb69131834f151fe1136", "30116": "6cdffd860c49d30d3b9fa72c5fc1174e8eeaa35e", "30118": "248f6cf3156f6a48333b4074aac4c12e2c15155c", "30123": "a278f2a2ce49bdd55ccb73bb67e35b9c2ada12e7", "30128": "73d0b4f2d1aad5884738eeaac1aab2c3135fc471", "30135": "f8f77b4acca401904f6e7332bea55067f9d1e797", "30145": "bacc91cf1d4531bcc91aa60893fdf7df319485ec", "30155": "35af6dc808c8d317eb7017d1b16e271c9c8bba77", "30156": "b1a5d3c40ce0664978e41305cfd1e616a8d3dfd2", "30157": "832513a7fb6570c41f3c8bf4bf7cbaf110da300e", "30165": "7c7666c9b9f894e3220f52dfc98d95d658e042b0", "30174": "80ebe21ec280892df98a02d8fdd61cbf3988ccd6", "30179": "3e0f49b62339941722d0dfbcb90f5af0ad1b2e6c", "30185": "3f8868072c1eb7b37ade0a131db37303817ab5c4", "30189": "4035b63f7ff9437e389b720db45f73ef66566ce9", "30190": "b1202af3b379e698539a2719f2b1e28706ce5388", "30198": "5f3d1e57a91e7c89fe3485971188f1ecd335f2c1", "30202": "02b41de8fca096d92aea6a5336fce372b842c5c7", "30203": "77fbdd1c46c2931fb06b373786efd03da90d3e78", "30208": "63a1a31a17f9bd9cdf617b2cf04bfaf2f32f0a17", "30212": "01109213520eccbb9d5a51ed2930e7763c3386c4", "30213": "056f993b411c1fa5cf6a2ced8e51de03617b25b4", "30215": "39782b71b03d180bb2fe2ac321b6bab87a43746a", "30218": "dce9782a0d174d317c89ad52124348fa3bfb4e47", "30225": "845b1fac9e8bcfc146e7b38119ce6c500e00a10b", "30227": "f21f1d7539134fabc93e57309dd3a4717d00c7f3", "30233": "b84d67751753cd7ee81b3ede8d3d16951ddc4cef", "30235": "cece90e57c2b64e56367ddc1bad7edacd4f29e26", "30238": "2fc9187879424556726d9345a6656884fa9fbc20", "30244": "e5cc0b80714223c709d48b832e32fa73bae323a4", "30248": "3e460e8b7e4c6d9eb2041d793a339dddc000b3f3", "30254": "304a14783ffa4eaad738aede0e12a76ae44df076", "30259": "78a941aa73756595baff805fd390a0590262ac97", "30260": "c72ace8cd652309963ecdd6c01e33fa3c58c9161", "30500": "7e1e6d09bcc2eaeba98f7e737aac2ac782f0e5f1", "30501": "9aff4def9890819556e3d32c8ca6b2f27b528c22", "30502": "5dfa5d979a3acb87ba028d0e9e72e3e73bf1657f", "30506": "b242b9dd200cbb3f60247e523adae43a303d8122", "30507": "ed865d7a3363a92846d7955a9bdedae2ad29542e", "30510": "42a34e81a2efd64ddd7b40b433765e7c361cb51e", "30515": "585f4f11bca4c5a4cd2949ebd4ba9aecb9f3dc31", "30519": "5d86281723891c3dda755509f67a524da94ea07a", "30520": "1c24595c74e0bea246737b19f8fdfc8a1ffa2282", "30524": "26e2c38a961a27a9e53ce7814bf27f840510b237", "30525": "49588ff1e677d3d6fddf8798603a06f06fdb6e61", "30529": "ff09c8a579b116500deade618f93c4dc0d5750bd", "30533": "4e974e0d5e0b9e4aeaf83ab5b2f6381c5e122c6f", "30538": "7f61186cbcbc43cd6ccd717abd097f638b786984", "30542": "8d6217107f02d6f52d2f8c8908958fe82778c7cc", "30543": "9daed7f8970c25afaa54f671815afd75605acf26", "30544": "1d1aadd0711b87d2a11c80aad15df6f8cf156712", "30545": "0c65bbfe8ce816a181780d2a249c94dd653e115a", "30550": "ab08e4dba5f1f87b8c3395f32469a6ddb5e34f89", "30552": "9816b35d05e139f1fcc1a5541a1398205280d75a", "30556": "330881a21ca48c543cc8a67aa0d4e4c1dc1001ab", "30561": "08e02167843d857c0fb205479ae32183a887bac6", "30564": "6145cae3d1cefaeffcb49b3080233022bcd1368d", "30565": "cdf0d69c9c0cd2ce400dd79176ed4457a7730d67", "30577": "203caeae4c90331fdd7e087ee27b54a8541bfe03", "30581": "1e4ac040eef6bc8c43c77122bbfdd5d83cb8365a", "30586": "26e1930abf5ad637e44573a152dadbd45fb5db0b", "30593": "755d10a7fcfc44656bbed8d7f00f9e06e505732a", "30615": "254ea8c453cd2100ade07644648f1f00392611a6", "30621": "46d914349dd4027bdb1a69eed4d73694d0b37fad", "30622": "0dfaaadfe2d0e0b4fd9d2ba22a75b7b1b1903049", "30629": "b0067e0e7e0ae095592bc3a9a8cb7ba9e200c1be", "30635": "9f96d42e3966ec0ac778132bf1192ba36f413006", "30639": "581a66316af6b57e6d455b5517c543932f857f0b", "30640": "9f85c9d44965b764f40169ef2917e5f7a798684f", "30643": "fc05d2b1d9e815aabc9f1436a8dabd281d08b0e1", "30646": "77bc7f921c9039f917456d81b0a9db9926b987ab", "30647": "6440856fbb0e1c0a048316befbf6df4e0a5765c1", "30650": "b80138fccb025ec1f8944e1b17d08b5fc2e9d1cb", "30657": "34f4465466028ccb3f7c42d71d97f7158281d6ff", "30665": "bdb7db524a5cb584d975b3bb1823494bcd5eb92f", "30670": "6c09bab585acc708b099acf383fefe6ffe50ca89", "30675": "0cb06ea33ead6bc191e6721942606a6b17ecc01a", "30679": "f9d046766f590af3c181cb2d994ab1ea125d1216", "30694": "3786daf7dc5c301478d489b0756f90d0ac5d010f", "30704": "abbee570f31a91243c22b1892e42056bb915c056", "30708": "e11c4d21a4579f0d49f414a4b76e386f80f0f074", "30718": "111c78214cb92d8a21c95734c6dd0e76d5398db2", "30723": "26d218cfeb80908a52bbfc302dc5f43cef4b5181", "30729": "998e8f2068c7d9f43a30d997b63e4875688d0b1a", "30730": "5c7dac0131eb2318ccd4afad1e2e646e7b83b5ff", "30734": "691972a7cf04e7a8918b907556b4e9904f82bd0c", "30739": "e0ebc7839153da72e091f385ee4e6d4df51f96ef", "30744": "a1a55886a0f615b4e87659af489369a9e66e40bc", "30748": "70eebb992e8a799cbc3d7f1fbfddd104c0908c66", "30750": "34d39c7da61499c7a0e5a57dbb8b02e31a914ac0", "30754": "7a2a0f74ca7b9e452c94ee6de3146ef879dfe41c", "30761": "9ced5ec0b123bbe47179cffff02844ba659a752e", "30762": "c83c6fc83d504b08bd6aab4f12c45d10cf0e9ffa", "30777": "b19c748adb30d8ac1af94dc296dcd424d4631ccf", "30782": "578e3eb532d8ab5396d5579ff06e46604818e750", "30785": "269bdb94898b9944b10de2db6b17fffe7b69a432", "30787": "742d39ca38f713027091324c4555f9b4e1b9da05", "30794": "7d9f1cae7f49ff6bca4e474a4c9e8f4e7b88a357", "30804": "692225dd2cb5058bc006716270c1d48c59172f95", "30812": "d6984db4f2c8ff8c0b29413b40d53903f2123ce7", "30817": "5afd5e160bb731a0445c960fd94740080a44ebd7", "30821": "ee1b6d217f0566115dec706c6256fd81c4087833", "30838": "f6d37b85d551051ab26e04135db5e6db623dd955", "30849": "bbdb2eff9b877c0ae00ed9854099b92119504f62", "30861": "fb4dbfd837483ac3daf06dfc28871bfcfb65c4ab", "30868": "751c5cd05ff545c20ad0b09ac491c07f31e4cd56", "30872": "142e388fa004e3367fdfc0be4a194be0d0c61c8c", "30890": "0b2f4ead15a8b069222c4bd538499c9c739a8f96", "30904": "99262c06c02375ce9579638d0f37ee1ce61807c8", "30907": "7116165f493998cde7989a29458f36bdfb0a9ab5", "30908": "ee5a1b69d1dfa99635a10f0a5b54ec263cedf866", "30917": "2a4b40a0a46b1e6b1271a89fdb466d1c7dfae6ea", "30928": "26eedbd1f453435b7d8f62d151ba23c22a567d88", "30931": "e5736afb316038c43301d2c53ce39f9a89b64495", "30938": "f89a40bd92004368dee38ea76a1b9eaddaff4d7a", "30945": "cb547ae5d1484d6332ea7891ec7d7ac742342741", "30949": "5b901fe5734d1f3900bd8f13534718b007012c4a", "30955": "2c5058e0d6cc4f5c627d2ee256f4735fd5ba4a39", "30957": "d14fd82cf423c21ab6d01f7d0430083f9d7026be", "30967": "fab022e2edf98d745f2ceaf3048e0ca6bc3b86f1", "30974": "86c62cff7121b218f7bd7007bd6880e206561019", "30978": "7811a3a4789f5a252e99708e7bd45445f78839e4", "30987": "59428da95751fa92d46687850932f8f6ab1b4f3d", "30988": "b4da3b406379b241bf5e81d0f60bbcddd424625b", "30994": "dded6761c53a433a8f72b40aef33bf7c2f76e425", "30997": "9858fdd9a34a630499cf34c0b5c4900d6f81d55b", "31009": "41b8f84f1f1eb5930c0ec60598ca1748005a1f75", "31019": "adb47e7c142ce6d699cc5927925d448cb2c1ab91", "31031": "df692c03c1a6003878c6fc4d2f9f222d304dcee3", "31039": "bd9336db0c23b4bb8725cbea34fc9c43cdec70b2", "31040": "aeeac1c1d634dc80abc93fb30b3fe48e1d709b64", "31041": "e275d9df3da36352605f4e68b14593bf9f435c9b", "31120": "c987b5ca84610bf5251ea8fa33b48c5826942a0d", "31184": "16625450b58f555dc3955d223f0c3b64a5686984", "31297": "80598905e517759b4696c74ecc35c6e2eb508cff", "31927": "6cb2c52375a812ff509c00f4eed1da232e7a8932", "32088": "b4f51fd1569a0b90d56061f678f2f4fa7b04bf5e", "32090": "5436818d8bfc7e6499c07f4225aba377899a687d", "32101": "29f80b058fd037c8c4a22ad0638ca7d833aa264e", "32104": "f3f3a804d7386e80003655c44d0a9faa707a618f", "32112": "20bb279d1f7602acdba4c13853b3c7d086aaf8db", "32115": "53acd0fe52cb5d8c6f5a86a1fc1352809240b68d", "32116": "189d2f304c73a40dd2d2d38f6203ff9d41cbd48e", "32120": "ad91259f20529306efe445f5a1da4dccc8c81b5a", "32130": "ee5d4ce151c633499b02abc85a0cbb863f3254f8", "32131": "2f8b8e7f1aa628289b92cfc5bdfc7907688962b1", "32132": "15599753b63f10748ffb374aacd37dbb37806a37", "32138": "bfe68b4641cd918f9f4d9f1a60f2f3e27fd707c8", "32148": "ae943bd7a02fe6ad93df619cce61cbad1a694c57", "32152": "ae6bf39b310ed5bb46349c831a05f55bba921dcc", "32156": "0bf24792d69ebc2024821adafd63ee37d0110cd3", "32157": "b4f17015ceba5dde8b720cb03992cbe6186604dc", "32163": "257757755b1c2bea22f3b78da392df07b809788f", "32174": "b22f7fa552c03aa7f6b9b4d661470d0173f8db5d", "32181": "681ab94222a9ba5f7b39f768f0ab92873905541a", "32186": "21829b5ddb8f50292dd302fff5c9aad1c4b1998a", "32187": "d2c713bce62974f7a17aab3e556d0bf14eebab3c", "32193": "df626e43ac3c99da2aeb005709d77395bd717e6a", "32197": "0c22fa1da475531aa31b5c67f427b5e1461835b5", "32198": "14684bbae31918a394d61c75c23edee42d6c9761", "32204": "8694eb00f8a3c0dede331fe60c0415bfaafef631", "32213": "4ee3fdd85c8d78da24c166a4127e8bc7bc8dd469", "32218": "b0b7c154ae5691310d56ea6c738a6b14c6692224", "32220": "5ceb8a6a031ddff26a7ede413db1b53edb64166a", "32224": "93c7306836aef3cb62e3cc25efeeae1a8dc8bbde", "32241": "0c8820b6e4f9c49f55e96fcbb297073a887eb37b", "32249": "8610e14f8a9acd488253444b8e551fb3e0d60ef7", "32252": "625650fa69c312f6d9b712eb41baf33dac1be3de", "32256": "1dc23d7a1a798151a45ce1d72954821d61728411", "32259": "3e6a39a73c2ca39e073e4b58117f59e92b3b2313", "32261": "7c2a58d51f4528827e9bfe9c43d06c5c1716bfb8", "32265": "0a4811677ee378c07a17062cedfbdcf3f9f40975", "32270": "ff9344f3d8d11d38fa3a2497199113e5bac9537c", "32274": "0e4e418eb2d34001724923b83111d5bb92edb4d1", "32291": "ffc0f66676b4835eb1bdd3f3ecab025e9c1be9fe", "32292": "86c7599d996368899898349185df068c4e2c5bd7", "32294": "53234c5b6bae7827fed9c74072cb059d33c476ba", "32303": "083ab6fcb6bfe2b4f454befcb1c585267b39e5fc", "32305": "af930a9aa4f55361a66051ac9ef151cda3742bf8", "32308": "80d21c37672dbb4b2439fbfb19b8d5e28d7f20ab", "32312": "b4ffba9e225971b9abe59aa28146197eb9910cb0", "32331": "239e16319116ab7445c0557bb08783ab2d60673d", "32339": "76511995f7804727c6f0494ca05e6e3f4d4f5430", "32340": "aee7f594f5d82ba75bcb8d720066ce18c727d0d1", "32342": "2e481f114169396660f0051eee1bcf6bcddfd556", "32343": "3e47fa91b6ed73f358105f2a1c6501e14f633bba", "32348": "64432e1cf65fc87c763737aa6422bb92d3573786", "32349": "e947074f63c6602ae15cd57b1fa4f6658040cff7", "32354": "7ec1bfc2ab7425bcd984d631b5bfeb9082ce11bf", "32358": "70442b9ee3753a6d63a9b2bfd35e3e51cadce230", "32361": "dbde1da1954be91b9a0a12c9a109c17cd109bc76", "32378": "c4d221ddcb9171f5bb05f7fe0dd0b96f7d532331", "32387": "86301acc28bb70f0e18f4be0e0b2d1e694e897ef", "32397": "85574f9cb847f39124816e6bf8a02fbf9550bd32", "32408": "9c9c8582dff9f4563aa130ef89f155bad0051493", "32409": "b728b2e8b192857f3522007328fa66909ed68787", "32411": "75db1bc2dbd716016170241d8daae97624d01252", "32420": "a7698a8bd853f1f32281ef635c7d4a827383d5fd", "32424": "3eb00d83ca40b458065d2739c0a7d60098e05701", "32432": "433600e68fbb12e72d8c5e0707916f5603bb7057", "32454": "c7d5f58d490e19680a4dc3d530f969baab033f2f", "32499": "dc580a8ef5ee2a8aea80498388690e2213118efd", "32569": "affaa62b1d053f3349e766aee91f397267a72656", "32572": "2cce02414d4a7161f0d105450c196d94b1182220", "32576": "96a0bc861ad2ba3c63db0326b42b41ddabeb2aff", "32580": "ce00ba817e7592c8e14f7610dd1f13ad694a3e5d", "32588": "e411c29625e66f7e440f1acce4069e01201cf122", "32591": "62a017efa047e9581ae7df8bbaa62cf4c0544ee4", "32597": "ba1d23d13e402367c6401e07256867fdd5a4a0bf", "32600": "9e08ed2279c80407f1d4c92a27279f73a2d08bb2", "32605": "bc00bdce93d6cbd4441d3427a65464fadbaaacbe", "32607": "a0a6ea744f355ed078e491eadf49d1b9c1a17cda", "32619": "52e89a4e17b8b27dbc8dc41592d354f65e179260", "32629": "dc7ef61d0d58be84355b965481032d59f8f41e2e", "32640": "f7eea978097085a6781a0e92fc14ba7712a52d75", "32646": "bf03a6354670414695ef483de8187135aeec6cbd", "32649": "d5fcb20b39c9b283d9485a9dcb4b2d554422e269", "32651": "71a647f8bcc4c0ec8e4b8ce76f5f566f0513a222", "32770": "e58f36c73bd524ad87b05126a4e5b50dc4b24fcc", "32838": "4ff92e03d78db5f6eb9abd87594b491cebc80bf9", "32841": "22336afec6384e85366d94dab7a108fd2a0b64fc", "32848": "677a4cfef679313cd437c6af9e0398a22df73ab6", "32852": "d4e7158bcaa6f91a42e8afba21b7803bf82c3813", "32853": "d9cfe3f6b1c58dd253dc87cb676ce5171ff1f8a1", "32854": "0c42159547d000dba29cf7d5d47bc251bdf0fd52", "32856": "6adb209acd63825affc884abcd85381f148fb1b0", "32869": "7b595569b26f4aa65a74a971ef428f4f071f48c4", "32870": "1042757565b85960c42e97ef4a21d9943e7cb48e", "32871": "e6b46675318950fd5138aaf29ba76f6ce2fd91b8", "32879": "b4afbeeebeefe253bdc12db2820f5eef5639c8b1", "32880": "ae4a1b1a780e50d07ca68c15a1876c618d8fd19f", "32881": "de67a4420f1713058070802ad593cbcd2ee2d5f3", "32895": "fabe1606daa8cc275222935769d855050cb8061d", "32898": "2c867b8f822eb7a684f0d5c4359e4426e1c9cfe0", "32900": "4180b079f7709fe5ab8d32a11438116dc8957715", "32914": "20ad9cd62cbef744eb28b29ab8a33fc3b51f8a3e", "32919": "7e8d3c505baafa45bd94d9e28ee3d35141ff91c4", "32984": "9aaed498795f68e5956ea762fef9c440ca9eb239", "32986": "a70954d8298965cbad25a337b08e1a765b736555", "32997": "c991e30c96ace1565604b429de22e36ed6b1e7bd", "33009": "30bf6f39a7126a351db8971d24aa865fa5605569", "33021": "fd9bff1fd20b129f516d4675b24aeacfdd3bac56", "33031": "ab7e3d19c16011d9ed4bd80f867336d8a741216a", "33040": "b397b8f2d952a26344cc062ff912c663f4afa6d5", "33050": "9260f510abcc9574f2383fc01e02ca7e677d6cb7", "33057": "e3e880f9a749df95727a9c3102feb755387d33bb", "33066": "3043ea6cf96571da0787252401abdb62ee04612f", "33075": "e3d1f9ac39e4bf0f31430e779acc50fb05fe1b64", "33086": "18af5508013d8497b0449c059b9a794c9643735a", "33090": "49a937e974190b4ab20c7506052ce8a67c129da1", "33095": "01b9050b690ebb07870454720f5f67ac235348e4", "33096": "545cc809e16005fb5f5ee401b19cf69e9874d58b", "33103": "10dbc142bd17ccf7bd38eec2ac04b52ce0d1009e", "33109": "ec8a2a63b3e02bb955079c2af26d95af6a407242", "33120": "70c489f1273a5ff877e61750b3a69590bc002b6f", "33127": "c3bfe86b45577a9405a4680d9971efa9594a0657", "33131": "1ac10736135a62b0dce02c2529f73cd049c31296", "33148": "7f1e15d5c253d5dfdc8c55b5f1c6139e9bcd1de3", "33179": "cf3573ee90c541c82d22b80d57c9dec7d99fc58d", "33189": "1834cd6b76f63156b786e3e63cc48604532505c1", "33194": "97327c75b3c77babc5a97d367c7512b19c07cffb", "33208": "66a4d9639e27bc04c21bac4eb259fe28b1dad4af", "33209": "667dc564848bf3cfd3bda47367ff1202ad7fa9bf", "33211": "463d1665e628628e837d11b323d86cadaae27081", "33213": "5a332e77a10a44107276843d8532ef79f239c8f3", "33225": "cec09e20910e3eb970310732c40ec63b35b5cd35", "33228": "a1877586bbe5eaa90bdd8aa5714b0a05efab750c", "33229": "66a39055412b5c1d0c5740be7e2849ef8b040fa1", "33259": "ae35ce83679ccef74932fbfe554d1e1ea63ff6fa", "33279": "28d65c55332350a85f84c0ad45a306a6e90b68e4", "33285": "a2b85716728da2596ee2275cbea939497af9146d", "33291": "ea046f024694b9a558c882b8c2610c52dad95e29", "33294": "f5ec34e0f76277ba6d0a77d3033db0af83899b64", "33295": "86541f2b3bc8a96264e265cb810cf79858544340", "33296": "6d356dda608e01537a53e20d4c5e80220297eb24", "33302": "f034f57b1ad7bc5a7a5dd342543cea30c85e74ff", "33309": "689efe2f25356aa674bd0090f44b0914aae4d3a3", "33310": "4ccf41beeb9618129ddf89200e6d9540ada7f96c", "33311": "42d235924efa64987a19e945035c85414c53d4f0", "33315": "41b0bd82ffa90c00778c6b69f400d8ddf5775eb2", "33323": "c8f79e234e99733bd2e9c52b97684cd924aa73e4", "33332": "295397890f26a21f5901108a94f2b80eb94e5705", "33333": "849c2f10f56b908abd9abbbffca8941494cc0bb0", "33337": "314f7babcda8fd5e6813b8a6ed31d87af0efdc62", "33338": "e5c65906ee7fdab81c2950fab0fe4d04ed7ad522", "33341": "4f89e717570e76650ca6f73e25c5151f8902dad5", "33346": "092b7f3f6721cb076c40aa4cc74b128ff3990f21", "33351": "99c9f41c774b6b3d4f36f515b06f5b20838d0771", "33358": "0e253d96f89eb507476a6c498f0972c1b426e8da", "33359": "1e8a5b833d1b58f3ab84099c4582239af854b23a", "33361": "18cf8d01ea67d44739d18dbb7c9452e5aa8c9b79", "33370": "8cac52f9d1a393f7809801405013b5e0d2785499", "33373": "21312644df0a6b4c6f3c27a74ac9d26cf49c2304", "33376": "9ea0ec40f8b2753ab1bb4d97407c9b05a883f0f1", "33380": "20be4dfb50e015ca62c11bc3f4c73ffe4d74c36f", "33386": "180e059b1b329dfb9b304a12a1506fc7e0fc20ff", "33393": "cb233674ddffeb1f75f63309f94e4f90d0a2bdf8", "33400": "33a1f1690e7a7007633f59b6bee32017f4229864", "33414": "ceec2fa696e51b8303f5475c3b263f68a856ab8b", "33424": "9cbcc1f205e8be4dad1f383239e98381abb28bd0", "33428": "ee5d94e0a05da11272a4af1cd731f9822565048e", "33437": "d2b9c802844a5bbd81687fbe6b43fc80a79c8ffa", "33444": "d9212debbce3513310c1e06709ab735d426850e9", "33453": "309a8b63ca4f127149140c0cfa0e0e0f417da436", "33504": "7f9bad99d6e0a3e8ddf92a7e5561245224dab102", "33516": "0a45f93418d2724e496b39c2d260a2ae047ec334", "33517": "b88b53985d9ddf8cec60414934c55a5745e8b958", "33518": "483fafe5d1a27446a8f05a0d9bb3762de47b1618", "33520": "14995509a996ff5575c032fb7aead25bf6bb595c", "33524": "27c3549b3dfa8a50e2753d825118588ea2923f2c", "33533": "34446739dfbe5cb61d2ddccb1f4fcfaa1efd7a9b", "33536": "3a291fce9b1db5f8b408de9dc8e0d6a2d6b93496", "33537": "d5a354605ab9dcdac5a05ffc692d962ad2bb0dac", "33543": "fe26a08c5c0902db80667bed2d72a506826417ab", "33546": "dbad41e58d6010cf1ab0f93eacb5fee652e91136", "33551": "dfd299b19e1e4a167023cac76c8e1c57c01341a9", "33648": "b35cd21530d9a97deba3a6fe70ba14d1d8d2afa6", "33704": "372b957ae3bdd5ec4758db1e58b2496532d53b78", "33707": "989d29946a197eedde3c30f71ea4498e6642ec05", "33708": "6f9c6629e505c5892ded725efa86f91c8fb986e4", "33712": "a05eb6bbe30bc40904274c87afb4ac93bcd60168", "33715": "8ed0270b99344cee9bb253cbfa1d986561ea6cd7", "33722": "cb15a82e6439feda50b0605d70ce6d06c2eac7fd", "33733": "c634b8abbb5d96e0089b593aa04fb5ac80a047ec", "33734": "bbc73cfd7f5a85f6ac63432d3294abecdcb81d2a", "33756": "611cffe181d7dc8b744947c6be801203f92f0f8d", "33766": "a823012281a6c7f3b2f92cddc048b9be82e98cf2", "33802": "0a03293a89895729eb6c8f0dcdd7db86142b92c5", "33808": "0d701e8fef043b3604008868bcd94a96d1217f4b", "33813": "8faa92011e76bace1df02230bce83ee3a5e083b0", "33818": "b7169fd060e10a9328cf985a5ac8440932f25fee", "33820": "3c9495cc64b738ce402103bb685afeb01543971d", "33826": "3b35ad03d348658cd85ba4b3647873fae5f75a48", "33833": "89ea028ebdb605bd75f48f59de3e0bf770d3b8a4", "34030": "55a65a2fa5653257225d7e184da3d0c00ff852b1", "34031": "ba7d86956da03aa4fd230b1bbe8df57b63cf2dc0", "34034": "20dad5851e77836a01aea710de3f965fe9384576", "34046": "f86f41d80bff882689fc16bd7da1fef4a805b464", "34049": "457b02c61a2f3cd353d2997929b67a3ef890bf60", "34052": "38a1e64bbe42a7b66a77835e46e5f7725bccd18b", "34058": "2a548da593ab7a8f1c7b0af8985de8935bc3be98", "34065": "bdf66d048c2113e94397b11ff17b7b5c03938ab7", "34068": "9f6592f714cf1b0fb6f2d8fb636d9e458fad41d5", "34075": "04e39db499afab852e4e2603807384a402a871a9", "34079": "286f0c9d17019e52f532d63b5ace9f8e1beb5fe5", "34113": "ebe4c7ea999a32bafc9044ebe75b4901f92037a0", "34115": "b470ba1bd5c5b4955016f509a6baeb06ffbbafe9", "34120": "65923a7850cb7aa128c2422205a1bcad732db54e", "34126": "b93f80badd1873bf7db9c703879163a9b7aab6c4", "34139": "fb6b9f59469a4ffcffee2999f531f4bb4c2128fd", "34140": "b22c706c700ce4ac24ee26e21fbce8a24ef799a6", "34141": "c6d0d29b1903e40c9947c5aa1a2f420fb7f4f004", "34152": "093e0cf14aff026cca6097e8c42f83b735d26358", "34155": "1f1329f7ecb001eda2ff8e6d6a68bc2054c4962f", "34158": "e9c74a3f0a5944b1420158d36b1bfed836234b97", "34160": "5c85b581b858c5c99b9f90c6a5fd049f0ad85a4b", "34162": "dcebbc4c5c97f886a57b0684a5e943f94db1bd58", "34164": "5fc67aeb092d636895b599921283221a68c7a2ad"}, "revision_to_date": {"382": 1264603663000, "395": 1265024295000, "587": 1269007740000, "590": 1269244318000, "646": 1270698297000, "745": 1272878771000, "755": 1272909852000, "811": 1273294444000, "813": 1273337313000, "826": 1273550555000, "998": 1277561666000, "1016": 1277824675000, "1131": 1279558872000, "1207": 1280235748000, "1288": 1281104090000, "1915": 1286358759000, "1917": 1286371631000, "1919": 1286373337000, "1969": 1286782666000, "1977": 1286812002000, "2701": 1292596297000, "2711": 1292968871000, "2743": 1294669325000, "3102": 1298808434000, "3151": 1299078131000, "3212": 1299680572000, "3289": 1300670714000, "3741": 1302729559000, "3905": 1304345121000, "4037": 1305108339000, "4054": 1305126138000, "4684": 1309505367000, "4696": 1309545528000, "6177": 1316527045000, "6225": 1316642399000, "6511": 1318977607000, "7872": 1326216418000, "7904": 1326287141000, "7919": 1326426441000, "9331": 1336328405000, "9349": 1336407543000, "9357": 1336426836000, "9369": 1336524866000, "9799": 1341415689000, "10413": 1346780365000, "10436": 1346788092000, "10457": 1346981442000, "10778": 1349734773000, "12368": 1358801181000, "12373": 1358806382000, "12748": 1361636276000, "14515": 1375060310000, "14698": 1375915741000, "14725": 1375972053000, "16940": 1401972588000, "17074": 1404172403000, "17075": 1404240383000, "17279": 1405354512000, "17645": 1406899808000, "17934": 1409835738000, "19198": 1425667359000, "19199": 1425681522000, "19375": 1427396256000, "19504": 1429027572000, "19920": 1436588422000, "20502": 1445007457000, "20509": 1445013082000, "20952": 1445953225000, "20955": 1445958667000, "21113": 1446753465000, "21126": 1446818031000, "21322": 1450749753000, "21323": 1450761225000, "21601": 1455802186000, "21602": 1455802246000, "22265": 1473791605000, "22268": 1473799038000, "22283": 1473882154000, "22393": 1475007587000, "22702": 1478902517000, "23197": 1497903977000, "23280": 1499947923000, "23283": 1499952302000, "23307": 1500281648000, "23480": 1502470027000, "23768": 1505921382000, "24417": 1531668719000, "24644": 1535551327000, "24809": 1537887812000, "25159": 1542875805000, "25261": 1545209521000, "25563": 1551431215000, "25750": 1556378170000, "25758": 1556603560000, "25766": 1556634531000, "25767": 1556635319000, "25841": 1557442357000, "25874": 1557893876000, "25910": 1558616196000, "26278": 1564406958000, "26284": 1558572641000, "26819": 1573637668000, "26820": 1573476950000, "26881": 1574093837000, "26890": 1574244189000, "26944": 1574933073000, "26953": 1575301264000, "27063": 1577976510000, "27300": 1582908441000, "27325": 1583315487000, "27498": 1588010313000, "27571": 1588689638000, "27604": 1589270282000, "27674": 1589872045000, "27937": 1593854670000, "28086": 1592994930000, "28255": 1599747257000, "28261": 1600274505000, "28269": 1600378277000, "28272": 1600458232000, "28277": 1600722669000, "28278": 1600789062000, "28284": 1600865667000, "28288": 1600968970000, "28291": 1601106935000, "28296": 1601326769000, "28302": 1601415150000, "28306": 1601462345000, "28308": 1601589341000, "28311": 1601660413000, "28314": 1601930618000, "28320": 1602017230000, "28326": 1602089300000, "28333": 1602190160000, "28339": 1602263563000, "28340": 1602436405000, "28345": 1602536302000, "28347": 1602591864000, "28357": 1602693776000, "28360": 1602796581000, "28361": 1602859901000, "28365": 1603135307000, "28367": 1603210848000, "28371": 1603296704000, "28373": 1603378269000, "28376": 1603484187000, "28377": 1603729650000, "28381": 1603813015000, "28390": 1603918365000, "28392": 1603993849000, "28396": 1604082959000, "28397": 1604157689000, "28404": 1604266317000, "28413": 1604338820000, "28416": 1604443088000, "28417": 1604518746000, "28418": 1604585464000, "28426": 1604687645000, "28428": 1604867994000, "28429": 1604916743000, "28435": 1605029333000, "28439": 1605135329000, "28443": 1605211856000, "28449": 1605292115000, "28450": 1605376572000, "28452": 1605564612000, "28454": 1605628238000, "28460": 1605722026000, "28462": 1605822301000, "28468": 1605911343000, "28469": 1606015242000, "28474": 1606161074000, "28476": 1606336705000, "28481": 1606416080000, "28485": 1606497935000, "28487": 1606765444000, "28495": 1606821855000, "28497": 1606904333000, "28499": 1606925797000, "28501": 1606931617000, "28502": 1607004204000, "28505": 1607116223000, "28506": 1607613543000, "28507": 1607723835000, "28510": 1607961058000, "28516": 1608059116000, "28520": 1608136519000, "28524": 1608242770000, "28527": 1608307759000, "28529": 1608395895000, "28532": 1608486943000, "28536": 1608587907000, "28541": 1608647213000, "28547": 1608676289000, "28550": 1609623728000, "28551": 1609698314000, "28554": 1609772780000, "28557": 1609840352000, "28561": 1609944537000, "28565": 1610128553000, "28566": 1610214433000, "28567": 1610304129000, "28572": 1610387413000, "28575": 1610461836000, "28580": 1610553773000, "28582": 1610641692000, "28584": 1610821727000, "28585": 1610915313000, "28588": 1610996785000, "28625": 1611052138000, "28629": 1611096802000, "28631": 1611164131000, "28633": 1611255467000, "28639": 1611341861000, "28644": 1611414840000, "28646": 1611487810000, "28653": 1611614513000, "28659": 1611689734000, "28663": 1611786407000, "28667": 1611868041000, "28670": 1611929245000, "28673": 1612010107000, "28674": 1612054336000, "28687": 1612217026000, "28688": 1612286029000, "28695": 1612393433000, "28696": 1612446975000, "28697": 1612514236000, "28702": 1612635631000, "28706": 1612696745000, "28712": 1612872626000, "28715": 1612885946000, "28720": 1612981796000, "28727": 1613076767000, "28734": 1613159543000, "28737": 1613400754000, "28740": 1613569280000, "28748": 1613674543000, "28751": 1613731449000, "28753": 1613840479000, "28761": 1614025369000, "28764": 1614104321000, "28767": 1614147824000, "28775": 1614262574000, "28779": 1614447340000, "28782": 1614618476000, "28786": 1614683996000, "28789": 1614793397000, "28790": 1615128856000, "28791": 1615226636000, "28792": 1615308357000, "28794": 1615382782000, "28797": 1615484044000, "28801": 1615590149000, "28802": 1615592700000, "28804": 1615733031000, "28808": 1615834814000, "28811": 1615930546000, "28817": 1615992780000, "28820": 1616089367000, "28827": 1616186648000, "28829": 1616249229000, "28834": 1616353572000, "28840": 1616519345000, "28841": 1616701156000, "28851": 1617400845000, "28853": 1617566024000, "28855": 1617640124000, "28859": 1617737608000, "28861": 1617832061000, "28867": 1617916880000, "28878": 1617992344000, "28879": 1618175593000, "28883": 1618257581000, "28890": 1618347639000, "28893": 1618413717000, "28895": 1618490002000, "28898": 1618600033000, "28905": 1618868919000, "28914": 1618954142000, "28917": 1619040868000, "28920": 1619110246000, "28922": 1619178650000, "28928": 1619467448000, "28936": 1619544136000, "29084": 1619600857000, "29085": 1619617061000, "29086": 1619725616000, "29088": 1619739533000, "29090": 1620050725000, "29092": 1620244799000, "29093": 1620265097000, "29097": 1620677421000, "29106": 1620770403000, "29108": 1620920636000, "29109": 1621006227000, "29110": 1621032016000, "29111": 1621172982000, "29113": 1621241554000, "29115": 1621364951000, "29119": 1621431262000, "29121": 1621520828000, "29123": 1621605580000, "29125": 1621709722000, "29126": 1621878405000, "29128": 1621944157000, "29131": 1622043901000, "29138": 1622124056000, "29142": 1622233878000, "29146": 1622489783000, "29156": 1622582567000, "29157": 1622648501000, "29164": 1622728054000, "29180": 1623250683000, "29185": 1623445015000, "29189": 1623510849000, "29190": 1623544407000, "29203": 1623793687000, "29215": 1623965080000, "29225": 1624040252000, "29227": 1624091050000, "29228": 1624219173000, "29229": 1624304793000, "29231": 1624373201000, "29233": 1624376492000, "29235": 1624391134000, "29240": 1624465784000, "29245": 1624562451000, "29246": 1624606131000, "29258": 1624736650000, "29262": 1624805941000, "29279": 1624903928000, "29286": 1624992439000, "29293": 1625090236000, "29294": 1625105021000, "29295": 1625431412000, "29296": 1625491027000, "29313": 1625595144000, "29318": 1625657660000, "29319": 1625751948000, "29322": 1625848516000, "29325": 1625952066000, "29327": 1626010586000, "29328": 1626111448000, "29340": 1626196541000, "29344": 1626363236000, "29349": 1626711194000, "29364": 1626810193000, "29371": 1626899379000, "29376": 1626986049000, "29381": 1627065892000, "29383": 1627161489000, "29387": 1627314805000, "29401": 1627418844000, "29404": 1627489158000, "29409": 1627574925000, "29414": 1627660909000, "29415": 1627719890000, "29420": 1627906614000, "29421": 1627974960000, "29425": 1628111422000, "29429": 1628181136000, "29435": 1628283892000, "29443": 1628368786000, "29446": 1628440292000, "29453": 1628538236000, "29454": 1628605886000, "29455": 1628675255000, "29457": 1628892021000, "29458": 1629060700000, "29469": 1629148355000, "29541": 1630592131000, "29548": 1630682386000, "29550": 1630790223000, "29551": 1630863632000, "29572": 1630935898000, "29586": 1631009128000, "29591": 1631035486000, "29598": 1631116383000, "29609": 1631193014000, "29611": 1631268037000, "29621": 1631548012000, "29636": 1631623921000, "29638": 1631647186000, "29644": 1631721222000, "29648": 1631796656000, "29652": 1631898294000, "29656": 1631979808000, "29657": 1632053184000, "29662": 1632171877000, "29665": 1632243233000, "29667": 1632346710000, "29733": 1632414516000, "29735": 1632423037000, "29742": 1632516259000, "29750": 1632746318000, "29753": 1632820895000, "29757": 1632916788000, "29761": 1632994638000, "29765": 1633110693000, "29766": 1633193599000, "29768": 1633355552000, "29776": 1633467847000, "29783": 1633621378000, "29788": 1633724151000, "29789": 1633749561000, "29790": 1633835632000, "29795": 1634072187000, "29798": 1634142184000, "29805": 1634230269000, "29806": 1634295072000, "29807": 1634399117000, "29808": 1634426648000, "29813": 1634558965000, "29815": 1634655567000, "29828": 1634761299000, "29839": 1634850335000, "29844": 1634909602000, "29858": 1635021251000, "29865": 1635104837000, "29997": 1635154787000, "29999": 1635179228000, "30002": 1635285319000, "30010": 1635365351000, "30013": 1635455200000, "30023": 1635527737000, "30028": 1635604153000, "30035": 1635850978000, "30046": 1635966997000, "30053": 1636041350000, "30066": 1636132510000, "30068": 1636189566000, "30070": 1636288882000, "30074": 1636385531000, "30076": 1636488027000, "30077": 1636582028000, "30078": 1636658652000, "30085": 1636756391000, "30086": 1636838462000, "30096": 1636999437000, "30104": 1637085139000, "30106": 1637168632000, "30112": 1637262498000, "30116": 1637319488000, "30118": 1637418893000, "30123": 1637618997000, "30128": 1637705763000, "30135": 1637777927000, "30145": 1637864181000, "30155": 1637956585000, "30156": 1638018624000, "30157": 1638057062000, "30165": 1638220668000, "30174": 1638310769000, "30179": 1638381381000, "30185": 1638476003000, "30189": 1638563225000, "30190": 1638654791000, "30198": 1638819086000, "30202": 1638888185000, "30203": 1638968646000, "30208": 1639082235000, "30212": 1639163319000, "30213": 1639179354000, "30215": 1639419807000, "30218": 1639518773000, "30225": 1639584547000, "30227": 1639692819000, "30233": 1639777744000, "30235": 1639934505000, "30238": 1640020199000, "30244": 1640116258000, "30248": 1640200222000, "30254": 1640294413000, "30259": 1640364531000, "30260": 1640431291000, "30500": 1640431648000, "30501": 1640701470000, "30502": 1640863001000, "30506": 1640982697000, "30507": 1641153417000, "30510": 1641224916000, "30515": 1641333323000, "30519": 1641416619000, "30520": 1641492764000, "30524": 1641589783000, "30525": 1641673299000, "30529": 1641854947000, "30533": 1641931361000, "30538": 1642009315000, "30542": 1642112955000, "30543": 1642155901000, "30544": 1642210241000, "30545": 1642433763000, "30550": 1642536525000, "30552": 1642593136000, "30556": 1642716792000, "30561": 1642787468000, "30564": 1642877522000, "30565": 1642958675000, "30577": 1643053590000, "30581": 1643130258000, "30586": 1643221209000, "30593": 1643294500000, "30615": 1643402974000, "30621": 1643494622000, "30622": 1643560106000, "30629": 1643638950000, "30635": 1643753378000, "30639": 1643824343000, "30640": 1643884968000, "30643": 1644011254000, "30646": 1644076710000, "30647": 1644187621000, "30650": 1644265942000, "30657": 1644357039000, "30665": 1644436807000, "30670": 1644533900000, "30675": 1644596303000, "30679": 1644699640000, "30694": 1644873503000, "30704": 1644958366000, "30708": 1645027501000, "30718": 1645117746000, "30723": 1645215955000, "30729": 1645306485000, "30730": 1645459454000, "30734": 1645557198000, "30739": 1645623865000, "30744": 1645739513000, "30748": 1645808094000, "30750": 1645892531000, "30754": 1645969117000, "30761": 1646084810000, "30762": 1646160183000, "30777": 1646262003000, "30782": 1646300512000, "30785": 1646416299000, "30787": 1646496694000, "30794": 1646682100000, "30804": 1646768999000, "30812": 1646859477000, "30817": 1646942986000, "30821": 1647030828000, "30838": 1647109345000, "30849": 1647209663000, "30861": 1647285454000, "30868": 1647371949000, "30872": 1647451140000, "30890": 1647557283000, "30904": 1647634447000, "30907": 1647727404000, "30908": 1647800199000, "30917": 1647896133000, "30928": 1647984962000, "30931": 1648054763000, "30938": 1648160658000, "30945": 1648243671000, "30949": 1648319349000, "30955": 1648406260000, "30957": 1648483673000, "30967": 1648581286000, "30974": 1648672004000, "30978": 1648748734000, "30987": 1648847676000, "30988": 1648901247000, "30994": 1649106907000, "30997": 1649150463000, "31009": 1649273792000, "31019": 1649350287000, "31031": 1649449476000, "31039": 1649539600000, "31040": 1649611192000, "31041": 1649689094000, "31120": 1651052569000, "31184": 1652277602000, "31297": 1652962489000, "31927": 1659704464000, "32088": 1662650106000, "32090": 1662708913000, "32101": 1662737945000, "32104": 1662814977000, "32112": 1663007356000, "32115": 1663074696000, "32116": 1663145605000, "32120": 1663256210000, "32130": 1663340845000, "32131": 1663401075000, "32132": 1663530485000, "32138": 1663598489000, "32148": 1663772127000, "32152": 1663870025000, "32156": 1663946749000, "32157": 1663986725000, "32163": 1664140855000, "32174": 1664229269000, "32181": 1664287910000, "32186": 1664388499000, "32187": 1664461587000, "32193": 1664562847000, "32197": 1664805604000, "32198": 1664868848000, "32204": 1665078930000, "32213": 1665164580000, "32218": 1665423832000, "32220": 1665524925000, "32224": 1665593694000, "32241": 1665696739000, "32249": 1665764076000, "32252": 1666028219000, "32256": 1666128017000, "32259": 1666180465000, "32261": 1666275645000, "32265": 1666549553000, "32270": 1666642605000, "32274": 1666714923000, "32291": 1666790709000, "32292": 1666777887000, "32294": 1666859255000, "32303": 1666971913000, "32305": 1667251255000, "32308": 1667319103000, "32312": 1667425048000, "32331": 1667500962000, "32339": 1667597404000, "32340": 1667655643000, "32342": 1667827735000, "32343": 1667920232000, "32348": 1668096180000, "32349": 1668161431000, "32354": 1668247510000, "32358": 1668370218000, "32361": 1668450346000, "32378": 1668542987000, "32387": 1668615570000, "32397": 1668712662000, "32408": 1668796144000, "32409": 1668967067000, "32411": 1669028816000, "32420": 1669155628000, "32424": 1669229533000, "32432": 1669314024000, "32454": 1669652459000, "32499": 1670501069000, "32569": 1672253566000, "32572": 1672335295000, "32576": 1672502364000, "32580": 1672681312000, "32588": 1672782103000, "32591": 1672846504000, "32597": 1672939907000, "32600": 1673017687000, "32605": 1673261378000, "32607": 1673369231000, "32619": 1673465204000, "32629": 1673554076000, "32640": 1673647527000, "32646": 1673714356000, "32649": 1673878111000, "32651": 1673989150000, "32770": 1674567494000, "32838": 1676412451000, "32841": 1676667117000, "32848": 1676831129000, "32852": 1676924601000, "32853": 1677007953000, "32854": 1677060631000, "32856": 1677174739000, "32869": 1677242387000, "32870": 1677318985000, "32871": 1677433403000, "32879": 1677533692000, "32880": 1677579308000, "32881": 1677582108000, "32895": 1677624245000, "32898": 1677758469000, "32900": 1677852228000, "32914": 1678142018000, "32919": 1678230083000, "32984": 1678293098000, "32986": 1678300766000, "32997": 1678376309000, "33009": 1678470836000, "33021": 1678726711000, "33031": 1678822655000, "33040": 1678919037000, "33050": 1679001183000, "33057": 1679069398000, "33066": 1679352540000, "33075": 1679412211000, "33086": 1679509889000, "33090": 1679586734000, "33095": 1679678108000, "33096": 1679772347000, "33103": 1679950288000, "33109": 1680037895000, "33120": 1680104936000, "33127": 1680197441000, "33131": 1680447506000, "33148": 1680547438000, "33179": 1681241666000, "33189": 1681315114000, "33194": 1681387148000, "33208": 1681509837000, "33209": 1681654063000, "33211": 1681751116000, "33213": 1681854133000, "33225": 1681925606000, "33228": 1682005553000, "33229": 1682068409000, "33259": 1683056233000, "33279": 1683705315000, "33285": 1684243870000, "33291": 1684328444000, "33294": 1684348796000, "33295": 1684455041000, "33296": 1684767724000, "33302": 1684848919000, "33309": 1684945115000, "33310": 1685003210000, "33311": 1685116374000, "33315": 1685468792000, "33323": 1685549169000, "33332": 1685636762000, "33333": 1685696112000, "33337": 1685775923000, "33338": 1685970274000, "33341": 1686060207000, "33346": 1686164484000, "33351": 1686223118000, "33358": 1686331783000, "33359": 1686562004000, "33361": 1686677411000, "33370": 1686762523000, "33373": 1686822807000, "33376": 1686837859000, "33380": 1686921372000, "33386": 1687195456000, "33393": 1687280423000, "33400": 1687362667000, "33414": 1687454936000, "33424": 1687533193000, "33428": 1687797870000, "33437": 1687889014000, "33444": 1687970808000, "33453": 1688059673000, "33504": 1688049596000, "33516": 1688140195000, "33517": 1688211972000, "33518": 1688408245000, "33520": 1688420112000, "33524": 1688567545000, "33533": 1688654566000, "33536": 1688738244000, "33537": 1688764635000, "33543": 1689015102000, "33546": 1689105785000, "33551": 1689179641000, "33648": 1692199567000, "33704": 1693312776000, "33707": 1693402216000, "33708": 1693497411000, "33712": 1693574690000, "33715": 1693915368000, "33722": 1694012791000, "33733": 1694116492000, "33734": 1694366006000, "33756": 1694455478000, "33766": 1694542477000, "33802": 1694634394000, "33808": 1694689715000, "33813": 1694807049000, "33818": 1694874439000, "33820": 1694956547000, "33826": 1695059234000, "33833": 1695143438000, "34030": 1695204060000, "34031": 1695224738000, "34034": 1695308063000, "34046": 1695653805000, "34049": 1695740821000, "34052": 1695830869000, "34058": 1695899976000, "34065": 1696007297000, "34068": 1696024508000, "34075": 1696265713000, "34079": 1696357529000, "34113": 1697533319000, "34115": 1697561306000, "34120": 1697643038000, "34126": 1697716358000, "34139": 1697824316000, "34140": 1697879383000, "34141": 1697997241000, "34152": 1698055850000, "34155": 1698081283000, "34158": 1698155592000, "34160": 1698235049000, "34162": 1698326139000, "34164": 1698408361000}, "params": {"arch": ["x86_64"], "cpu": ["Intel Core Processor (Haswell, no TSX)"], "machine": ["sklearn-benchmark"], "num_cpu": ["8"], "os": ["Linux 4.15.0-20-generic"], "ram": ["16424684"], "python": ["3.11", "3.8"], "numpy": ["", "1.25.2"], "scipy": ["", "1.11.2"], "cython": ["", "0.29.36", "3.0.2", "3.0.3"], "joblib": ["", "1.3.2"], "threadpoolctl": ["", "3.2.0"], "pandas": ["", "2.1.0", null], "branch": ["main"]}, "graph_param_list": [{"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.8", "numpy": "", "scipy": "", "cython": "", "joblib": "", "threadpoolctl": "", "pandas": "", "branch": "main"}, {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.8", "numpy": "", "scipy": "", "cython": "", "joblib": "", "threadpoolctl": "", "branch": "main", "pandas": null}, {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.11", "numpy": "", "scipy": "", "cython": "", "joblib": "", "threadpoolctl": "", "pandas": "", "branch": "main"}, {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.11", "numpy": "1.25.2", "scipy": "1.11.2", "cython": "3.0.3", "joblib": "1.3.2", "threadpoolctl": "3.2.0", "pandas": "2.1.0", "branch": "main"}, {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.11", "numpy": "1.25.2", "scipy": "1.11.2", "cython": "0.29.36", "joblib": "1.3.2", "threadpoolctl": "3.2.0", "pandas": "2.1.0", "branch": "main"}, {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "python": "3.11", "numpy": "1.25.2", "scipy": "1.11.2", "cython": "3.0.2", "joblib": "1.3.2", "threadpoolctl": "3.2.0", "pandas": "2.1.0", "branch": "main"}], "benchmarks": {"cluster.KMeansBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.KMeansBenchmark.peakmem_fit", "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "a9d893de2d92e56e4dbeab4d7b7b4d5e00add3f4e993b164664b7ebbdd036dc7"}, "cluster.KMeansBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.KMeansBenchmark.peakmem_predict", "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "0f7d945338d774baae43a82dff7fe9f0db16ff6d1481b5afd437048b544396fc"}, "cluster.KMeansBenchmark.peakmem_transform": {"code": "class Transformer:\n def peakmem_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.KMeansBenchmark.peakmem_transform", "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "576d76cb6e3aa82315e3d3dc6a2e8b7e58cb38bdd510df6801ab645465f4eb70"}, "cluster.KMeansBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.KMeansBenchmark.time_fit", "number": 0, "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "a8dbf56b4b6365cb1e3c23b71c7df95ae011632c95124496f8fd1c30430154ec", "warmup_time": 1}, "cluster.KMeansBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.KMeansBenchmark.time_predict", "number": 0, "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "611589f0c08131355c37720106ea132a2653a100660cd34884455259325b9c83", "warmup_time": 1}, "cluster.KMeansBenchmark.time_transform": {"code": "class Transformer:\n def time_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.KMeansBenchmark.time_transform", "number": 0, "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "8a02da09ca430e84b11161256032a2d4c08df103e4626718278e8b69b90acb0c", "warmup_time": 1}, "cluster.KMeansBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.KMeansBenchmark.track_test_score", "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:16", "timeout": 500, "type": "track", "unit": "unit", "version": "67ff12752edbc7e4055ec0bddc293f22d59aec0eaa675c166f502a008bc22c59"}, "cluster.KMeansBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.KMeansBenchmark.track_train_score", "param_names": ["representation", "algorithm", "init"], "params": [["'dense'", "'sparse'"], ["'lloyd'", "'elkan'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:16", "timeout": 500, "type": "track", "unit": "unit", "version": "a5e07140ef3dd16920358a4c08c2f9f81d0e21f40bf5d8990b8a37b6a07c64e9"}, "cluster.MiniBatchKMeansBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.MiniBatchKMeansBenchmark.peakmem_fit", "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:65", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "42f5ccf79079b60ff9fa8b0220a6b1fb951f46d27574d343f6e6b4b69dd8f1f0"}, "cluster.MiniBatchKMeansBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.MiniBatchKMeansBenchmark.peakmem_predict", "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:65", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "03ee5b059682250c4b3d0793edf5a4978efb06c760148550f068e82dcb71e75f"}, "cluster.MiniBatchKMeansBenchmark.peakmem_transform": {"code": "class Transformer:\n def peakmem_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.MiniBatchKMeansBenchmark.peakmem_transform", "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:65", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "f844a68fb0292b177c459487189f905d1afb89d79ab35a0539f9f4217b445ff2"}, "cluster.MiniBatchKMeansBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.MiniBatchKMeansBenchmark.time_fit", "number": 0, "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:65", "timeout": 500, "type": "time", "unit": "seconds", "version": "40617ec6fdd94e3a650dba98f8204c9779e63ae7803343b23e7368f7b068f26e", "warmup_time": 1}, "cluster.MiniBatchKMeansBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.MiniBatchKMeansBenchmark.time_predict", "number": 0, "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:65", "timeout": 500, "type": "time", "unit": "seconds", "version": "561b80fa4780c86ee698a0efd05c5d6c1bce24014006c5ec9096c2f3a960b9fe", "warmup_time": 1}, "cluster.MiniBatchKMeansBenchmark.time_transform": {"code": "class Transformer:\n def time_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "cluster.MiniBatchKMeansBenchmark.time_transform", "number": 0, "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "cluster:65", "timeout": 500, "type": "time", "unit": "seconds", "version": "2cf7a764c9fa1511ff1e1dee921060dc33eb0608e1cee96b782dc7b5d3f91f89", "warmup_time": 1}, "cluster.MiniBatchKMeansBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.MiniBatchKMeansBenchmark.track_test_score", "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:65", "timeout": 500, "type": "track", "unit": "unit", "version": "7aeb8a20f66080e18e15f92e245fd1dd8de235e2f53d355596424dc7c30ae295"}, "cluster.MiniBatchKMeansBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchKMeansBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "cluster.MiniBatchKMeansBenchmark.track_train_score", "param_names": ["representation", "init"], "params": [["'dense'", "'sparse'"], ["'random'", "'k-means++'"]], "setup_cache_key": "cluster:65", "timeout": 500, "type": "track", "unit": "unit", "version": "b0c324767051682ea0bfc17c991f3de50e4876d683b1167c11ae8d4f2349b9c9"}, "decomposition.DictionaryLearningBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.DictionaryLearningBenchmark.peakmem_fit", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:41", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "8c3205268eade479bfda221734bf6129ab2a7b2bf4c59a8e6e855469f519672a"}, "decomposition.DictionaryLearningBenchmark.peakmem_transform": {"code": "class Transformer:\n def peakmem_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.DictionaryLearningBenchmark.peakmem_transform", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:41", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "b2c047a9e4d9d9cc6dd2d41a3738c21c183facbf5d609e8bfb354499f0b38ee4"}, "decomposition.DictionaryLearningBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.DictionaryLearningBenchmark.time_fit", "number": 0, "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:41", "timeout": 500, "type": "time", "unit": "seconds", "version": "9f6c61216a35b8b5a205dbce3e4f541613c2e1df4cda9f85b16a7a41a02a9e02", "warmup_time": 1}, "decomposition.DictionaryLearningBenchmark.time_transform": {"code": "class Transformer:\n def time_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.DictionaryLearningBenchmark.time_transform", "number": 0, "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:41", "timeout": 500, "type": "time", "unit": "seconds", "version": "a9786d7edfa47d44fb49632ba092edb63068a33298968990f071b58ad312e45a", "warmup_time": 1}, "decomposition.DictionaryLearningBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.DictionaryLearningBenchmark.track_test_score", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:41", "timeout": 500, "type": "track", "unit": "unit", "version": "022cecb50e5ba330d0728d08afbca34a130f0e74529bce6c8c93aca80a4bcae5"}, "decomposition.DictionaryLearningBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass DictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.DictionaryLearningBenchmark.track_train_score", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:41", "timeout": 500, "type": "track", "unit": "unit", "version": "6ed8ae7b04c1c5b4be0a5847795321be4c50195958c72642e1ca9367d838649d"}, "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:75", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "cf54cbec149e048235b388e434462754421fc5f8593697b431e17bd01f79cbe1"}, "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform": {"code": "class Transformer:\n def peakmem_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:75", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "c9e62449ea399590080c790df85e63df815e88ceaa029196f9ea925d3acfecd7"}, "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_fit", "number": 0, "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:75", "timeout": 500, "type": "time", "unit": "seconds", "version": "48d290a4fd2b0a9ecdd1a7add3b7e7b231d8df63e32889758ec0bbd8c1cb37ef", "warmup_time": 1}, "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform": {"code": "class Transformer:\n def time_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.MiniBatchDictionaryLearningBenchmark.time_transform", "number": 0, "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:75", "timeout": 500, "type": "time", "unit": "seconds", "version": "3ac7bfb8060c67e6dd13c37f1901d3f4274b8b0edfaf3d6a575d4e20ecbaf45e", "warmup_time": 1}, "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:75", "timeout": 500, "type": "track", "unit": "unit", "version": "a0774d6e8f922842e4b916076deab0ed00f152a84632f732cec174d5d619192f"}, "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass MiniBatchDictionaryLearningBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score", "param_names": ["fit_algorithm", "n_jobs"], "params": [["'lars'", "'cd'"], ["1", "4"]], "setup_cache_key": "decomposition:75", "timeout": 500, "type": "track", "unit": "unit", "version": "13436574eaa40a2dd7b58fbef029cd2171941b963cec765dff95a1889f6a157a"}, "decomposition.PCABenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.PCABenchmark.peakmem_fit", "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "setup_cache_key": "decomposition:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "1dc803fc882e472d9bc70274b900eb03304281cd2dff33ec3e3c039fffbb74a4"}, "decomposition.PCABenchmark.peakmem_transform": {"code": "class Transformer:\n def peakmem_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.PCABenchmark.peakmem_transform", "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "setup_cache_key": "decomposition:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "2b31c7c4510aca17a679729f995ba0b7d6548de119b989f414876912bc7851ff"}, "decomposition.PCABenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.PCABenchmark.time_fit", "number": 0, "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "4a753451bb0c872008db51c421599cf8badfcb691aab39aaa7822dad561241dc", "warmup_time": 1}, "decomposition.PCABenchmark.time_transform": {"code": "class Transformer:\n def time_transform(self, *args):\n self.estimator.transform(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "decomposition.PCABenchmark.time_transform", "number": 0, "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "decomposition:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "1f73bed6685d54963e63f4de9713d472d0ab242d57c6a0cfa54fac7d1e1e83ef", "warmup_time": 1}, "decomposition.PCABenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.PCABenchmark.track_test_score", "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "setup_cache_key": "decomposition:16", "timeout": 500, "type": "track", "unit": "unit", "version": "2bf9b85b93e81f43bf6e2e900a8ef13fb83b9b9298c32d0808bda654eb57c0c3"}, "decomposition.PCABenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass PCABenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "decomposition.PCABenchmark.track_train_score", "param_names": ["svd_solver"], "params": [["'full'", "'arpack'", "'randomized'"]], "setup_cache_key": "decomposition:16", "timeout": 500, "type": "track", "unit": "unit", "version": "16881c7fae4abaa9923123fc258e6542b0b3aa0c232d2db206548668bced23bb"}, "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_fit", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "ensemble:64", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "0bed7eba4859779600e1b1cb03539724eddad1419ad1332e897185f93bd3d6df"}, "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.GradientBoostingClassifierBenchmark.peakmem_predict", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "ensemble:64", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "5f65eed561196ec366996fc83d2258f891bbe9608480b00948108fa794a3c81e"}, "ensemble.GradientBoostingClassifierBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.GradientBoostingClassifierBenchmark.time_fit", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:64", "timeout": 500, "type": "time", "unit": "seconds", "version": "5702f67868717f5884d82ed22b8940f7ff2b626a2b46e2a4b6e1173c83db484f", "warmup_time": 1}, "ensemble.GradientBoostingClassifierBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.GradientBoostingClassifierBenchmark.time_predict", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:64", "timeout": 500, "type": "time", "unit": "seconds", "version": "17e3a4098ef2254174162a060b1286418984a4be5438aefd71301bf6a8f4c13d", "warmup_time": 1}, "ensemble.GradientBoostingClassifierBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.GradientBoostingClassifierBenchmark.track_test_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "ensemble:64", "timeout": 500, "type": "track", "unit": "unit", "version": "55092be1f965aa51752829bda24b944bdb1222a6b8e5fdf0d4026c9580953dea"}, "ensemble.GradientBoostingClassifierBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.GradientBoostingClassifierBenchmark.track_train_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "ensemble:64", "timeout": 500, "type": "track", "unit": "unit", "version": "cd78924c15421dcfc8b45a7d26a8b035a1e441c45612ee6ae169b9155e5a631b"}, "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit", "param_names": [], "params": [], "setup_cache_key": "ensemble:103", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "733ac3d039d12bcb9c7f00c745fad3c3723c29f21f67e444aabac276cbc3a916"}, "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict", "param_names": [], "params": [], "setup_cache_key": "ensemble:103", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "ef8fbc52879ef0add38e7cec975a52bd207c7003e688e265dcc4839b0bcaa3a8"}, "ensemble.HistGradientBoostingClassifierBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.HistGradientBoostingClassifierBenchmark.time_fit", "number": 0, "param_names": [], "params": [], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:103", "timeout": 500, "type": "time", "unit": "seconds", "version": "6840b9adeccbde7fc736aae2aa37f9b118d3fa9a78f2e0b2f0a4f09503e1a48d", "warmup_time": 1}, "ensemble.HistGradientBoostingClassifierBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.HistGradientBoostingClassifierBenchmark.time_predict", "number": 0, "param_names": [], "params": [], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:103", "timeout": 500, "type": "time", "unit": "seconds", "version": "ce65e5d6c62eebe1e73935285f56bc6c7ecebde97fb73fb4b9370c9b5979288a", "warmup_time": 1}, "ensemble.HistGradientBoostingClassifierBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.HistGradientBoostingClassifierBenchmark.track_test_score", "param_names": [], "params": [], "setup_cache_key": "ensemble:103", "timeout": 500, "type": "track", "unit": "unit", "version": "8c9a915f4dd669a61ceb38728602e43f84a976ebb06628f8026837eb7a5d30f6"}, "ensemble.HistGradientBoostingClassifierBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass HistGradientBoostingClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.HistGradientBoostingClassifierBenchmark.track_train_score", "param_names": [], "params": [], "setup_cache_key": "ensemble:103", "timeout": 500, "type": "track", "unit": "unit", "version": "43f6c225874e5193533ad56bdd398f471c7caa0f0f8c9a8ebb5486e10a2bec7f"}, "ensemble.RandomForestClassifierBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.RandomForestClassifierBenchmark.peakmem_fit", "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "setup_cache_key": "ensemble:24", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "14ca8ab81b54b4f2775c94fd794a13b049f48b9927979b964b90acc22ebf08a8"}, "ensemble.RandomForestClassifierBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.RandomForestClassifierBenchmark.peakmem_predict", "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "setup_cache_key": "ensemble:24", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "3febfd0d8977731921e7d366e6a585c8e405c0520f9a94415b96c6c334ed1c2f"}, "ensemble.RandomForestClassifierBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.RandomForestClassifierBenchmark.time_fit", "number": 0, "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:24", "timeout": 500, "type": "time", "unit": "seconds", "version": "7f77f2ea22b57af3ff27a86843c654c08e6aa926896f2c421666fd31d95ce65f", "warmup_time": 1}, "ensemble.RandomForestClassifierBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "ensemble.RandomForestClassifierBenchmark.time_predict", "number": 0, "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "ensemble:24", "timeout": 500, "type": "time", "unit": "seconds", "version": "6a93ee4dfb1d21e994eb8d7568e75ee99e0f416c9711bb2b45d1c022a27f0746", "warmup_time": 1}, "ensemble.RandomForestClassifierBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.RandomForestClassifierBenchmark.track_test_score", "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "setup_cache_key": "ensemble:24", "timeout": 500, "type": "track", "unit": "unit", "version": "a3b01d5f39647a3a6d6bfac31a005a5fdc82ad531a1b71f249ae2f4e98dc44c9"}, "ensemble.RandomForestClassifierBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RandomForestClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "ensemble.RandomForestClassifierBenchmark.track_train_score", "param_names": ["representation", "n_jobs"], "params": [["'dense'", "'sparse'"], ["1", "4"]], "setup_cache_key": "ensemble:24", "timeout": 500, "type": "track", "unit": "unit", "version": "42daa18fec647c7415a78ff56b84cf07b2253222c89f24baf5f12238463b9400"}, "linear_model.ElasticNetBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.ElasticNetBenchmark.peakmem_fit", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:187", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "aeb53df9e9543a762cf297b5697780eafb3cfbf2a7e750ad0f079ea50ff3d051"}, "linear_model.ElasticNetBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.ElasticNetBenchmark.peakmem_predict", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:187", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "27f5ef6022a3a4cdd5a0854b9428349a5e461bf638a76337760251639c9d7f02"}, "linear_model.ElasticNetBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.ElasticNetBenchmark.time_fit", "number": 0, "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:187", "timeout": 500, "type": "time", "unit": "seconds", "version": "02947c3221cd53cf645dab6e61c787646637d66474795a722ec537ff85976c8c", "warmup_time": 1}, "linear_model.ElasticNetBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.ElasticNetBenchmark.time_predict", "number": 0, "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:187", "timeout": 500, "type": "time", "unit": "seconds", "version": "4140a00f540d4dea5268a3813730d6fbb270e40b74285dbf046b3e26069f1287", "warmup_time": 1}, "linear_model.ElasticNetBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.ElasticNetBenchmark.track_test_score", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:187", "timeout": 500, "type": "track", "unit": "unit", "version": "1c0c2170cd23de65b973498cfc8dff584d9983a7513d2ead27d49594b092a280"}, "linear_model.ElasticNetBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass ElasticNetBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.ElasticNetBenchmark.track_train_score", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:187", "timeout": 500, "type": "track", "unit": "unit", "version": "6cff911c1163f327c86117f3dc306d62cdba87d9ea8068cc68977b61d151da78"}, "linear_model.LassoBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LassoBenchmark.peakmem_fit", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:228", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "8fa5824a898ff683065f60683a1805ae55dfdde209f22eb520e3dddac3b02688"}, "linear_model.LassoBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LassoBenchmark.peakmem_predict", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:228", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "2fd8dcd052ba7edddc85213c847b8fd149f36b0b9c0b058b88adae232e1fe0c6"}, "linear_model.LassoBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LassoBenchmark.time_fit", "number": 0, "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:228", "timeout": 500, "type": "time", "unit": "seconds", "version": "d0f2ce5dce5564f0fc096b1e4ee47c583962a62baf6a13edf150b4edaf353e05", "warmup_time": 1}, "linear_model.LassoBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LassoBenchmark.time_predict", "number": 0, "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:228", "timeout": 500, "type": "time", "unit": "seconds", "version": "9adfa14dab87a3a8a4de49d179ab5891f08045e1b81194ae39643622cb6487c9", "warmup_time": 1}, "linear_model.LassoBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LassoBenchmark.track_test_score", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:228", "timeout": 500, "type": "track", "unit": "unit", "version": "b56564a7b1756eeff8bbe981fa28bfb58f992c09069c2672ae87e637ba91f565"}, "linear_model.LassoBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LassoBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LassoBenchmark.track_train_score", "param_names": ["representation", "precompute"], "params": [["'dense'", "'sparse'"], ["True", "False"]], "setup_cache_key": "linear_model:228", "timeout": 500, "type": "track", "unit": "unit", "version": "97c0e5ecdddd2ee7c31046ec01b6d29119975ffd6774712a778a26f8499350c4"}, "linear_model.LinearRegressionBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LinearRegressionBenchmark.peakmem_fit", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:119", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "a905fac8878f96b0ccc05296ca1cbb10654937aa04579453c79a4255ec7865f1"}, "linear_model.LinearRegressionBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LinearRegressionBenchmark.peakmem_predict", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:119", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "759535a8913b60467ef240fed4181399ff149efa33bea0eb69eed231df3f8876"}, "linear_model.LinearRegressionBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LinearRegressionBenchmark.time_fit", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:119", "timeout": 500, "type": "time", "unit": "seconds", "version": "e5dbbebbcad57689afbefadad2fb87cb71161a32a9d6caa162975a5b419f0f97", "warmup_time": 1}, "linear_model.LinearRegressionBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LinearRegressionBenchmark.time_predict", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:119", "timeout": 500, "type": "time", "unit": "seconds", "version": "ba279c28dffebbb04b7b173dee9e976b48b05ffbada322dd53d9a2de22ff70f6", "warmup_time": 1}, "linear_model.LinearRegressionBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LinearRegressionBenchmark.track_test_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:119", "timeout": 500, "type": "track", "unit": "unit", "version": "0641fe07389de5e5b9811f51f186e4a4a96a856eb50c8810c62734a593513594"}, "linear_model.LinearRegressionBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LinearRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LinearRegressionBenchmark.track_train_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:119", "timeout": 500, "type": "track", "unit": "unit", "version": "5853e8435e7eba58f2264852c35444debdedaa05b29cccd9fef895ce848a5f06"}, "linear_model.LogisticRegressionBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LogisticRegressionBenchmark.peakmem_fit", "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "setup_cache_key": "linear_model:28", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "3b211361ab927e53d5697c6b9e81013a7575a9ce103d21adeb68544ea7a4e5dc"}, "linear_model.LogisticRegressionBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LogisticRegressionBenchmark.peakmem_predict", "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "setup_cache_key": "linear_model:28", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "be6101aa74d4f94ec846334788b859094ed4b1d36ca92bf7d693b3043a8d39da"}, "linear_model.LogisticRegressionBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LogisticRegressionBenchmark.time_fit", "number": 0, "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:28", "timeout": 500, "type": "time", "unit": "seconds", "version": "7cd42b119dd9bf6c8bf33ee70890f7ebaf0b159e0c0c8cd5b299c3f632725f21", "warmup_time": 1}, "linear_model.LogisticRegressionBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.LogisticRegressionBenchmark.time_predict", "number": 0, "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:28", "timeout": 500, "type": "time", "unit": "seconds", "version": "b9dd34b6a7b894f6afbd6e27f4d0cfe829c1b0e4af4f7203e56269b873ee049b", "warmup_time": 1}, "linear_model.LogisticRegressionBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LogisticRegressionBenchmark.track_test_score", "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "setup_cache_key": "linear_model:28", "timeout": 500, "type": "track", "unit": "unit", "version": "37e537f82f54da1d89003018c8370da6ac290d672b6343a457ee49dd444e3c9f"}, "linear_model.LogisticRegressionBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass LogisticRegressionBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.LogisticRegressionBenchmark.track_train_score", "param_names": ["representation", "solver", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'lbfgs'", "'saga'"], ["1", "4"]], "setup_cache_key": "linear_model:28", "timeout": 500, "type": "track", "unit": "unit", "version": "5647f2df8db098461a973d60cb900515f403287ed3e109a99151c94309e568f1"}, "linear_model.RidgeBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.RidgeBenchmark.peakmem_fit", "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "setup_cache_key": "linear_model:78", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "d06a93be5cf39a0df663d696943713376c4ba4abb2568ebc0bc97fd2a2fd5173"}, "linear_model.RidgeBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.RidgeBenchmark.peakmem_predict", "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "setup_cache_key": "linear_model:78", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "24e4dc55ce8e6b9311d26ca2936364cad3ddb0b8827b656a81886db508e69866"}, "linear_model.RidgeBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.RidgeBenchmark.time_fit", "number": 0, "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:78", "timeout": 500, "type": "time", "unit": "seconds", "version": "6ebbadd5cfeeb543e69ca73d777ab88bff49391965e0c0e3270868f1fa6bb385", "warmup_time": 1}, "linear_model.RidgeBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.RidgeBenchmark.time_predict", "number": 0, "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:78", "timeout": 500, "type": "time", "unit": "seconds", "version": "f41e9813a5f8239fbb0ef5e81982549e297ff18f751b7e4b42982972851b7cd0", "warmup_time": 1}, "linear_model.RidgeBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.RidgeBenchmark.track_test_score", "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "setup_cache_key": "linear_model:78", "timeout": 500, "type": "track", "unit": "unit", "version": "663c821271fbdb18d0252832535191137787f37ad6d6397624c92edd96dc6f3f"}, "linear_model.RidgeBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass RidgeBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.RidgeBenchmark.track_train_score", "param_names": ["representation", "solver"], "params": [["'dense'", "'sparse'"], ["'auto'", "'svd'", "'cholesky'", "'lsqr'", "'sparse_cg'", "'sag'", "'saga'"]], "setup_cache_key": "linear_model:78", "timeout": 500, "type": "track", "unit": "unit", "version": "92bfe13d8da10b255d1c72982a3a88f70985b864b39584e51a184ea88116f35d"}, "linear_model.SGDRegressorBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.SGDRegressorBenchmark.peakmem_fit", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:151", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "d81ea5fe5efd3e1ec085f0a2c66d712cfec7e2c4e03b19b7a50ab79dfd661f77"}, "linear_model.SGDRegressorBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.SGDRegressorBenchmark.peakmem_predict", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:151", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "cf12939ffeb2f97f86ada7e454920a994d254a98a02eac5e34ea687f8ec11ad0"}, "linear_model.SGDRegressorBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.SGDRegressorBenchmark.time_fit", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:151", "timeout": 500, "type": "time", "unit": "seconds", "version": "cc477ee1fcfc2e853f5113072b49c7dc80acf8f2e19f83518368e1efe8dd5374", "warmup_time": 1}, "linear_model.SGDRegressorBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "linear_model.SGDRegressorBenchmark.time_predict", "number": 0, "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "linear_model:151", "timeout": 500, "type": "time", "unit": "seconds", "version": "fcd01e3604428cf2063cbbfe4e708974618533d55ec0784a787b8bb838a2ece9", "warmup_time": 1}, "linear_model.SGDRegressorBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.SGDRegressorBenchmark.track_test_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:151", "timeout": 500, "type": "track", "unit": "unit", "version": "5c184c0b957ec177b911999a0cc2cd3996407b726efe5d7adeaeddea222a16d0"}, "linear_model.SGDRegressorBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SGDRegressorBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "linear_model.SGDRegressorBenchmark.track_train_score", "param_names": ["representation"], "params": [["'dense'", "'sparse'"]], "setup_cache_key": "linear_model:151", "timeout": 500, "type": "track", "unit": "unit", "version": "84040f29c546fcb4fb3fed1db35c198a88607a920f0d1aad43ae542738470257"}, "manifold.TSNEBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass TSNEBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "manifold.TSNEBenchmark.peakmem_fit", "param_names": ["method"], "params": [["'exact'", "'barnes_hut'"]], "setup_cache_key": "manifold:15", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "5b07ad9c3bf4af00ff4022361ced135ee0591fe9a613dddb484f0142685497c4"}, "manifold.TSNEBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass TSNEBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "manifold.TSNEBenchmark.time_fit", "number": 0, "param_names": ["method"], "params": [["'exact'", "'barnes_hut'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "manifold:15", "timeout": 500, "type": "time", "unit": "seconds", "version": "d7906ea0d1e8bee6103afdb924f0c5471c1c3e392feb7dbcc411b9e3f3535e6a", "warmup_time": 1}, "manifold.TSNEBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass TSNEBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "manifold.TSNEBenchmark.track_test_score", "param_names": ["method"], "params": [["'exact'", "'barnes_hut'"]], "setup_cache_key": "manifold:15", "timeout": 500, "type": "track", "unit": "unit", "version": "7c865f9e53f16c8492cb36db3b656646d6585227ebfbf097102fda1e83f5e953"}, "manifold.TSNEBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass TSNEBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "manifold.TSNEBenchmark.track_train_score", "param_names": ["method"], "params": [["'exact'", "'barnes_hut'"]], "setup_cache_key": "manifold:15", "timeout": 500, "type": "track", "unit": "unit", "version": "92a5fc587f972e63dad98657097b1bcd64a743dfce5f07b3e1847ed8b720d46d"}, "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances": {"code": "class PairwiseDistancesBenchmark:\n def peakmem_pairwise_distances(self, *args):\n pairwise_distances(self.X, **self.pdist_params)\n\n def setup(self, *params):\n representation, metric, n_jobs = params\n \n if representation == \"sparse\" and metric == \"correlation\":\n raise NotImplementedError\n \n if Benchmark.data_size == \"large\":\n if metric in (\"manhattan\", \"correlation\"):\n n_samples = 8000\n else:\n n_samples = 24000\n else:\n if metric in (\"manhattan\", \"correlation\"):\n n_samples = 4000\n else:\n n_samples = 12000\n \n data = _random_dataset(n_samples=n_samples, representation=representation)\n self.X, self.X_val, self.y, self.y_val = data\n \n self.pdist_params = {\"metric\": metric, \"n_jobs\": n_jobs}", "name": "metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances", "param_names": ["representation", "metric", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'cosine'", "'euclidean'", "'manhattan'", "'correlation'"], ["1", "4"]], "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "f982061fc53163362f863b2455a1f2f660861c4a4357be712dcacab0682833db"}, "metrics.PairwiseDistancesBenchmark.time_pairwise_distances": {"code": "class PairwiseDistancesBenchmark:\n def time_pairwise_distances(self, *args):\n pairwise_distances(self.X, **self.pdist_params)\n\n def setup(self, *params):\n representation, metric, n_jobs = params\n \n if representation == \"sparse\" and metric == \"correlation\":\n raise NotImplementedError\n \n if Benchmark.data_size == \"large\":\n if metric in (\"manhattan\", \"correlation\"):\n n_samples = 8000\n else:\n n_samples = 24000\n else:\n if metric in (\"manhattan\", \"correlation\"):\n n_samples = 4000\n else:\n n_samples = 12000\n \n data = _random_dataset(n_samples=n_samples, representation=representation)\n self.X, self.X_val, self.y, self.y_val = data\n \n self.pdist_params = {\"metric\": metric, \"n_jobs\": n_jobs}", "min_run_count": 2, "name": "metrics.PairwiseDistancesBenchmark.time_pairwise_distances", "number": 0, "param_names": ["representation", "metric", "n_jobs"], "params": [["'dense'", "'sparse'"], ["'cosine'", "'euclidean'", "'manhattan'", "'correlation'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "timeout": 500, "type": "time", "unit": "seconds", "version": "968c4646f4f823e76e062ccbbe50249793691ae13e472124d1ebd2642c86b5e0", "warmup_time": 1}, "model_selection.CrossValidationBenchmark.peakmem_crossval": {"code": "class CrossValidationBenchmark:\n def peakmem_crossval(self, *args):\n cross_val_score(self.clf, self.X, self.y, **self.cv_params)\n\n def setup(self, *params):\n (n_jobs,) = params\n \n data = _synth_classification_dataset(n_samples=50000, n_features=100)\n self.X, self.X_val, self.y, self.y_val = data\n \n self.clf = RandomForestClassifier(n_estimators=50, max_depth=10, random_state=0)\n \n cv = 16 if Benchmark.data_size == \"large\" else 4\n \n self.cv_params = {\"n_jobs\": n_jobs, \"cv\": cv}", "name": "model_selection.CrossValidationBenchmark.peakmem_crossval", "param_names": ["n_jobs"], "params": [["1", "4"]], "timeout": 20000, "type": "peakmemory", "unit": "bytes", "version": "4b6fc20c55d0bbbf2b9b56117a6725d0351eec991f183d04b136f1ce4552e0c7"}, "model_selection.CrossValidationBenchmark.time_crossval": {"code": "class CrossValidationBenchmark:\n def time_crossval(self, *args):\n cross_val_score(self.clf, self.X, self.y, **self.cv_params)\n\n def setup(self, *params):\n (n_jobs,) = params\n \n data = _synth_classification_dataset(n_samples=50000, n_features=100)\n self.X, self.X_val, self.y, self.y_val = data\n \n self.clf = RandomForestClassifier(n_estimators=50, max_depth=10, random_state=0)\n \n cv = 16 if Benchmark.data_size == \"large\" else 4\n \n self.cv_params = {\"n_jobs\": n_jobs, \"cv\": cv}", "min_run_count": 2, "name": "model_selection.CrossValidationBenchmark.time_crossval", "number": 0, "param_names": ["n_jobs"], "params": [["1", "4"]], "rounds": 1, "sample_time": 0.01, "timeout": 20000, "type": "time", "unit": "seconds", "version": "9959454181a0ddb22a0ce5727c352955d47bf0ce97d2189ff73d567981c64587", "warmup_time": 1}, "model_selection.CrossValidationBenchmark.track_crossval": {"code": "class CrossValidationBenchmark:\n def track_crossval(self, *args):\n return float(cross_val_score(self.clf, self.X, self.y, **self.cv_params).mean())\n\n def setup(self, *params):\n (n_jobs,) = params\n \n data = _synth_classification_dataset(n_samples=50000, n_features=100)\n self.X, self.X_val, self.y, self.y_val = data\n \n self.clf = RandomForestClassifier(n_estimators=50, max_depth=10, random_state=0)\n \n cv = 16 if Benchmark.data_size == \"large\" else 4\n \n self.cv_params = {\"n_jobs\": n_jobs, \"cv\": cv}", "name": "model_selection.CrossValidationBenchmark.track_crossval", "param_names": ["n_jobs"], "params": [["1", "4"]], "timeout": 20000, "type": "track", "unit": "unit", "version": "5e7e6b0e0116bbc68953414ce4e0eec203cc51c80a71d897dd599172b82aeedd"}, "model_selection.GridSearchBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "model_selection.GridSearchBenchmark.peakmem_fit", "param_names": ["n_jobs"], "params": [["1", "4"]], "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "peakmemory", "unit": "bytes", "version": "95b48fd99a9327cc7b96fbaf3fb68de0488e277098c5f71aa31f5bcc0af0aa35"}, "model_selection.GridSearchBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "model_selection.GridSearchBenchmark.peakmem_predict", "param_names": ["n_jobs"], "params": [["1", "4"]], "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "peakmemory", "unit": "bytes", "version": "c892cd859a96073eba53d60e549a73d8202c9d0e97f5469f5e0333d949ce8dce"}, "model_selection.GridSearchBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "model_selection.GridSearchBenchmark.time_fit", "number": 0, "param_names": ["n_jobs"], "params": [["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "time", "unit": "seconds", "version": "ce048ba169bd01fc98abe0f363fcaafc41dfc6d88ae4658795602e37fd0bd003", "warmup_time": 1}, "model_selection.GridSearchBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "model_selection.GridSearchBenchmark.time_predict", "number": 0, "param_names": ["n_jobs"], "params": [["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "time", "unit": "seconds", "version": "acfeae20f02fb4775c69f3a23452a495e43a2abb0e684954a33824913f37e3eb", "warmup_time": 1}, "model_selection.GridSearchBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "model_selection.GridSearchBenchmark.track_test_score", "param_names": ["n_jobs"], "params": [["1", "4"]], "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "track", "unit": "unit", "version": "ec63718f94ff0beda5889deafa3b1f1f3ff7750bf6254fce002cadda537bee4b"}, "model_selection.GridSearchBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass GridSearchBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "model_selection.GridSearchBenchmark.track_train_score", "param_names": ["n_jobs"], "params": [["1", "4"]], "setup_cache_key": "model_selection:51", "timeout": 20000, "type": "track", "unit": "unit", "version": "51575cdf87b95c5096592cecfc1f386cff2b52230b19a7bd6b1afee2fb55910c"}, "neighbors.KNeighborsClassifierBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "neighbors.KNeighborsClassifierBenchmark.peakmem_fit", "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "setup_cache_key": "neighbors:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "66acb7f2ea52ea49f9a5239c437782b0ac7cd030f150166dff686727e06ae1f5"}, "neighbors.KNeighborsClassifierBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "neighbors.KNeighborsClassifierBenchmark.peakmem_predict", "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "setup_cache_key": "neighbors:16", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "e7fb64f5f61911736101d3ca625806937a6bb4fc75b64a8ed0c9be1f37e0f10f"}, "neighbors.KNeighborsClassifierBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "neighbors.KNeighborsClassifierBenchmark.time_fit", "number": 0, "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "neighbors:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "455e6017e69db76a36673f135b8300f5288867804ae588240ef238340de7bc82", "warmup_time": 1}, "neighbors.KNeighborsClassifierBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "neighbors.KNeighborsClassifierBenchmark.time_predict", "number": 0, "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "neighbors:16", "timeout": 500, "type": "time", "unit": "seconds", "version": "6611e4000bd5b1d8935eb7407c10355bf476dfef925640b9a8445912b72c8183", "warmup_time": 1}, "neighbors.KNeighborsClassifierBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "neighbors.KNeighborsClassifierBenchmark.track_test_score", "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "setup_cache_key": "neighbors:16", "timeout": 500, "type": "track", "unit": "unit", "version": "95d25638754fb5c021b379d6f4f51868a7303bedb4868e52cac2a036eb0bc248"}, "neighbors.KNeighborsClassifierBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass KNeighborsClassifierBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "neighbors.KNeighborsClassifierBenchmark.track_train_score", "param_names": ["algorithm", "dimension", "n_jobs"], "params": [["'brute'", "'kd_tree'", "'ball_tree'"], ["'low'", "'high'"], ["1", "4"]], "setup_cache_key": "neighbors:16", "timeout": 500, "type": "track", "unit": "unit", "version": "1e1b6891a1563cf0c8ae446c751cfd6dec48cc2fcc4d0157f30a7189f05e938a"}, "svm.SVCBenchmark.peakmem_fit": {"code": "class Estimator:\n def peakmem_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "svm.SVCBenchmark.peakmem_fit", "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "setup_cache_key": "svm:14", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "b5099e172031e9a0f7b7706ec386c5bf36f9bd427f7d47274c66c6c39f5bf730"}, "svm.SVCBenchmark.peakmem_predict": {"code": "class Predictor:\n def peakmem_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "svm.SVCBenchmark.peakmem_predict", "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "setup_cache_key": "svm:14", "timeout": 500, "type": "peakmemory", "unit": "bytes", "version": "4a6611919a2e5a6cbd1f6c211b23857b3912da5e1484da897bf70155d62b7980"}, "svm.SVCBenchmark.time_fit": {"code": "class Estimator:\n def time_fit(self, *args):\n self.estimator.fit(self.X, self.y)\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "svm.SVCBenchmark.time_fit", "number": 0, "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "svm:14", "timeout": 500, "type": "time", "unit": "seconds", "version": "60f69bb46f97b00f249209ee47574d1508b9e81a8ba3ec0a8a3a430eb6aa719d", "warmup_time": 1}, "svm.SVCBenchmark.time_predict": {"code": "class Predictor:\n def time_predict(self, *args):\n self.estimator.predict(self.X)\n\nclass Estimator:\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "min_run_count": 2, "name": "svm.SVCBenchmark.time_predict", "number": 0, "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "rounds": 1, "sample_time": 0.01, "setup_cache_key": "svm:14", "timeout": 500, "type": "time", "unit": "seconds", "version": "ab64f47e62b03803ca9ee0734d6a0734af8278b39121b069d9abdf86a8e79285", "warmup_time": 1}, "svm.SVCBenchmark.track_test_score": {"code": "class Estimator:\n def track_test_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_val_pred = self.estimator.predict(self.X_val)\n else:\n y_val_pred = None\n return float(self.test_scorer(self.y_val, y_val_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "svm.SVCBenchmark.track_test_score", "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "setup_cache_key": "svm:14", "timeout": 500, "type": "track", "unit": "unit", "version": "f04be6a642a0b71d7bb27a3b184c53cf61aa01dead2ec4bbc68bf22ea78b68b3"}, "svm.SVCBenchmark.track_train_score": {"code": "class Estimator:\n def track_train_score(self, *args):\n if hasattr(self.estimator, \"predict\"):\n y_pred = self.estimator.predict(self.X)\n else:\n y_pred = None\n return float(self.train_scorer(self.y, y_pred))\n\n def setup(self, *params):\n \"\"\"Generate dataset and load the fitted estimator\"\"\"\n # This is run once per combination of parameters and per repeat so we\n # need to avoid doing expensive operations there.\n \n if self.skip(params):\n raise NotImplementedError\n \n self.X, self.X_val, self.y, self.y_val = self.make_data(params)\n \n est_path = get_estimator_path(\n self, Benchmark.save_dir, params, Benchmark.save_estimators\n )\n with est_path.open(mode=\"rb\") as f:\n self.estimator = pickle.load(f)\n \n self.make_scorers()\n\nclass SVCBenchmark:\n def setup_cache(self):\n super().setup_cache()", "name": "svm.SVCBenchmark.track_train_score", "param_names": ["kernel"], "params": [["'linear'", "'poly'", "'rbf'", "'sigmoid'"]], "setup_cache_key": "svm:14", "timeout": 500, "type": "track", "unit": "unit", "version": "30dfcaa0d1c48f402d28bf241f4c7c013ac533fbb528d470c427a34c237993f7"}}, "machines": {"sklearn-benchmark": {"arch": "x86_64", "cpu": "Intel Core Processor (Haswell, no TSX)", "machine": "sklearn-benchmark", "num_cpu": "8", "os": "Linux 4.15.0-20-generic", "ram": "16424684", "version": 1}}, "tags": {"0.10": 7904, "0.10-branching": 7872, "0.11": 9357, "0.11-beta": 9331, "0.11-branching": 9349, "0.12": 10436, "0.12-branching": 10413, "0.12.1": 10778, "0.13": 12373, "0.13-branching": 12368, "0.13.1": 12748, "0.14.1": 14725, "0.14a1": 14515, "0.15-branching": 17074, "0.15.0b1": 16940, "0.15.1": 17645, "0.16-branching": 19198, "0.16.0": 19375, "0.16.1": 19504, "0.16b1": 19199, "0.17-branching": 20502, "0.17.1": 21601, "0.17.1-1": 21602, "0.17b1": 20509, "0.18": 22393, "0.18.1": 22702, "0.18.2": 23197, "0.18rc": 22265, "0.18rc1": 22268, "0.18rc2": 22283, "0.19-branching": 23280, "0.19.1": 23768, "0.19.2": 24417, "0.20.0": 24809, "0.20.1": 25159, "0.20.2": 25261, "0.20.3": 25563, "0.20.4": 26284, "0.20rc1": 24644, "0.21.0": 25841, "0.21.1": 25874, "0.21.2": 25910, "0.21.3": 26278, "0.21b2": 25766, "0.21rc1": 25758, "0.21rc2": 25767, "0.22.1": 27063, "0.3": 745, "0.5": 1969, "0.5.rc": 1915, "0.5.rc2": 1917, "0.5.rc3": 1919, "0.6-rc": 2701, "0.6.0": 2711, "0.7": 3151, "0.7-branching": 3102, "0.7.1": 3212, "0.8": 4037, "0.8-branching": 3905, "0.8.1": 4684, "0.9": 6225, "0.9-branching": 6177, "1.0.1": 29997, "1.1.1": 31297, "1.3.1": 34030, "1.3.2": 34152, "sprint01": 1207, "0.2": 590, "0.1": 395, "0.2-beta": 587, "0.1-beta": 382, "debian/0.2+svn625-1": 646, "debian/0.3-1": 755, "debian/0.4-3": 1288, "debian/0.3-2": 811, "debian/0.3-3": 813, "debian/0.4-2": 1131, "debian/0.4-1": 1016, "debian/0.3-4": 826, "0.4": 998, "debian/0.5-1": 1977, "debian/0.6.0.dfsg-1": 2743, "debian/0.7.1.dfsg-1": 3289, "debian/0.7.1.dfsg-3": 3741, "debian/0.8.0.dfsg-1": 4054, "debian/0.8.1.dfsg-1": 4696, "debian/0.9.0.dfsg-1": 6511, "debian/0.10.0-1": 7919, "debian/0.11.0-1": 9369, "debian/0.11.0-2": 9799, "debian/0.12.0-1": 10457, "0.14": 14698, "0.15.0b2": 17075, "0.15.0": 17279, "0.15.2": 17934, "debian/0.16.1-2": 19920, "debian/0.17.0_b1-1": 20952, "debian/0.17.0_b1+git14-g4e6829c-1": 20955, "0.17": 21113, "debian/0.17.0-1": 21126, "debian/0.17.0-3": 21322, "debian/0.17.0-4": 21323, "0.19b1": 23283, "0.19b2": 23307, "0.19.0": 23480, "0.22rc1": 26820, "0.22rc2": 26881, "0.22rc2.post1": 26890, "0.22rc3": 26944, "0.22": 26953, "0.22.2": 27300, "0.22.2.post1": 27325, "0.23.0rc1": 27571, "0.23.0": 27604, "0.23.1": 27674, "0.23.2": 28086, "0.24.0rc1": 28501, "0.24.0": 28541, "0.24.1": 28625, "0.24.2": 29084, "1.0.rc1": 29586, "1.0.rc2": 29636, "1.0": 29733, "1.0.2": 30500, "1.1.0rc1": 31120, "1.1.0": 31184, "1.1.2": 31927, "1.1.3": 32291, "1.2.0rc1": 32454, "1.2.0": 32499, "1.2.1": 32770, "1.2.2": 32984, "1.3.0rc1": 33376, "1.3.0": 33504}, "pages": [["", "Grid view", "Display as a agrid"], ["summarylist", "List view", "Display as a list"], ["regressions", "Show regressions", "Display information about recent regressions"]]} \ No newline at end of file diff --git a/info.json b/info.json index f2a3e1e0a7..2f860eec88 100644 --- a/info.json +++ b/info.json @@ -1,4 +1,4 @@ { "asv-version": "0.6.1", - "timestamp": 1698360478606 + "timestamp": 1698446953889 } \ No newline at end of file diff --git a/regressions.json b/regressions.json index 8ede413f90..515a853f2f 100644 --- a/regressions.json +++ b/regressions.json @@ -1 +1 @@ -{"regressions": [["cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 0, 0.13430951849989015, 0.09576546900007088, [[33031, 33040, 0.09576546900007088, 0.13430951849989015]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.13418976350010325, 0.09606840549997742, [[33031, 33040, 0.09606840549997742, 0.13418976350010325]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 10, 3.3947032634996503, 2.786043321500074, [[null, 32881, 2.786043321500074, 3.3947032634996503]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 11, 5.619692420999854, 2.1219118814997273, [[null, 32881, 2.1219118814997273, 5.619692420999854]]], ["model_selection.CrossValidationBenchmark.peakmem_crossval(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.peakmem_crossval.json", {"python": "3.8", "cython": ""}, 1, 130850816.0, 123015168.0, [[null, 32198, 123015168.0, 125816832.0]]], ["cluster.KMeansBenchmark.peakmem_transform('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 141039616.0, 133468160.0, [[null, 32198, 133468160.0, 135958528.0]]], ["cluster.KMeansBenchmark.peakmem_transform('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 140912640.0, 133468160.0, [[null, 32198, 133468160.0, 135995392.0]]], ["cluster.KMeansBenchmark.peakmem_transform('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 141043712.0, 133459968.0, [[null, 32198, 133459968.0, 136044544.0]]], ["cluster.KMeansBenchmark.peakmem_transform('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 140982272.0, 133443584.0, [[null, 32198, 133443584.0, 135970816.0]]], ["cluster.KMeansBenchmark.peakmem_transform('sparse', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 4, 140716032.0, 129863680.0, [[32294, 32303, 132198400.0, 135419904.0]]], ["cluster.KMeansBenchmark.peakmem_transform('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 5, 140716032.0, 129863680.0, [[32294, 32303, 132198400.0, 135419904.0]]], ["cluster.KMeansBenchmark.peakmem_transform('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 6, 140716032.0, 129863680.0, [[32294, 32303, 132198400.0, 135419904.0]]], ["cluster.KMeansBenchmark.peakmem_transform('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 7, 140716032.0, 129863680.0, [[32294, 32303, 132198400.0, 135419904.0]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 5, 2.4938819634999163, 1.9416651550000097, [[32651, 32838, 1.9416651550000097, 2.4938819634999163]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 7, 8.892551909000758, 5.197582111500196, [[32651, 32838, 5.197582111500196, 8.892551909000758]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 11, 8.846687373999885, 5.187773386998742, [[32651, 32838, 5.187773386998742, 8.846687373999885]]], ["linear_model.ElasticNetBenchmark.peakmem_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 135835648.0, 128327680.0, [[null, 32198, 128327680.0, 130998272.0]]], ["ensemble.GradientBoostingClassifierBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 4.864555561500083, 3.04781713400007, [[32432, 32572, 3.04781713400007, 4.864555561500083]]], ["linear_model.LassoBenchmark.time_fit('dense', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 1.4256798984999932, 1.2750800849998996, [[32651, 32838, 1.2750800849998996, 1.4256798984999932]]], ["linear_model.LassoBenchmark.time_fit('dense', False)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.6213949935001892, 1.4736898109999856, [[32651, 32838, 1.4736898109999856, 1.6213949935001892]]], ["manifold.TSNEBenchmark.peakmem_fit('exact')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/manifold.TSNEBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 113817600.0, 104988672.0, [[32294, 32303, 108363776.0, 112087040.0]]], ["manifold.TSNEBenchmark.peakmem_fit('barnes_hut')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/manifold.TSNEBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 120670208.0, 111697920.0, [[null, 32198, 111697920.0, 114991104.0]]], ["model_selection.CrossValidationBenchmark.time_crossval(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.time_crossval.json", {"python": "3.8", "cython": ""}, 0, 84.81582076599989, 43.90737086200079, [[32432, 32572, 43.90737086200079, 84.81582076599989]]], ["model_selection.CrossValidationBenchmark.time_crossval(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.time_crossval.json", {"python": "3.8", "cython": ""}, 1, 25.012438464999832, 13.38686093599972, [[32411, 32420, 13.38686093599972, 21.806337958000768], [32580, 32588, 21.806337958000768, 25.012438464999832]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 120133632.0, 112246784.0, [[null, 32198, 112246784.0, 115359744.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 111405056.0, 103583744.0, [[null, 32198, 103583744.0, 106188800.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 95678464.0, 87138304.0, [[32294, 32303, 90152960.0, 93949952.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 97529856.0, 89346048.0, [[32294, 32303, 92061696.0, 96141312.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 5, 134678528.0, 126783488.0, [[null, 32198, 126783488.0, 129425408.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 6, 119717888.0, 107761664.0, [[32294, 32303, 110923776.0, 114593792.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 7, 120035328.0, 108300288.0, [[32294, 32303, 108300288.0, 118687744.0]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 0, -4.109885215759277, -5.011288642883301, [[33050, 33057, -5.011288642883301, -4.109886169433594], [33211, 33213, -4.109886169433594, -4.109885215759277]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 1, -3.077857732772827, -3.1141350269317627, [[33050, 33057, -3.1141350269317627, -3.0778582096099854], [33179, 33189, -3.0778582096099854, -3.0778582096099854]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 2, -4.109885215759277, -5.011288642883301, [[33050, 33057, -5.011288642883301, -4.109886169433594], [null, 33229, -4.109886169433594, -4.109885215759277]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 3, -3.0778582096099854, -3.1141350269317627, [[33050, 33057, -3.1141350269317627, -3.0778582096099854]]], ["cluster.KMeansBenchmark.track_test_score('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 5, -0.9249227643013, -0.9306698441505432, [[33050, 33057, -0.9306698441505432, -0.9249227643013]]], ["cluster.KMeansBenchmark.track_test_score('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 7, -0.9249262809753418, -0.930671751499176, [[33050, 33057, -0.9306698441505432, -0.9249262809753418]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.002980613333344688, 0.0026784809999753634, [[32649, 32651, 0.0026784809999753634, 0.002980613333344688]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.001904074000018833, 0.0016939145714656792, [[32213, 32218, 0.0016939145714656792, 0.001904074000018833]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 0.054224893999162305, 0.04985318950002693, [[32424, 32432, 0.04985318950002693, 0.054224893999162305]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 11, 0.03840343999854667, 0.03311949050021212, [[32424, 32432, 0.03311949050021212, 0.03840343999854667]]], ["linear_model.SGDRegressorBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 5.958662469000046, 3.880424359999779, [[32651, 32838, 3.880424359999779, 4.447991056999854], [33075, 33086, 4.447991056999854, 4.822892239999874], [33194, 33208, 4.822892239999874, 5.958662469000046]]], ["linear_model.SGDRegressorBenchmark.time_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 5.567558806999841, 1.343501784000182, [[32881, 32895, 1.343501784000182, 5.567558806999841]]], ["cluster.KMeansBenchmark.time_fit('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 2.2565097730000616, 1.9918717970000444, [[33050, 33057, 1.9918717970000444, 2.2565097730000616]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 107773952.0, 97619968.0, [[32294, 32303, 100749312.0, 104982528.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 107841536.0, 97685504.0, [[32294, 32303, 100941824.0, 105211904.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 113688576.0, 103673856.0, [[32294, 32303, 106737664.0, 111140864.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 113649664.0, 103677952.0, [[32294, 32303, 106741760.0, 111126528.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 4, 93020160.0, 84926464.0, [[32294, 32303, 87994368.0, 91623424.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 5, 96159744.0, 88256512.0, [[32294, 32303, 91013120.0, 94982144.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 6, 102901760.0, 94826496.0, [[32294, 32303, 97832960.0, 101521408.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 7, 106457088.0, 98553856.0, [[32294, 32303, 100913152.0, 105259008.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 8, 92801024.0, 84770816.0, [[32294, 32303, 87386112.0, 91441152.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 9, 95963136.0, 88084480.0, [[32294, 32303, 90542080.0, 94851072.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 10, 102443008.0, 94355456.0, [[32294, 32303, 97394688.0, 101095424.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 11, 106049536.0, 98168832.0, [[32294, 32303, 100644864.0, 104923136.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 106934272.0, 99745792.0, [[null, 32198, 99745792.0, 102088704.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 106383360.0, 99762176.0, [[null, 32198, 99762176.0, 101568512.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 107032576.0, 99667968.0, [[null, 32198, 99667968.0, 102084608.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 106647552.0, 99868672.0, [[null, 32198, 99868672.0, 101769216.0]]], ["linear_model.LogisticRegressionBenchmark.time_fit('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 5.119495814999937, 3.6039345849999336, [[32432, 32572, 3.6039345849999336, 5.119495814999937]]], ["linear_model.LogisticRegressionBenchmark.time_fit('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 5.222811944999648, 3.462408609000022, [[32432, 32572, 3.462408609000022, 5.222811944999648]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 3.795173198499924, 2.901297688500108, [[32432, 32572, 2.901297688500108, 3.795173198499924]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 7, 4.10541693200048, 2.99407483899995, [[32432, 32572, 2.99407483899995, 4.10541693200048]]], ["cluster.MiniBatchKMeansBenchmark.track_test_score('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 2, -0.9366871118545532, -0.9376848340034485, [[33050, 33057, -0.9376848340034485, -0.9366871118545532]]], ["cluster.MiniBatchKMeansBenchmark.track_test_score('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 3, -0.9386959075927734, -0.9521117806434631, [[33050, 33057, -0.9521117806434631, -0.9386959075927734]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 89192448.0, 80896000.0, [[32294, 32303, 83898368.0, 87613440.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 89192448.0, 80891904.0, [[32294, 32303, 83894272.0, 87605248.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 92465152.0, 84221952.0, [[32294, 32303, 87355392.0, 91029504.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 92469248.0, 84226048.0, [[32294, 32303, 87306240.0, 91033600.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 4, 91398144.0, 83234816.0, [[32294, 32303, 86237184.0, 89958400.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 5, 91406336.0, 83247104.0, [[32294, 32303, 86237184.0, 89960448.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 6, 100026368.0, 91869184.0, [[32294, 32303, 94842880.0, 98586624.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 7, 100026368.0, 91869184.0, [[32294, 32303, 94842880.0, 98586624.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 8, 91361280.0, 83218432.0, [[32294, 32303, 86245376.0, 89929728.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 9, 91355136.0, 83218432.0, [[32294, 32303, 86437888.0, 89929728.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 10, 99780608.0, 91643904.0, [[32294, 32303, 94646272.0, 98338816.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 11, 99780608.0, 91643904.0, [[32294, 32303, 94646272.0, 98338816.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 106211328.0, 98676736.0, [[null, 32198, 98676736.0, 101310464.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 105893888.0, 98840576.0, [[32294, 32303, 100823040.0, 104460288.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 106115072.0, 98525184.0, [[null, 32198, 98525184.0, 101117952.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 105959424.0, 98955264.0, [[null, 32198, 98955264.0, 101011456.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 105529344.0, 98103296.0, [[null, 32198, 98103296.0, 100728832.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 105494528.0, 98109440.0, [[32193, 32197, 98109440.0, 100718592.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 121044992.0, 113606656.0, [[null, 32198, 113606656.0, 116293632.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 121044992.0, 113606656.0, [[null, 32198, 113606656.0, 116293632.0]]], ["svm.SVCBenchmark.time_fit('rbf')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 0.9007304115011721, 0.7037775400003738, [[32651, 32838, 0.7037775400003738, 0.9007304115011721]]], ["linear_model.LassoBenchmark.peakmem_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 108089344.0, 100954112.0, [[null, 32198, 100954112.0, 103546880.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 111282176.0, 103063552.0, [[null, 32198, 103063552.0, 106151936.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 111249408.0, 103026688.0, [[null, 32198, 103026688.0, 106123264.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 102078464.0, 93495296.0, [[32294, 32303, 96657408.0, 100253696.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 102035456.0, 93614080.0, [[32294, 32303, 96575488.0, 100253696.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 4, 112154624.0, 103952384.0, [[null, 32198, 103952384.0, 106954752.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 5, 112156672.0, 103952384.0, [[null, 32198, 103952384.0, 106954752.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 6, 99727360.0, 91521024.0, [[32294, 32303, 94703616.0, 98209792.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 7, 99735552.0, 91529216.0, [[32294, 32303, 94707712.0, 98209792.0]]], ["cluster.KMeansBenchmark.peakmem_fit('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 120840192.0, 112832512.0, [[null, 32198, 112832512.0, 115462144.0]]], ["cluster.KMeansBenchmark.peakmem_fit('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 135401472.0, 125513728.0, [[32294, 32303, 128184320.0, 131653632.0]]], ["cluster.KMeansBenchmark.peakmem_fit('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 156628992.0, 148451328.0, [[null, 32198, 148451328.0, 151097344.0]]], ["cluster.KMeansBenchmark.peakmem_fit('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 157786112.0, 149676032.0, [[null, 32198, 149676032.0, 152330240.0]]], ["cluster.KMeansBenchmark.peakmem_fit('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 6, 224722944.0, 213315584.0, [[null, 32198, 213315584.0, 215736320.0]]], ["model_selection.GridSearchBenchmark.peakmem_fit(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 106528768.0, 98037760.0, [[32294, 32303, 101011456.0, 104521728.0]]], ["model_selection.GridSearchBenchmark.peakmem_fit(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 104763392.0, 96858112.0, [[null, 32198, 96858112.0, 100007936.0]]], ["cluster.MiniBatchKMeansBenchmark.track_train_score('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 2, -0.9323447346687317, -0.9334458708763123, [[33050, 33057, -0.9334458708763123, -0.9323447346687317]]], ["cluster.MiniBatchKMeansBenchmark.track_train_score('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 3, -0.934399425983429, -0.9480265974998474, [[33050, 33057, -0.9480265974998474, -0.934399425983429]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 139159552.0, 131629056.0, [[null, 32198, 131629056.0, 134172672.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 139159552.0, 131719168.0, [[null, 32198, 131719168.0, 134193152.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 140017664.0, 129003520.0, [[32294, 32303, 131420160.0, 134772736.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 140017664.0, 128999424.0, [[32294, 32303, 131420160.0, 134760448.0]]], ["linear_model.ElasticNetBenchmark.time_fit('dense', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 1.4241585639999812, 1.2580682324999088, [[32651, 32838, 1.2580682324999088, 1.4241585639999812]]], ["linear_model.ElasticNetBenchmark.time_fit('dense', False)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.6408157220000703, 1.4637692859998879, [[32651, 32838, 1.4637692859998879, 1.6408157220000703]]], ["linear_model.ElasticNetBenchmark.time_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 2.737181770000234, 2.4433016624998345, [[null, 32409, 2.4433016624998345, 2.737181770000234]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 101578752.0, 94609408.0, [[null, 32198, 94609408.0, 97341440.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 111319040.0, 104300544.0, [[null, 32198, 104300544.0, 106926080.0]]], ["cluster.KMeansBenchmark.time_transform('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 0, 0.13446171199984747, 0.09999187950006672, [[33031, 33040, 0.09999187950006672, 0.13446171199984747]]], ["cluster.KMeansBenchmark.time_transform('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.13351594300002034, 0.09808573050008818, [[33031, 33040, 0.09808573050008818, 0.13351594300002034]]], ["cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 0.1336752395000076, 0.09787636049986759, [[33031, 33040, 0.09787636049986759, 0.1336752395000076]]], ["cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 3, 0.13355329900002744, 0.09772891250008797, [[33031, 33040, 0.09772891250008797, 0.13355329900002744]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 4, 3.9109639700000116, 3.642721819000144, [[32879, 32895, 3.642721819000144, 3.9109639700000116]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 5, 3.9039899700001115, 3.6996333510001023, [[32879, 32895, 3.6996333510001023, 3.9039899700001115]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 6, 3.900951019999866, 3.660172879000129, [[32879, 32895, 3.660172879000129, 3.900951019999866]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 7, 3.8940096110000013, 3.6817158400001517, [[32879, 32895, 3.6817158400001517, 3.8940096110000013]]], ["model_selection.GridSearchBenchmark.peakmem_predict(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 98850816.0, 91230208.0, [[32294, 32303, 94040064.0, 97390592.0]]], ["model_selection.GridSearchBenchmark.peakmem_predict(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 98838528.0, 91246592.0, [[32294, 32303, 94040064.0, 97390592.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 125505536.0, 117731328.0, [[null, 32198, 117731328.0, 120594432.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 124577792.0, 117481472.0, [[null, 32198, 117481472.0, 119992320.0]]], ["ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, null, 117735424.0, 110399488.0, [[null, 32198, 110399488.0, 113397760.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 108146688.0, 101130240.0, [[null, 32198, 101130240.0, 103452672.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 110882816.0, 102653952.0, [[32294, 32303, 105533440.0, 109289472.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_fit('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 138711040.0, 127209472.0, [[32294, 32303, 129851392.0, 133025792.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_fit('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 134176768.0, 126898176.0, [[null, 32198, 126898176.0, 129597440.0]]], ["linear_model.LassoBenchmark.peakmem_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 135835648.0, 128278528.0, [[null, 32198, 128278528.0, 130985984.0]]], ["ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, null, 105981952.0, 98271232.0, [[null, 32198, 98271232.0, 101003264.0]]], ["linear_model.ElasticNetBenchmark.peakmem_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 108079104.0, 100945920.0, [[null, 32198, 100945920.0, 103530496.0]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 11.385541180000018, 6.362006434000023, [[32432, 32572, 6.362006434000023, 11.385541180000018]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 3.595307277499842, 2.2652268890001324, [[32411, 32420, 2.2652268890001324, 3.595307277499842]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 0, -4.1075520515441895, -4.988476753234863, [[32424, 32432, -4.988476753234863, -4.988476276397705], [33050, 33057, -4.988476276397705, -4.1075520515441895]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 1, -3.0774285793304443, -3.1168856620788574, [[33050, 33057, -3.1168856620788574, -3.0774285793304443]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 2, -4.1075520515441895, -4.988476753234863, [[33050, 33057, -4.988476753234863, -4.1075520515441895]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 3, -3.0774285793304443, -3.1168856620788574, [[33050, 33057, -3.1168856620788574, -3.0774285793304443]]], ["cluster.KMeansBenchmark.track_train_score('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 5, -0.922096312046051, -0.9255540370941162, [[33050, 33057, -0.9255540370941162, -0.922096312046051]]], ["cluster.KMeansBenchmark.track_train_score('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 7, -0.9221000075340271, -0.9255544543266296, [[33050, 33057, -0.9255540370941162, -0.9221000075340271]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 103989248.0, 96636928.0, [[null, 32198, 96636928.0, 99500032.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 145133568.0, 137379840.0, [[null, 32198, 137379840.0, 140144640.0]]], ["cluster.KMeansBenchmark.peakmem_predict('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 107298816.0, 99885056.0, [[null, 32198, 99885056.0, 102500352.0]]], ["cluster.KMeansBenchmark.peakmem_predict('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 107274240.0, 99856384.0, [[null, 32198, 99856384.0, 102514688.0]]], ["cluster.KMeansBenchmark.peakmem_predict('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 107274240.0, 99885056.0, [[null, 32198, 99885056.0, 102514688.0]]], ["cluster.KMeansBenchmark.peakmem_predict('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 107274240.0, 99856384.0, [[null, 32198, 99856384.0, 102514688.0]]], ["cluster.KMeansBenchmark.peakmem_predict('sparse', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 4, 115148800.0, 107716608.0, [[null, 32198, 107716608.0, 110415872.0]]], ["cluster.KMeansBenchmark.peakmem_predict('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 5, 115148800.0, 107716608.0, [[null, 32198, 107716608.0, 110415872.0]]], ["cluster.KMeansBenchmark.peakmem_predict('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 6, 115148800.0, 107716608.0, [[null, 32198, 107716608.0, 110415872.0]]], ["cluster.KMeansBenchmark.peakmem_predict('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 7, 115148800.0, 107716608.0, [[null, 32198, 107716608.0, 110415872.0]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 0, 0.10278367200010052, 0.06730766499993024, [[29429, 29435, 0.06730766499993024, 0.0945217194999941], [29768, 29776, 0.0945217194999941, 0.10278367200010052]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.10242281449995971, 0.0678365380000514, [[29429, 29435, 0.0678365380000514, 0.09472550850011885], [29768, 29776, 0.09472550850011885, 0.10242281449995971]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 6.944649688499908, 5.944078384000022, [[29429, 29435, 5.944078384000022, 6.944649688499908]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 3, 6.9146122589999095, 5.989741488999925, [[29429, 29435, 5.989741488999925, 6.9146122589999095]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'cosine', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 0, 1.0816761809992386, 0.6492327094999837, [[29429, 29435, 0.6492327094999837, 1.0816761809992386]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'cosine', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 1, 1.1749681209994378, 0.9846832859998358, [[29768, 29776, 1.0704449280001427, 1.1749681209994378]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'euclidean', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 2, 1.6267482870002823, 1.131574778999493, [[29768, 29776, 1.511747548999665, 1.6267482870002823]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'euclidean', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 3, 2.8029338409996853, 2.0952009089996864, [[29429, 29435, 2.0952009089996864, 2.6413094899999123], [29768, 29776, 2.6413094899999123, 2.8029338409996853]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'manhattan', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 5, 3.2750708539997504, 1.5104139889999715, [[29429, 29435, 1.5104139889999715, 2.665036097999291], [29572, 29591, 2.665036097999291, 3.2750708539997504]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'correlation', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 7, 2.6057268360000307, 1.5212544939995496, [[29429, 29435, 1.5212544939995496, 2.6057268360000307]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 8, 3.7114240050000262, 3.227034360000289, [[29429, 29435, 3.227034360000289, 3.7114240050000262]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 9, 2.6670874330002334, 1.367151794000165, [[29429, 29435, 1.394243098500283, 2.500172876000306], [29768, 29776, 2.500172876000306, 2.6670874330002334]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 10, 2.613872798000557, 2.1499179414995524, [[29429, 29435, 2.1499179414995524, 2.613872798000557]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 11, 2.116926750499715, 1.0954036029997951, [[29429, 29435, 1.0954036029997951, 1.9836563979997663], [29776, 29783, 1.9836563979997663, 2.116926750499715]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'manhattan', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 13, 1.3542568210000354, 1.0587421519994678, [[29429, 29435, 1.0587421519994678, 1.3542568210000354]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 0, -0.07244396209716797, -0.0724489969415666, [[30002, 30010, -0.0724489969415666, -0.07244396209716797]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 1, -0.07244398094095815, -0.0724489969415666, [[30002, 30010, -0.0724489969415666, -0.07244398094095815]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 2, -0.0724455937743187, -0.07246800406583326, [[28497, 29215, -0.07246800406583326, -0.0724455937743187]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 3, -0.07244561411419302, -0.072468004065939, [[28497, 29215, -0.072468004065939, -0.07244563316074562], [30665, 30670, -0.07244563316074562, -0.07244561411419302]]], ["linear_model.LinearRegressionBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LinearRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 3.1949284400000124, 1.0697697784996762, [[28497, 29215, 1.0697697784996762, 1.1204848459997265], [30890, 30904, 2.2272244540001793, 3.1949284400000124]]], ["linear_model.LinearRegressionBenchmark.time_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LinearRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.5362763814998743, 0.5499250379998557, [[29429, 29435, 0.5888377334999859, 1.201512325000067], [30890, 30904, 1.3145294084997659, 1.5362763814998743]]], ["model_selection.CrossValidationBenchmark.peakmem_crossval(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.peakmem_crossval.json", {"python": "3.8", "cython": ""}, 0, 222187520.0, 208627712.0, [[31041, 32090, 210403328.0, 222187520.0]]], ["model_selection.CrossValidationBenchmark.peakmem_crossval(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.peakmem_crossval.json", {"python": "3.8", "cython": ""}, 1, 122601472.0, 109465600.0, [[31041, 32090, 110780416.0, 122601472.0]]], ["cluster.MiniBatchKMeansBenchmark.time_fit('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 0.34298792899994623, 0.2601930060000086, [[29429, 29435, 0.2601930060000086, 0.3001380919999974]]], ["cluster.MiniBatchKMeansBenchmark.time_fit('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 0.36076429649995134, 0.2681720820000919, [[29768, 29776, 0.3065479290000894, 0.36076429649995134]]], ["cluster.MiniBatchKMeansBenchmark.time_fit('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 1.648156553999911, 1.0463895640000374, [[29429, 29435, 1.0463895640000374, 1.648156553999911]]], ["metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'cosine', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json", {"python": "3.8", "cython": ""}, 1, 995737600.0, 881528832.0, [[29443, 29446, 881528832.0, 995737600.0]]], ["metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'manhattan', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json", {"python": "3.8", "cython": ""}, 4, 257814528.0, 244285440.0, [[30145, 30155, 245489664.0, 245960704.0]]], ["metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'correlation', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json", {"python": "3.8", "cython": ""}, 6, 251781120.0, 237273088.0, [[31041, 32090, 239529984.0, 251781120.0]]], ["metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'manhattan', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json", {"python": "3.8", "cython": ""}, 12, 195002368.0, 181387264.0, [[31041, 32090, 182956032.0, 195002368.0]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 4, 0.941246193000552, 0.6924204100005227, [[29429, 29435, 0.7239697439999873, 0.941246193000552]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 5, 2.5587522334990354, 0.7722874989995034, [[29429, 29435, 0.8071847430001071, 1.625175291999767], [29768, 29776, 1.625175291999767, 2.5587522334990354]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 6, 8.099321813000643, 5.71836935400006, [[29429, 29435, 6.1424575720002395, 8.099321813000643]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 7, 9.311504750001404, 5.3428612119996615, [[29768, 29776, 5.3428612119996615, 9.311504750001404]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 8, 1.8560742700001356, 1.259906507499636, [[29429, 29435, 1.3675167944993518, 1.8560742700001356]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 10, 7.459379219500079, 5.234896867999851, [[29429, 29435, 5.234896867999851, 7.459379219500079]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 11, 10.010013914999945, 4.5771756980002465, [[29768, 29776, 4.5771756980002465, 10.010013914999945]]], ["linear_model.ElasticNetBenchmark.peakmem_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 128458752.0, 115314688.0, [[31041, 32090, 116367360.0, 128458752.0]]], ["decomposition.PCABenchmark.time_fit('full')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 1.9829450105000888, 1.1255870280000408, [[29429, 29435, 1.1255870280000408, 1.8539050950003002]]], ["decomposition.PCABenchmark.time_fit('arpack')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.1924363670000275, 1.0004457000000002, [[29776, 29783, 1.0004457000000002, 1.1924363670000275]]], ["ensemble.GradientBoostingClassifierBenchmark.time_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 12.053724431999854, 4.695657648499946, [[29429, 29435, 4.695657648499946, 12.053724431999854]]], ["linear_model.LassoBenchmark.time_fit('dense', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 1.3532190169999012, 0.7728853464998338, [[29425, 29429, 0.7728853464998338, 1.283576799499997]]], ["linear_model.LassoBenchmark.time_fit('dense', False)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.5789366555000015, 0.8136002810001628, [[29429, 29435, 0.8136002810001628, 1.4818555120002657], [29783, 29788, 1.4818555120002657, 1.5789366555000015]]], ["manifold.TSNEBenchmark.peakmem_fit('exact')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/manifold.TSNEBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 99151872.0, 85667840.0, [[31041, 32090, 86941696.0, 99151872.0]]], ["svm.SVCBenchmark.time_predict('linear')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.7379378209989227, 0.4336090870001499, [[29768, 29776, 0.4336090870001499, 0.7379378209989227]]], ["svm.SVCBenchmark.time_predict('poly')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.7377982245006933, 0.4378497059988149, [[29768, 29776, 0.4378497059988149, 0.7377982245006933]]], ["svm.SVCBenchmark.time_predict('sigmoid')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.736312139999427, 0.43831788200077426, [[29768, 29776, 0.43831788200077426, 0.736312139999427]]], ["decomposition.DictionaryLearningBenchmark.track_train_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 0, -0.07231885939836502, -0.07231886145768542, [[29808, 29813, -0.07231886145768542, -0.07231886144906298], [30028, 30035, -0.07231886144906298, -0.07231886144287691], [null, 30502, -0.07231886144287691, -0.07231885939836502]]], ["decomposition.DictionaryLearningBenchmark.track_train_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 1, -0.07231886145064417, -0.07231886146221082, [[30028, 30035, -0.07231886146221082, -0.07231886145064417]]], ["decomposition.DictionaryLearningBenchmark.track_train_score('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 2, -0.07231885939836502, -0.07231886156090023, [[30028, 30035, -0.07231886156090023, -0.07231886156066476], [null, 30502, -0.07231886156066476, -0.07231885939836502]]], ["decomposition.DictionaryLearningBenchmark.time_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.33597187700001996, 0.21053998650006633, [[29429, 29435, 0.21053998650006633, 0.33597187700001996]]], ["decomposition.DictionaryLearningBenchmark.time_transform('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 0.3605742634999842, 0.17617045400004372, [[28497, 29215, 0.17629199900000003, 0.17617045400004372]]], ["decomposition.DictionaryLearningBenchmark.time_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 3, 0.33594549300005383, 0.21017575449991455, [[29429, 29435, 0.21017575449991455, 0.33594549300005383]]], ["decomposition.PCABenchmark.time_transform('full')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 0, 0.1835508125002434, 0.09774972349998734, [[29429, 29435, 0.09774972349998734, 0.1755720655000914]]], ["decomposition.PCABenchmark.time_transform('arpack')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.1826529350000783, 0.08935556799997357, [[29371, 29376, 0.08935556799997357, 0.09930157899998449], [29429, 29435, 0.09930157899998449, 0.17445163200000025]]], ["decomposition.PCABenchmark.time_transform('randomized')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 0.1826093990002846, 0.09633852199999637, [[29429, 29435, 0.09633852199999637, 0.1746349420000115]]], ["model_selection.CrossValidationBenchmark.time_crossval(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.time_crossval.json", {"python": "3.8", "cython": ""}, 1, 13.437568640999416, 11.55077611500019, [[29429, 29435, 11.55077611500019, 13.437568640999416]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 103350272.0, 90861568.0, [[31041, 32090, 92123136.0, 103350272.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 87556096.0, 74616832.0, [[31041, 32090, 76148736.0, 87556096.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 89333760.0, 75927552.0, [[31041, 32090, 77529088.0, 89333760.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 4, 561745920.0, 522616832.0, [[29572, 29591, 522616832.0, 541575168.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 5, 126636032.0, 113799168.0, [[31041, 32090, 115187712.0, 126636032.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 6, 108130304.0, 95338496.0, [[31041, 32090, 96980992.0, 108130304.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 7, 108695552.0, 95617024.0, [[31041, 32090, 97185792.0, 108695552.0]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.25424427599978117, 0.19696048499986318, [[29429, 29435, 0.19696048499986318, 0.25424427599978117]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.15377317899992704, 0.06864178599994375, [[29429, 29435, 0.06864178599994375, 0.13039021200006573], [29776, 29783, 0.13039021200006573, 0.15377317899992704]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('sparse', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 1.8535161529998732, 1.2419844685000498, [[29429, 29435, 1.2419844685000498, 1.8535161529998732]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('sparse', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.7554132919999574, 0.32528277099982006, [[29429, 29435, 0.32528277099982006, 0.6583188555000561], [29768, 29776, 0.6583188555000561, 0.7554132919999574]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.0037360741666816466, 0.0033110036667191407, [[29768, 29776, 0.0033110036667191407, 0.0037360741666816466]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.003479095833275399, 0.0029587079999942034, [[29742, 29750, 0.0029587079999942034, 0.003479095833275399]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.002068962900011684, 0.0015545652500274323, [[29429, 29435, 0.0015545652500274323, 0.002068962900011684]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.002073254599872598, 0.001594828666649543, [[29429, 29435, 0.001594828666649543, 0.002073254599872598]]], ["linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 4, 0.008229826249930738, 0.006104737249984282, [[29425, 29429, 0.006104737249984282, 0.008229826249930738]]], ["linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 5, 0.010718544499923155, 0.006156468000085624, [[29429, 29435, 0.006156468000085624, 0.010718544499923155]]], ["linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 6, 0.006497366000075999, 0.0031171457500249744, [[29429, 29435, 0.0031171457500249744, 0.006497366000075999]]], ["linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 7, 0.006472251249988403, 0.003108011125050325, [[29429, 29435, 0.003108011125050325, 0.006472251249988403]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 0.0013805179999378326, 0.0007659814285554083, [[29429, 29435, 0.0007688613571385108, 0.0013130286249634082], [29768, 29776, 0.0013130286249634082, 0.0013805179999378326]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 0.0013767745000829261, 0.0007682408928368595, [[29429, 29435, 0.0007682408928368595, 0.0009858626363810881], [30545, 30550, 0.0009858626363810881, 0.0013767745000829261]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 0.0015072048333119406, 0.000974174045454261, [[29429, 29435, 0.000974174045454261, 0.0015072048333119406]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 0.001758898749964525, 0.0009750611363663418, [[29429, 29435, 0.0009750611363663418, 0.001758898749964525]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 9, 0.012407672000335879, 0.007881215499992322, [[29429, 29435, 0.007881215499992322, 0.008835557749989675], [30945, 30949, 0.008835557749989675, 0.012407672000335879]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 10, 0.033569565499419696, 0.029447855500166042, [[29429, 29435, 0.029447855500166042, 0.033569565499419696]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 11, 0.03338413749952451, 0.02946141600023111, [[29429, 29435, 0.02946141600023111, 0.03338413749952451]]], ["linear_model.SGDRegressorBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 3.6811428874998455, 2.868250787000079, [[29429, 29435, 2.868250787000079, 3.6811428874998455]]], ["cluster.KMeansBenchmark.time_fit('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 2.6487308000000667, 1.555339187999948, [[29768, 29776, 1.8251347794999333, 2.6487308000000667]]], ["svm.SVCBenchmark.peakmem_predict('linear')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 214925312.0, 201424896.0, [[31041, 32090, 203014144.0, 214925312.0]]], ["svm.SVCBenchmark.peakmem_predict('poly')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 214925312.0, 201424896.0, [[31041, 32090, 203014144.0, 214925312.0]]], ["svm.SVCBenchmark.peakmem_predict('rbf')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 214925312.0, 201451520.0, [[31041, 32090, 203014144.0, 214925312.0]]], ["svm.SVCBenchmark.peakmem_predict('sigmoid')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 214925312.0, 201424896.0, [[31041, 32090, 203014144.0, 214925312.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 4, 85250048.0, 71094272.0, [[31041, 32090, 72650752.0, 85250048.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 5, 88010752.0, 74592256.0, [[31041, 32090, 76038144.0, 88010752.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 6, 95232000.0, 81330176.0, [[31041, 32090, 82948096.0, 95232000.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 7, 98312192.0, 81231872.0, [[31041, 32090, 82960384.0, 98312192.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 8, 85028864.0, 70955008.0, [[31041, 32090, 72501248.0, 85028864.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 9, 87773184.0, 74440704.0, [[31041, 32090, 75870208.0, 87773184.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 10, 94744576.0, 80932864.0, [[31041, 32090, 82599936.0, 94744576.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 11, 97861632.0, 81006592.0, [[31041, 32090, 82552832.0, 97861632.0]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 0, -0.07475552707910538, -0.07475553179776506, [[null, 30502, -0.07475553179776506, -0.07475552707910538]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 1, -0.07475553052041055, -0.07475553176565611, [[29808, 29813, -0.07475553176565611, -0.07475553081876116], [30028, 30035, -0.07475553081876116, -0.07475553052041055]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 2, -0.07475553452968597, -0.07475553497618004, [[30028, 30035, -0.07475553497618004, -0.07475553497247069], [null, 30502, -0.07475553497247069, -0.07475553452968597]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 100106240.0, 88055808.0, [[31041, 32090, 88055808.0, 100106240.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 99553280.0, 87676928.0, [[31041, 32090, 87676928.0, 99553280.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 99844096.0, 87941120.0, [[31041, 32090, 87941120.0, 99844096.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 99913728.0, 87957504.0, [[31041, 32090, 87957504.0, 99913728.0]]], ["linear_model.ElasticNetBenchmark.time_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.002437477200010108, 0.002127209099990068, [[29776, 29783, 0.002127209099990068, 0.002437477200010108]]], ["ensemble.GradientBoostingClassifierBenchmark.time_predict('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.056121019500096736, 0.04575886599991463, [[29429, 29435, 0.04575886599991463, 0.056121019500096736]]], ["ensemble.GradientBoostingClassifierBenchmark.time_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.05286075050003092, 0.03754658399998334, [[29429, 29435, 0.03754658399998334, 0.05286075050003092]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 4, 10.377584896999906, 5.7189132469998185, [[29429, 29435, 5.7189132469998185, 8.790683242999876], [30679, 30694, 9.405624714999703, 10.377584896999906]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 5, 12.635107517999131, 6.988539030500306, [[29429, 29435, 6.988539030500306, 11.869692158999896]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 2.75509055800012, 1.852105071500091, [[29429, 29435, 1.852105071500091, 2.75509055800012]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 7, 3.0337587310000345, 1.8472522849999677, [[29429, 29435, 1.8472522849999677, 3.0337587310000345]]], ["cluster.MiniBatchKMeansBenchmark.track_test_score('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 0, -3.940943717956543, -5.135444641113281, [[28497, 29215, -5.135444641113281, -3.940943717956543]]], ["cluster.MiniBatchKMeansBenchmark.track_test_score('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 1, -3.108213186264038, -3.1083624362945557, [[28497, 29215, -3.1083624362945557, -3.108213186264038]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 80945152.0, 67645440.0, [[31041, 32090, 69120000.0, 80945152.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 80949248.0, 67649536.0, [[31041, 32090, 69120000.0, 80949248.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 84459520.0, 71041024.0, [[31041, 32090, 72617984.0, 84459520.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 84443136.0, 71036928.0, [[31041, 32090, 72622080.0, 84443136.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 4, 83550208.0, 70078464.0, [[31041, 32090, 71768064.0, 83550208.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 5, 83550208.0, 70086656.0, [[31041, 32090, 71755776.0, 83550208.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 6, 92094464.0, 78336000.0, [[31041, 32090, 79966208.0, 92094464.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 7, 92094464.0, 78336000.0, [[31041, 32090, 79966208.0, 92094464.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 8, 83517440.0, 70066176.0, [[31041, 32090, 71716864.0, 83517440.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 9, 83517440.0, 70062080.0, [[31041, 32090, 71725056.0, 83517440.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 10, 91856896.0, 78139392.0, [[31041, 32090, 79757312.0, 91856896.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 11, 91856896.0, 78139392.0, [[31041, 32090, 79757312.0, 91856896.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 99069952.0, 86284288.0, [[31041, 32090, 87101440.0, 99069952.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 99373056.0, 86315008.0, [[31041, 32090, 86843392.0, 99373056.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 98844672.0, 86226944.0, [[31041, 32090, 86906880.0, 98844672.0]]], ["cluster.MiniBatchKMeansBenchmark.time_predict('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.011599520000004304, 0.007076670499998272, [[29429, 29435, 0.007076670499998272, 0.009678551000092739], [30002, 30010, 0.009678551000092739, 0.011599520000004304]]], ["cluster.MiniBatchKMeansBenchmark.time_predict('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.01003910399998631, 0.007175752499961163, [[29429, 29435, 0.007175752499961163, 0.008954720500014446], [29768, 29776, 0.008954720500014446, 0.01003910399998631]]], ["cluster.MiniBatchKMeansBenchmark.time_predict('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.04333704450004916, 0.02026937499988435, [[null, 29454, 0.02026937499988435, 0.04333704450004916]]], ["cluster.MiniBatchKMeansBenchmark.time_predict('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.04323968300002434, 0.020301649000089128, [[29443, 29446, 0.020301649000089128, 0.04323968300002434]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 98217984.0, 87117824.0, [[31041, 32090, 88268800.0, 98217984.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 98213888.0, 87093248.0, [[31041, 32090, 88244224.0, 98213888.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 113737728.0, 101203968.0, [[31041, 32090, 102363136.0, 113737728.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 113737728.0, 101203968.0, [[31041, 32090, 102363136.0, 113737728.0]]], ["svm.SVCBenchmark.time_fit('linear')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 0.9549204214999918, 0.6676248109997687, [[29768, 29776, 0.6676248109997687, 0.9549204214999918]]], ["svm.SVCBenchmark.time_fit('poly')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 0.9526650339994376, 0.6656067194999196, [[29768, 29776, 0.6697120789995097, 0.9526650339994376]]], ["svm.SVCBenchmark.time_fit('rbf')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 0.955368300000373, 0.6764446990000579, [[null, 29294, 0.6961092275000738, 0.6764446990000579]]], ["svm.SVCBenchmark.time_fit('sigmoid')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 0.9532537739996769, 0.6729825549991801, [[null, 29551, 0.8879308570003559, 0.6729825549991801]]], ["linear_model.LassoBenchmark.peakmem_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 100855808.0, 87793664.0, [[31041, 32090, 89329664.0, 100855808.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 103108608.0, 90646528.0, [[31041, 32090, 92213248.0, 103108608.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 93667328.0, 81596416.0, [[31041, 32090, 82665472.0, 93667328.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 93736960.0, 81616896.0, [[31041, 32090, 82776064.0, 93736960.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 4, 104148992.0, 91480064.0, [[31041, 32090, 92934144.0, 104148992.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 5, 104144896.0, 91471872.0, [[31041, 32090, 92934144.0, 104144896.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 6, 91873280.0, 79282176.0, [[31041, 32090, 80656384.0, 91873280.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 7, 91877376.0, 79286272.0, [[31041, 32090, 80662528.0, 91877376.0]]], ["linear_model.LassoBenchmark.time_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.0028186511249828072, 0.00211358219999056, [[29429, 29435, 0.00211358219999056, 0.0028186511249828072]]], ["linear_model.SGDRegressorBenchmark.peakmem_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 96911360.0, 83673088.0, [[31041, 32090, 85041152.0, 96911360.0]]], ["manifold.TSNEBenchmark.time_fit('exact')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/manifold.TSNEBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 11.320914042999902, 5.088630448500226, [[29429, 29435, 5.088630448500226, 11.320914042999902]]], ["ensemble.HistGradientBoostingClassifierBenchmark.time_fit", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, null, 2.5009271564999835, 1.879087534999826, [[null, 29415, 1.879087534999826, 2.1288411184998495]]], ["model_selection.GridSearchBenchmark.time_fit(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 76.34837349199915, 66.27560593599992, [[29429, 29435, 66.27560593599992, 76.34837349199915]]], ["model_selection.GridSearchBenchmark.peakmem_fit(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 98156544.0, 84082688.0, [[31041, 32090, 86249472.0, 98156544.0]]], ["model_selection.GridSearchBenchmark.peakmem_fit(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 97107968.0, 83275776.0, [[31041, 32090, 84750336.0, 97107968.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 0, 0.35336302799987607, 0.14268698000000768, [[29429, 29435, 0.14472420250001505, 0.21666642600007435], [null, 30502, 0.21666642600007435, 0.35336302799987607]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.33678162400019573, 0.19031749699990996, [[29429, 29435, 0.19031749699990996, 0.2791712099999586], [null, 30502, 0.2791712099999586, 0.33678162400019573]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 0.34903030400028, 0.14430166950000967, [[null, 30502, 0.21973356249986864, 0.34903030400028]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 3, 0.3328575200002888, 0.18915657349998583, [[29429, 29435, 0.18915657349998583, 0.2806294154997886], [null, 30260, 0.2806294154997886, 0.3328575200002888]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'auto')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 0.1839239480004835, 0.16990794200000892, [[29768, 29776, 0.16990794200000892, 0.1839239480004835]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'svd')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 0.9384877170004984, 0.7077082870000595, [[29429, 29435, 0.7077082870000595, 0.8721067125002264], [29768, 29776, 0.8721067125002264, 0.9384877170004984]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'cholesky')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 0.1816674939996119, 0.16969983799981492, [[29768, 29776, 0.16969983799981492, 0.1816674939996119]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'sparse_cg')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 4, 0.20515116199931072, 0.17772288449987172, [[29768, 29776, 0.17772288449987172, 0.20515116199931072]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'saga')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 8.221493384000496, 6.566381228500177, [[29429, 29435, 6.566381228500177, 8.221493384000496]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'auto')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 7, 0.12927607850042477, 0.10852525499990406, [[29429, 29435, 0.10852525499990406, 0.12927607850042477]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'cholesky')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 9, 5.194330158999946, 4.426838388500073, [[29429, 29435, 4.426838388500073, 5.194330158999946]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'lsqr')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 10, 0.1145862319999651, 0.0909436879999248, [[29429, 29435, 0.0909436879999248, 0.11134417650009709]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'sparse_cg')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 11, 0.12983924199988905, 0.10884381050004777, [[29429, 29435, 0.10884381050004777, 0.12983924199988905]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'saga')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 13, 1.2060327659992254, 0.9948669144998803, [[29429, 29435, 0.9948669144998803, 1.2060327659992254]]], ["cluster.KMeansBenchmark.time_predict('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.009837056000037592, 0.007327421500008313, [[29429, 29435, 0.007327421500008313, 0.008976847250011133]]], ["cluster.KMeansBenchmark.time_predict('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.009865871750037059, 0.007280855499999461, [[29429, 29435, 0.007280855499999461, 0.009061120000012579]]], ["cluster.KMeansBenchmark.time_predict('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 5, 0.03096969550006179, 0.019307464000007712, [[null, 30156, 0.019307464000007712, 0.03096969550006179]]], ["cluster.KMeansBenchmark.time_predict('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 7, 0.03092300699995576, 0.01521101999998109, [[29790, 29795, 0.016851793499995438, 0.03092300699995576]]], ["cluster.MiniBatchKMeansBenchmark.track_train_score('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 0, -3.95550537109375, -5.140804767608643, [[28497, 29215, -5.140804767608643, -3.95550537109375]]], ["cluster.MiniBatchKMeansBenchmark.track_train_score('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 1, -3.1156556606292725, -3.1158313751220703, [[28497, 29215, -3.1158313751220703, -3.1156556606292725]]], ["svm.SVCBenchmark.peakmem_fit('linear')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 280915968.0, 266887168.0, [[29572, 29591, 266887168.0, 268001280.0]]], ["svm.SVCBenchmark.peakmem_fit('poly')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 280920064.0, 266878976.0, [[29572, 29591, 266878976.0, 268001280.0]]], ["svm.SVCBenchmark.peakmem_fit('rbf')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 280928256.0, 266878976.0, [[29572, 29591, 266878976.0, 267997184.0]]], ["svm.SVCBenchmark.peakmem_fit('sigmoid')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 280907776.0, 266878976.0, [[29572, 29591, 266878976.0, 267997184.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 131710976.0, 118521856.0, [[31041, 32090, 120074240.0, 131710976.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 131584000.0, 118448128.0, [[31041, 32090, 120064000.0, 131584000.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 129400832.0, 115208192.0, [[31041, 32090, 116719616.0, 129400832.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 129404928.0, 115171328.0, [[31041, 32090, 116727808.0, 129404928.0]]], ["model_selection.GridSearchBenchmark.time_predict(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.07944053849996635, 0.04805837400044766, [[29429, 29435, 0.04805837400044766, 0.061927900000227964], [29795, 29798, 0.061927900000227964, 0.07944053849996635]]], ["model_selection.GridSearchBenchmark.time_predict(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.07940275800001473, 0.04805780200013032, [[29429, 29435, 0.04805780200013032, 0.06160099299995636], [29795, 29798, 0.06160099299995636, 0.07940275800001473]]], ["linear_model.ElasticNetBenchmark.time_fit('dense', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 1.3423465609998857, 0.8082962149997002, [[29425, 29429, 0.8082962149997002, 1.3423465609998857]]], ["linear_model.ElasticNetBenchmark.time_fit('dense', False)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.5426730259998749, 0.8214312485001756, [[29425, 29429, 0.8214312485001756, 1.5426730259998749]]], ["ensemble.RandomForestClassifierBenchmark.peakmem_fit('sparse', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 415879168.0, 382615552.0, [[31041, 32090, 384073728.0, 415879168.0]]], ["ensemble.RandomForestClassifierBenchmark.peakmem_fit('sparse', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 583557120.0, 382621696.0, [[31041, 32090, 384073728.0, 583557120.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 94924800.0, 80715776.0, [[31041, 32090, 82552832.0, 94924800.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 104632320.0, 90421248.0, [[31041, 32090, 92262400.0, 104632320.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 12.15160157199989, 6.181946199000095, [[29429, 29435, 6.181946199000095, 10.234541518999777], [29776, 29783, 10.234541518999777, 11.299374638000018]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 12.2896960449998, 8.333827376000045, [[29429, 29435, 8.333827376000045, 12.2896960449998]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 3.436805663500081, 2.0184760459999325, [[29429, 29435, 2.0184760459999325, 3.436805663500081]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 10.596280627999931, 6.671095888499963, [[29429, 29435, 6.671095888499963, 10.596280627999931]]], ["cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 0.10267154099994968, 0.06435031950002212, [[29429, 29435, 0.06435031950002212, 0.09706874549999611], [29766, 29768, 0.09706874549999611, 0.10267154099994968]]], ["cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 3, 0.10241049249998468, 0.07129803300000503, [[29429, 29435, 0.07129803300000503, 0.10241049249998468]]], ["model_selection.GridSearchBenchmark.peakmem_predict(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 91131904.0, 77533184.0, [[31041, 32090, 79130624.0, 91131904.0]]], ["model_selection.GridSearchBenchmark.peakmem_predict(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 91131904.0, 77561856.0, [[31041, 32090, 79126528.0, 91131904.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 0, -0.07506927847862244, -0.07510037399771871, [[28497, 29215, -0.07510037399771871, -0.07506970316171646], [30665, 30670, -0.07506970316171646, -0.07506927847862244]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 1, -0.07506933907442145, -0.07510037399771871, [[28497, 29215, -0.07510037399771871, -0.07506938750741735], [30665, 30670, -0.07506938750741735, -0.07506933907442145]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 2, -0.07509581744670868, -0.07513441131092331, [[30002, 30010, -0.07513441131092331, -0.07509581744670868]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 3, -0.0750967908033854, -0.07513441131091578, [[30002, 30010, -0.07513441131091578, -0.07509702921597634], [30665, 30670, -0.07509702921597634, -0.0750967908033854]]], ["linear_model.SGDRegressorBenchmark.time_predict('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.06927924100000382, 0.0416322764999677, [[29429, 29435, 0.0416322764999677, 0.06457441049997215], [29768, 29776, 0.06457441049997215, 0.06927924100000382]]], ["linear_model.SGDRegressorBenchmark.time_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.0028513947499959613, 0.0020094605833567885, [[29429, 29435, 0.0020094605833567885, 0.0028513947499959613]]], ["ensemble.RandomForestClassifierBenchmark.peakmem_predict('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 183767040.0, 169633792.0, [[31041, 32090, 171216896.0, 183767040.0]]], ["ensemble.RandomForestClassifierBenchmark.peakmem_predict('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 191209472.0, 177053696.0, [[31041, 32090, 178663424.0, 191209472.0]]], ["ensemble.RandomForestClassifierBenchmark.peakmem_predict('sparse', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 407543808.0, 382615552.0, [[31041, 32090, 384073728.0, 407543808.0]]], ["ensemble.HistGradientBoostingClassifierBenchmark.time_predict", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, null, 0.09166909100008525, 0.06920451249993675, [[29768, 29776, 0.08349480000015319, 0.09166909100008525]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 101826560.0, 87252992.0, [[31041, 32090, 89260032.0, 101826560.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 102715392.0, 89346048.0, [[31041, 32090, 91041792.0, 102715392.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 183271424.0, 147341312.0, [[28497, 29215, 147341312.0, 170203136.0], [31041, 32090, 171456512.0, 183271424.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 185290752.0, 148074496.0, [[28497, 29215, 148074496.0, 171051008.0], [31041, 32090, 172433408.0, 185290752.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_fit('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 142299136.0, 128606208.0, [[31041, 32090, 129718272.0, 142299136.0]]], ["linear_model.LinearRegressionBenchmark.peakmem_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LinearRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 312299520.0, 294404096.0, [[31041, 32090, 297058304.0, 312299520.0]]], ["linear_model.LassoBenchmark.peakmem_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 128458752.0, 115302400.0, [[31041, 32090, 116492288.0, 128458752.0]]], ["decomposition.DictionaryLearningBenchmark.time_fit('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 20.96365941099998, 11.686320630999944, [[29429, 29435, 11.686320630999944, 20.96365941099998]]], ["decomposition.DictionaryLearningBenchmark.time_fit('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 12.623588757999869, 7.625391940500094, [[29429, 29435, 7.625391940500094, 10.978311945000087], [null, 29808, 10.978311945000087, 12.623588757999869]]], ["ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, null, 98570240.0, 84518912.0, [[31041, 32090, 86597632.0, 98570240.0]]], ["linear_model.ElasticNetBenchmark.peakmem_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 100864000.0, 87785472.0, [[31041, 32090, 89325568.0, 100864000.0]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 2.2086317100001907, 1.6445342565000374, [[29429, 29435, 1.6445342565000374, 2.2086317100001907]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('sparse', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 11.68485020900016, 9.329817396999715, [[29429, 29435, 9.329817396999715, 11.339105372000176]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('sparse', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 4.1254891919998045, 2.5183323590003965, [[29429, 29435, 2.5183323590003965, 3.7254366419997496], [29783, 29788, 3.7254366419997496, 4.1254891919998045]]], ["linear_model.LinearRegressionBenchmark.time_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LinearRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.07332005749981363, 0.02999779849983497, [[29429, 29435, 0.02999779849983497, 0.07332005749981363]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'auto')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.04865560800044477, 0.04527986250059257, [[29768, 29776, 0.04527986250059257, 0.04865560800044477]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'svd')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.04873439250013689, 0.04537838099986402, [[29768, 29776, 0.04537838099986402, 0.04873439250013689]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'cholesky')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.04875643650029815, 0.04508350249989235, [[29768, 29776, 0.04508350249989235, 0.04875643650029815]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'lsqr')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.048763901500024076, 0.044978951499615505, [[29768, 29776, 0.044978951499615505, 0.048763901500024076]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'sparse_cg')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 4, 0.04886832699958177, 0.04498280000007071, [[29768, 29776, 0.04498280000007071, 0.04886832699958177]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'sag')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 5, 0.04870970399952057, 0.04517217400007212, [[29768, 29776, 0.04517217400007212, 0.04870970399952057]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'saga')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 6, 0.048838410999906046, 0.04518474350015822, [[29768, 29776, 0.04518474350015822, 0.048838410999906046]]], ["linear_model.RidgeBenchmark.time_predict('sparse', 'auto')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 7, 0.008774279999897772, 0.007123232500021004, [[29429, 29435, 0.007123232500021004, 0.008774279999897772]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 0, -4.988476276397705, -4.988476753234863, [[null, 31040, -4.988476753234863, -4.988476276397705]]], ["cluster.KMeansBenchmark.track_train_score('sparse', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 4, -0.9219751358032227, -0.9219752550125122, [[31009, 31019, -0.9219752550125122, -0.9219752550125122]]], ["cluster.KMeansBenchmark.track_train_score('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 6, -0.9219751358032227, -0.9219752550125122, [[null, 31041, -0.9219752550125122, -0.9219751358032227]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 97042432.0, 82796544.0, [[31041, 32090, 84553728.0, 97042432.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 137732096.0, 123445248.0, [[31041, 32090, 125181952.0, 137732096.0]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'cosine', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.11", "cython": ""}, 0, 2.068716466999831, 1.0737004809998325, [[null, 33338, 1.0737004809998325, 2.015810868000699]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 0, -0.07244318723678589, -0.07244402170181274, [[null, 33338, -0.07244402170181274, -0.07244318723678589]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 1, -0.0724431814750343, -0.0724439081840023, [[null, 33338, -0.0724439081840023, -0.0724431814750343]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 6, 13.704112094001175, 8.217527961000087, [[33546, 33648, 8.217527961000087, 13.704112094001175]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 7, 118.892867655999, 7.752664515001015, [[33546, 33648, 7.752664515001015, 118.892867655999]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 8, 9.494422158000816, 1.893763650999972, [[33546, 33648, 1.893763650999972, 9.494422158000816]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 9, 89.47836760599967, 5.274313496500326, [[33546, 33648, 5.274313496500326, 89.47836760599967]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 10, 15.559124529001565, 7.032794542999909, [[33546, 33648, 7.032794542999909, 15.559124529001565]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 11, 10.55756757800009, 4.015357905000201, [[33359, 33361, 4.015357905000201, 10.55756757800009]]], ["decomposition.PCABenchmark.time_fit('randomized')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 2, 1.3684700034998514, 1.09559860499985, [[null, 33310, 1.09559860499985, 1.3684700034998514]]], ["ensemble.GradientBoostingClassifierBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 0, 6.9965942435001125, 3.234195917999841, [[33546, 33648, 3.234195917999841, 6.9965942435001125]]], ["svm.SVCBenchmark.time_predict('sigmoid')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 3, 0.7031137019985181, 0.6139816905006228, [[33543, 33546, 0.6139816905006228, 0.7031137019985181]]], ["decomposition.DictionaryLearningBenchmark.track_train_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 1, -0.07231886142615113, -0.07231886144615562, [[null, 33338, -0.07231886144615562, -0.07231886142615113]]], ["decomposition.DictionaryLearningBenchmark.track_train_score('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 3, -0.07231886152126107, -0.07231886154495859, [[null, 33338, -0.07231886154495859, -0.07231886152126107]]], ["model_selection.CrossValidationBenchmark.time_crossval(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.time_crossval.json", {"python": "3.11", "cython": ""}, 0, 145.80456604399933, 56.59311816300033, [[33546, 33648, 56.59311816300033, 145.80456604399933]]], ["model_selection.CrossValidationBenchmark.time_crossval(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.time_crossval.json", {"python": "3.11", "cython": ""}, 1, 43.13186384200162, 18.011856807000186, [[33546, 33648, 18.011856807000186, 43.13186384200162]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 1, 0.1538074810002854, 0.13355942049997793, [[33437, 33444, 0.13355942049997793, 0.1538074810002854]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 2, -4.109885215759277, -4.109886169433594, [[33712, 33715, -4.109886169433594, -4.109885215759277]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 0, -0.07475551962852478, -0.07475553452968597, [[null, 33338, -0.07475553452968597, -0.07475551962852478]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 1, -0.07475552729939185, -0.07475553216947851, [[null, 33338, -0.07475553216947851, -0.07475552729939185]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 2, -0.07475553452968597, -0.07475554198026657, [[null, 33338, -0.07475554198026657, -0.07475553452968597]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 3, -0.0747555306627162, -0.07475553654479, [[null, 33338, -0.07475553654479, -0.0747555306627162]]], ["svm.SVCBenchmark.time_fit('rbf')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 2, 1.5799147024990816, 1.4258665469988046, [[33359, 33361, 1.4258665469988046, 1.5799147024990816]]], ["ensemble.HistGradientBoostingClassifierBenchmark.time_fit", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, null, 7.549271686999873, 2.372120019000022, [[33546, 33551, 2.372120019000022, 7.549271686999873]]], ["model_selection.GridSearchBenchmark.time_fit(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 0, 945.3629577170013, 341.92955999100013, [[33546, 33648, 341.92955999100013, 945.3629577170013]]], ["model_selection.GridSearchBenchmark.time_fit(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 1, 275.2593120170004, 104.69993370100019, [[33546, 33648, 104.69993370100019, 275.2593120170004]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'saga')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 6, 12.958227949000502, 12.102378384000076, [[33546, 33648, 12.102378384000076, 12.958227949000502]]], ["cluster.KMeansBenchmark.time_predict('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 5, 0.028549803000032625, 0.01591946000007738, [[33537, 33543, 0.01591946000007738, 0.028549803000032625]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 3, 16.97975306599983, 9.980928548000065, [[33437, 33444, 9.980928548000065, 16.97975306599983]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 3, -0.07509114984802133, -0.07509371825113932, [[null, 33338, -0.07509371825113932, -0.07509114984802133]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 0, 18.63268166999933, 7.890376977999949, [[33546, 33551, 7.890376977999949, 18.63268166999933]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('sparse', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 3, 103.97959800199988, 3.8619773030000033, [[33546, 33551, 3.8619773030000033, 103.97959800199988]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 1, -3.0780560970306396, -3.0780563354492188, [[null, 33708, -3.0780563354492188, -3.0780560970306396]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 3, -3.0780560970306396, -3.0780563354492188, [[null, 33518, -3.0780563354492188, -3.0780563354492188]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'manhattan', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.11", "cython": "3.0.3"}, 5, 2.6176616529996863, 2.1561904800000775, [[34113, 34115, 2.1561904800000775, 2.6176616529996863]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.11", "cython": "3.0.3"}, 8, 4.127793399999973, 3.6725709250004, [[null, 34141, 3.6725709250004, 4.127793399999973]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.3"}, 10, 8.201274101000308, 7.358123495499967, [[34155, 34158, 7.358123495499967, 8.201274101000308]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.11", "cython": "3.0.3"}, 0, -4.109885215759277, -4.109886169433594, [[34126, 34139, -4.109886169433594, -4.109886169433594]]], ["linear_model.LassoBenchmark.time_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.3"}, 2, 0.003087816833309868, 0.002283395899985408, [[null, 34140, 0.0026101646999904917, 0.002283395899985408]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_transform.json", {"python": "3.11", "cython": "3.0.3"}, 4, 3.8029851090000193, 3.570233304000112, [[34120, 34126, 3.570233304000112, 3.8029851090000193]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_transform.json", {"python": "3.11", "cython": "3.0.3"}, 5, 3.8003822919999948, 3.5546480730001804, [[null, 34141, 3.5546480730001804, 3.8003822919999948]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_transform.json", {"python": "3.11", "cython": "3.0.3"}, 6, 3.781139291000045, 3.521388963999925, [[null, 34140, 3.521388963999925, 3.781139291000045]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_transform.json", {"python": "3.11", "cython": "3.0.3"}, 7, 3.8138180620001094, 3.5410637559998577, [[null, 34140, 3.5410637559998577, 3.8138180620001094]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.11", "cython": "0.29.36"}, 3, 7.531629993500019, 6.888835698500088, [[33820, 33826, 6.888835698500088, 7.531629993500019]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('brute', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": "0.29.36"}, 1, 0.086020061000454, 0.08140420650033775, [[33813, 33818, 0.08140420650033775, 0.086020061000454]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": "0.29.36"}, 1, 0.16475128400020367, 0.15381539999998495, [[33826, 33833, 0.15381539999998495, 0.16475128400020367]]], ["linear_model.SGDRegressorBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.time_fit.json", {"python": "3.11", "cython": "0.29.36"}, 0, 5.71938168899942, 5.068996183999843, [[33766, 33802, 5.068996183999843, 5.71938168899942]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'sag')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.11", "cython": "0.29.36"}, 12, 2.7997688129999005, 2.5590021950001756, [[33818, 33820, 2.5590021950001756, 2.7997688129999005]]], ["cluster.KMeansBenchmark.time_predict('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_predict.json", {"python": "3.11", "cython": "0.29.36"}, 6, 0.02846665949994076, 0.014001588500036632, [[33818, 33820, 0.014001588500036632, 0.02846665949994076]]], ["linear_model.ElasticNetBenchmark.time_fit('dense', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.11", "cython": "0.29.36"}, 0, 1.4990876480001134, 1.347287838000284, [[null, 33734, 1.347287838000284, 1.4990876480001134]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": "0.29.36"}, 1, -3.0780560970306396, -3.0780563354492188, [[33808, 33813, -3.0780563354492188, -3.0780560970306396]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.11", "cython": "3.0.2"}, 11, 2.0897179319995303, 1.865396010999575, [[34031, 34034, 1.865396010999575, 2.0897179319995303]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.2"}, 7, 123.64697125900057, 117.0689821349988, [[34058, 34065, 117.0689821349988, 123.64697125900057]]], ["decomposition.PCABenchmark.time_fit('arpack')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.time_fit.json", {"python": "3.11", "cython": "3.0.2"}, 1, 1.46766711950022, 1.0839253939998343, [[34031, 34034, 1.0839253939998343, 1.46766711950022]]], ["ensemble.GradientBoostingClassifierBenchmark.time_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": "3.0.2"}, 1, 2.462212150500136, 2.108637685500298, [[34046, 34049, 2.108637685500298, 2.462212150500136]]], ["linear_model.LassoBenchmark.time_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_fit.json", {"python": "3.11", "cython": "3.0.2"}, 2, 2.7477894640005616, 2.3575837060002414, [[34058, 34065, 2.3575837060002414, 2.7477894640005616]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.2"}, 0, 0.2703902740004196, 0.2379772194999532, [[34052, 34058, 0.2379772194999532, 0.2703902740004196]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.11", "cython": "3.0.2"}, 0, -4.1098856925964355, -4.109886169433594, [[34049, 34052, -4.109886169433594, -4.109886169433594]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.11", "cython": "3.0.2"}, 2, -4.109885215759277, -4.109886169433594, [[34046, 34049, -4.109886169433594, -4.109886169433594], [34075, 34079, -4.1098856925964355, -4.109885215759277]]], ["linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.2"}, 7, 0.006289843499871495, 0.00497264433336871, [[34065, 34068, 0.00497264433336871, 0.006289843499871495]]], ["cluster.KMeansBenchmark.time_predict('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.2"}, 7, 0.028358634499909385, 0.015978468999946926, [[34049, 34052, 0.015978468999946926, 0.028358634499909385]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.11", "cython": "3.0.2"}, 2, 3.2055468270000347, 3.050744257500128, [[34052, 34058, 3.050744257500128, 3.2055468270000347]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": "3.0.2"}, 0, 21.906948195999576, 18.536215199000253, [[34052, 34058, 18.536215199000253, 21.906948195999576]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": "3.0.2"}, 1, -3.0780560970306396, -3.0780563354492188, [[34065, 34068, -3.0780563354492188, -3.0780560970306396]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": "3.0.2"}, 3, -3.0780560970306396, -3.0780563354492188, [[34031, 34034, -3.0780563354492188, -3.0780563354492188]]]]} \ No newline at end of file +{"regressions": [["model_selection.GridSearchBenchmark.peakmem_predict(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 98850816.0, 91230208.0, [[32294, 32303, 94040064.0, 97390592.0]]], ["model_selection.GridSearchBenchmark.peakmem_predict(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 98838528.0, 91246592.0, [[32294, 32303, 94040064.0, 97390592.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 101578752.0, 94609408.0, [[null, 32198, 94609408.0, 97341440.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 111319040.0, 104300544.0, [[null, 32198, 104300544.0, 106926080.0]]], ["model_selection.GridSearchBenchmark.peakmem_fit(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 106528768.0, 98037760.0, [[32294, 32303, 101011456.0, 104521728.0]]], ["model_selection.GridSearchBenchmark.peakmem_fit(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 104763392.0, 96858112.0, [[null, 32198, 96858112.0, 100007936.0]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 10, 3.3947032634996503, 2.786043321500074, [[null, 32881, 2.786043321500074, 3.3947032634996503]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 11, 5.619692420999854, 2.1219118814997273, [[null, 32881, 2.1219118814997273, 5.619692420999854]]], ["linear_model.LassoBenchmark.time_fit('dense', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 1.4256798984999932, 1.2750800849998996, [[32651, 32838, 1.2750800849998996, 1.4256798984999932]]], ["linear_model.LassoBenchmark.time_fit('dense', False)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.6213949935001892, 1.4736898109999856, [[32651, 32838, 1.4736898109999856, 1.6213949935001892]]], ["cluster.KMeansBenchmark.time_fit('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 2.2565097730000616, 1.9918717970000444, [[33050, 33057, 1.9918717970000444, 2.2565097730000616]]], ["model_selection.CrossValidationBenchmark.time_crossval(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.time_crossval.json", {"python": "3.8", "cython": ""}, 0, 84.81582076599989, 43.90737086200079, [[32432, 32572, 43.90737086200079, 84.81582076599989]]], ["model_selection.CrossValidationBenchmark.time_crossval(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.time_crossval.json", {"python": "3.8", "cython": ""}, 1, 25.012438464999832, 13.38686093599972, [[32411, 32420, 13.38686093599972, 21.806337958000768], [32580, 32588, 21.806337958000768, 25.012438464999832]]], ["decomposition.DictionaryLearningBenchmark.peakmem_fit('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 138711040.0, 127209472.0, [[32294, 32303, 129851392.0, 133025792.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_fit('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 134176768.0, 126898176.0, [[null, 32198, 126898176.0, 129597440.0]]], ["svm.SVCBenchmark.time_fit('rbf')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 0.9007304115011721, 0.7037775400003738, [[32651, 32838, 0.7037775400003738, 0.9007304115011721]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 106211328.0, 98676736.0, [[null, 32198, 98676736.0, 101310464.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 105893888.0, 98840576.0, [[32294, 32303, 100823040.0, 104460288.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 106115072.0, 98525184.0, [[null, 32198, 98525184.0, 101117952.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 105959424.0, 98955264.0, [[null, 32198, 98955264.0, 101011456.0]]], ["ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, null, 105981952.0, 98271232.0, [[null, 32198, 98271232.0, 101003264.0]]], ["manifold.TSNEBenchmark.peakmem_fit('exact')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/manifold.TSNEBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 113817600.0, 104988672.0, [[32294, 32303, 108363776.0, 112087040.0]]], ["manifold.TSNEBenchmark.peakmem_fit('barnes_hut')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/manifold.TSNEBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 120670208.0, 111697920.0, [[null, 32198, 111697920.0, 114991104.0]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 5, 2.4938819634999163, 1.9416651550000097, [[32651, 32838, 1.9416651550000097, 2.4938819634999163]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 7, 8.892551909000758, 5.197582111500196, [[32651, 32838, 5.197582111500196, 8.892551909000758]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 11, 8.846687373999885, 5.187773386998742, [[32651, 32838, 5.187773386998742, 8.846687373999885]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 0, 0.13430951849989015, 0.09576546900007088, [[33031, 33040, 0.09576546900007088, 0.13430951849989015]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.13418976350010325, 0.09606840549997742, [[33031, 33040, 0.09606840549997742, 0.13418976350010325]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 0.054224893999162305, 0.04985318950002693, [[32424, 32432, 0.04985318950002693, 0.054224893999162305]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 11, 0.03840343999854667, 0.03311949050021212, [[32424, 32432, 0.03311949050021212, 0.03840343999854667]]], ["cluster.KMeansBenchmark.peakmem_transform('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 141039616.0, 133468160.0, [[null, 32198, 133468160.0, 135958528.0]]], ["cluster.KMeansBenchmark.peakmem_transform('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 140912640.0, 133468160.0, [[null, 32198, 133468160.0, 135995392.0]]], ["cluster.KMeansBenchmark.peakmem_transform('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 141043712.0, 133459968.0, [[null, 32198, 133459968.0, 136044544.0]]], ["cluster.KMeansBenchmark.peakmem_transform('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 140982272.0, 133443584.0, [[null, 32198, 133443584.0, 135970816.0]]], ["cluster.KMeansBenchmark.peakmem_transform('sparse', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 4, 140716032.0, 129863680.0, [[32294, 32303, 132198400.0, 135419904.0]]], ["cluster.KMeansBenchmark.peakmem_transform('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 5, 140716032.0, 129863680.0, [[32294, 32303, 132198400.0, 135419904.0]]], ["cluster.KMeansBenchmark.peakmem_transform('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 6, 140716032.0, 129863680.0, [[32294, 32303, 132198400.0, 135419904.0]]], ["cluster.KMeansBenchmark.peakmem_transform('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 7, 140716032.0, 129863680.0, [[32294, 32303, 132198400.0, 135419904.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 120133632.0, 112246784.0, [[null, 32198, 112246784.0, 115359744.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 111405056.0, 103583744.0, [[null, 32198, 103583744.0, 106188800.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 95678464.0, 87138304.0, [[32294, 32303, 90152960.0, 93949952.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 97529856.0, 89346048.0, [[32294, 32303, 92061696.0, 96141312.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 5, 134678528.0, 126783488.0, [[null, 32198, 126783488.0, 129425408.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 6, 119717888.0, 107761664.0, [[32294, 32303, 110923776.0, 114593792.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 7, 120035328.0, 108300288.0, [[32294, 32303, 108300288.0, 118687744.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 105529344.0, 98103296.0, [[null, 32198, 98103296.0, 100728832.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 105494528.0, 98109440.0, [[32193, 32197, 98109440.0, 100718592.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 121044992.0, 113606656.0, [[null, 32198, 113606656.0, 116293632.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 121044992.0, 113606656.0, [[null, 32198, 113606656.0, 116293632.0]]], ["cluster.MiniBatchKMeansBenchmark.track_test_score('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 2, -0.9366871118545532, -0.9376848340034485, [[33050, 33057, -0.9376848340034485, -0.9366871118545532]]], ["cluster.MiniBatchKMeansBenchmark.track_test_score('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 3, -0.9386959075927734, -0.9521117806434631, [[33050, 33057, -0.9521117806434631, -0.9386959075927734]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 89192448.0, 80896000.0, [[32294, 32303, 83898368.0, 87613440.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 89192448.0, 80891904.0, [[32294, 32303, 83894272.0, 87605248.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 92465152.0, 84221952.0, [[32294, 32303, 87355392.0, 91029504.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 92469248.0, 84226048.0, [[32294, 32303, 87306240.0, 91033600.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 4, 91398144.0, 83234816.0, [[32294, 32303, 86237184.0, 89958400.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 5, 91406336.0, 83247104.0, [[32294, 32303, 86237184.0, 89960448.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 6, 100026368.0, 91869184.0, [[32294, 32303, 94842880.0, 98586624.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 7, 100026368.0, 91869184.0, [[32294, 32303, 94842880.0, 98586624.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 8, 91361280.0, 83218432.0, [[32294, 32303, 86245376.0, 89929728.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 9, 91355136.0, 83218432.0, [[32294, 32303, 86437888.0, 89929728.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 10, 99780608.0, 91643904.0, [[32294, 32303, 94646272.0, 98338816.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 11, 99780608.0, 91643904.0, [[32294, 32303, 94646272.0, 98338816.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 107773952.0, 97619968.0, [[32294, 32303, 100749312.0, 104982528.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 107841536.0, 97685504.0, [[32294, 32303, 100941824.0, 105211904.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 113688576.0, 103673856.0, [[32294, 32303, 106737664.0, 111140864.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('brute', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 113649664.0, 103677952.0, [[32294, 32303, 106741760.0, 111126528.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 4, 93020160.0, 84926464.0, [[32294, 32303, 87994368.0, 91623424.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 5, 96159744.0, 88256512.0, [[32294, 32303, 91013120.0, 94982144.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 6, 102901760.0, 94826496.0, [[32294, 32303, 97832960.0, 101521408.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 7, 106457088.0, 98553856.0, [[32294, 32303, 100913152.0, 105259008.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 8, 92801024.0, 84770816.0, [[32294, 32303, 87386112.0, 91441152.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 9, 95963136.0, 88084480.0, [[32294, 32303, 90542080.0, 94851072.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 10, 102443008.0, 94355456.0, [[32294, 32303, 97394688.0, 101095424.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 11, 106049536.0, 98168832.0, [[32294, 32303, 100644864.0, 104923136.0]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 0, -4.109885215759277, -5.011288642883301, [[33050, 33057, -5.011288642883301, -4.109886169433594], [33211, 33213, -4.109886169433594, -4.109885215759277]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 1, -3.077857732772827, -3.1141350269317627, [[33050, 33057, -3.1141350269317627, -3.0778582096099854], [33179, 33189, -3.0778582096099854, -3.0778582096099854]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 2, -4.109885215759277, -5.011288642883301, [[33050, 33057, -5.011288642883301, -4.109886169433594], [null, 33229, -4.109886169433594, -4.109885215759277]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 3, -3.0778582096099854, -3.1141350269317627, [[33050, 33057, -3.1141350269317627, -3.0778582096099854]]], ["cluster.KMeansBenchmark.track_test_score('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 5, -0.9249227643013, -0.9306698441505432, [[33050, 33057, -0.9306698441505432, -0.9249227643013]]], ["cluster.KMeansBenchmark.track_test_score('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 7, -0.9249262809753418, -0.930671751499176, [[33050, 33057, -0.9306698441505432, -0.9249262809753418]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 106934272.0, 99745792.0, [[null, 32198, 99745792.0, 102088704.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 106383360.0, 99762176.0, [[null, 32198, 99762176.0, 101568512.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 107032576.0, 99667968.0, [[null, 32198, 99667968.0, 102084608.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 106647552.0, 99868672.0, [[null, 32198, 99868672.0, 101769216.0]]], ["ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, null, 117735424.0, 110399488.0, [[null, 32198, 110399488.0, 113397760.0]]], ["linear_model.ElasticNetBenchmark.peakmem_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 135835648.0, 128327680.0, [[null, 32198, 128327680.0, 130998272.0]]], ["cluster.KMeansBenchmark.peakmem_fit('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 120840192.0, 112832512.0, [[null, 32198, 112832512.0, 115462144.0]]], ["cluster.KMeansBenchmark.peakmem_fit('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 135401472.0, 125513728.0, [[32294, 32303, 128184320.0, 131653632.0]]], ["cluster.KMeansBenchmark.peakmem_fit('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 156628992.0, 148451328.0, [[null, 32198, 148451328.0, 151097344.0]]], ["cluster.KMeansBenchmark.peakmem_fit('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 157786112.0, 149676032.0, [[null, 32198, 149676032.0, 152330240.0]]], ["cluster.KMeansBenchmark.peakmem_fit('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 6, 224722944.0, 213315584.0, [[null, 32198, 213315584.0, 215736320.0]]], ["linear_model.LogisticRegressionBenchmark.time_fit('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 5.119495814999937, 3.6039345849999336, [[32432, 32572, 3.6039345849999336, 5.119495814999937]]], ["linear_model.LogisticRegressionBenchmark.time_fit('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 5.222811944999648, 3.462408609000022, [[32432, 32572, 3.462408609000022, 5.222811944999648]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 3.795173198499924, 2.901297688500108, [[32432, 32572, 2.901297688500108, 3.795173198499924]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 7, 4.10541693200048, 2.99407483899995, [[32432, 32572, 2.99407483899995, 4.10541693200048]]], ["ensemble.GradientBoostingClassifierBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 4.864555561500083, 3.04781713400007, [[32432, 32572, 3.04781713400007, 4.864555561500083]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 11.385541180000018, 6.362006434000023, [[32432, 32572, 6.362006434000023, 11.385541180000018]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 3.595307277499842, 2.2652268890001324, [[32411, 32420, 2.2652268890001324, 3.595307277499842]]], ["model_selection.CrossValidationBenchmark.peakmem_crossval(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.peakmem_crossval.json", {"python": "3.8", "cython": ""}, 1, 130850816.0, 123015168.0, [[null, 32198, 123015168.0, 125816832.0]]], ["cluster.MiniBatchKMeansBenchmark.track_train_score('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 2, -0.9323447346687317, -0.9334458708763123, [[33050, 33057, -0.9334458708763123, -0.9323447346687317]]], ["cluster.MiniBatchKMeansBenchmark.track_train_score('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 3, -0.934399425983429, -0.9480265974998474, [[33050, 33057, -0.9480265974998474, -0.934399425983429]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 111282176.0, 103063552.0, [[null, 32198, 103063552.0, 106151936.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 111249408.0, 103026688.0, [[null, 32198, 103026688.0, 106123264.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 102078464.0, 93495296.0, [[32294, 32303, 96657408.0, 100253696.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 102035456.0, 93614080.0, [[32294, 32303, 96575488.0, 100253696.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 4, 112154624.0, 103952384.0, [[null, 32198, 103952384.0, 106954752.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 5, 112156672.0, 103952384.0, [[null, 32198, 103952384.0, 106954752.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 6, 99727360.0, 91521024.0, [[32294, 32303, 94703616.0, 98209792.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 7, 99735552.0, 91529216.0, [[32294, 32303, 94707712.0, 98209792.0]]], ["cluster.KMeansBenchmark.peakmem_predict('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 107298816.0, 99885056.0, [[null, 32198, 99885056.0, 102500352.0]]], ["cluster.KMeansBenchmark.peakmem_predict('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 107274240.0, 99856384.0, [[null, 32198, 99856384.0, 102514688.0]]], ["cluster.KMeansBenchmark.peakmem_predict('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 107274240.0, 99885056.0, [[null, 32198, 99885056.0, 102514688.0]]], ["cluster.KMeansBenchmark.peakmem_predict('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 107274240.0, 99856384.0, [[null, 32198, 99856384.0, 102514688.0]]], ["cluster.KMeansBenchmark.peakmem_predict('sparse', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 4, 115148800.0, 107716608.0, [[null, 32198, 107716608.0, 110415872.0]]], ["cluster.KMeansBenchmark.peakmem_predict('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 5, 115148800.0, 107716608.0, [[null, 32198, 107716608.0, 110415872.0]]], ["cluster.KMeansBenchmark.peakmem_predict('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 6, 115148800.0, 107716608.0, [[null, 32198, 107716608.0, 110415872.0]]], ["cluster.KMeansBenchmark.peakmem_predict('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 7, 115148800.0, 107716608.0, [[null, 32198, 107716608.0, 110415872.0]]], ["linear_model.LassoBenchmark.peakmem_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 135835648.0, 128278528.0, [[null, 32198, 128278528.0, 130985984.0]]], ["linear_model.LassoBenchmark.peakmem_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 108089344.0, 100954112.0, [[null, 32198, 100954112.0, 103546880.0]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.002980613333344688, 0.0026784809999753634, [[32649, 32651, 0.0026784809999753634, 0.002980613333344688]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.001904074000018833, 0.0016939145714656792, [[32213, 32218, 0.0016939145714656792, 0.001904074000018833]]], ["linear_model.SGDRegressorBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 5.958662469000046, 3.880424359999779, [[32651, 32838, 3.880424359999779, 4.447991056999854], [33075, 33086, 4.447991056999854, 4.822892239999874], [33194, 33208, 4.822892239999874, 5.958662469000046]]], ["linear_model.SGDRegressorBenchmark.time_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 5.567558806999841, 1.343501784000182, [[32881, 32895, 1.343501784000182, 5.567558806999841]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 103989248.0, 96636928.0, [[null, 32198, 96636928.0, 99500032.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 145133568.0, 137379840.0, [[null, 32198, 137379840.0, 140144640.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 139159552.0, 131629056.0, [[null, 32198, 131629056.0, 134172672.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 139159552.0, 131719168.0, [[null, 32198, 131719168.0, 134193152.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 140017664.0, 129003520.0, [[32294, 32303, 131420160.0, 134772736.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 140017664.0, 128999424.0, [[32294, 32303, 131420160.0, 134760448.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 108146688.0, 101130240.0, [[null, 32198, 101130240.0, 103452672.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 110882816.0, 102653952.0, [[32294, 32303, 105533440.0, 109289472.0]]], ["linear_model.ElasticNetBenchmark.time_fit('dense', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 1.4241585639999812, 1.2580682324999088, [[32651, 32838, 1.2580682324999088, 1.4241585639999812]]], ["linear_model.ElasticNetBenchmark.time_fit('dense', False)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.6408157220000703, 1.4637692859998879, [[32651, 32838, 1.4637692859998879, 1.6408157220000703]]], ["linear_model.ElasticNetBenchmark.time_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 2.737181770000234, 2.4433016624998345, [[null, 32409, 2.4433016624998345, 2.737181770000234]]], ["cluster.KMeansBenchmark.time_transform('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 0, 0.13446171199984747, 0.09999187950006672, [[33031, 33040, 0.09999187950006672, 0.13446171199984747]]], ["cluster.KMeansBenchmark.time_transform('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.13351594300002034, 0.09808573050008818, [[33031, 33040, 0.09808573050008818, 0.13351594300002034]]], ["cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 0.1336752395000076, 0.09787636049986759, [[33031, 33040, 0.09787636049986759, 0.1336752395000076]]], ["cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 3, 0.13355329900002744, 0.09772891250008797, [[33031, 33040, 0.09772891250008797, 0.13355329900002744]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 4, 3.9109639700000116, 3.642721819000144, [[32879, 32895, 3.642721819000144, 3.9109639700000116]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 5, 3.9039899700001115, 3.6996333510001023, [[32879, 32895, 3.6996333510001023, 3.9039899700001115]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 6, 3.900951019999866, 3.660172879000129, [[32879, 32895, 3.660172879000129, 3.900951019999866]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 7, 3.8940096110000013, 3.6817158400001517, [[32879, 32895, 3.6817158400001517, 3.8940096110000013]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 125505536.0, 117731328.0, [[null, 32198, 117731328.0, 120594432.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 124577792.0, 117481472.0, [[null, 32198, 117481472.0, 119992320.0]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 0, -4.1075520515441895, -4.988476753234863, [[32424, 32432, -4.988476753234863, -4.988476276397705], [33050, 33057, -4.988476276397705, -4.1075520515441895]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 1, -3.0774285793304443, -3.1168856620788574, [[33050, 33057, -3.1168856620788574, -3.0774285793304443]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 2, -4.1075520515441895, -4.988476753234863, [[33050, 33057, -4.988476753234863, -4.1075520515441895]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 3, -3.0774285793304443, -3.1168856620788574, [[33050, 33057, -3.1168856620788574, -3.0774285793304443]]], ["cluster.KMeansBenchmark.track_train_score('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 5, -0.922096312046051, -0.9255540370941162, [[33050, 33057, -0.9255540370941162, -0.922096312046051]]], ["cluster.KMeansBenchmark.track_train_score('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 7, -0.9221000075340271, -0.9255544543266296, [[33050, 33057, -0.9255540370941162, -0.9221000075340271]]], ["linear_model.ElasticNetBenchmark.peakmem_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 108079104.0, 100945920.0, [[null, 32198, 100945920.0, 103530496.0]]], ["cluster.MiniBatchKMeansBenchmark.time_fit('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 0.34298792899994623, 0.2601930060000086, [[29429, 29435, 0.2601930060000086, 0.3001380919999974]]], ["cluster.MiniBatchKMeansBenchmark.time_fit('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 0.36076429649995134, 0.2681720820000919, [[29768, 29776, 0.3065479290000894, 0.36076429649995134]]], ["cluster.MiniBatchKMeansBenchmark.time_fit('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 1.648156553999911, 1.0463895640000374, [[29429, 29435, 1.0463895640000374, 1.648156553999911]]], ["model_selection.GridSearchBenchmark.peakmem_predict(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 91131904.0, 77533184.0, [[31041, 32090, 79130624.0, 91131904.0]]], ["model_selection.GridSearchBenchmark.peakmem_predict(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 91131904.0, 77561856.0, [[31041, 32090, 79126528.0, 91131904.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 94924800.0, 80715776.0, [[31041, 32090, 82552832.0, 94924800.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 104632320.0, 90421248.0, [[31041, 32090, 92262400.0, 104632320.0]]], ["model_selection.GridSearchBenchmark.peakmem_fit(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 98156544.0, 84082688.0, [[31041, 32090, 86249472.0, 98156544.0]]], ["model_selection.GridSearchBenchmark.peakmem_fit(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 97107968.0, 83275776.0, [[31041, 32090, 84750336.0, 97107968.0]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'cosine', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 0, 1.0816761809992386, 0.6492327094999837, [[29429, 29435, 0.6492327094999837, 1.0816761809992386]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'cosine', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 1, 1.1749681209994378, 0.9846832859998358, [[29768, 29776, 1.0704449280001427, 1.1749681209994378]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'euclidean', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 2, 1.6267482870002823, 1.131574778999493, [[29768, 29776, 1.511747548999665, 1.6267482870002823]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'euclidean', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 3, 2.8029338409996853, 2.0952009089996864, [[29429, 29435, 2.0952009089996864, 2.6413094899999123], [29768, 29776, 2.6413094899999123, 2.8029338409996853]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'manhattan', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 5, 3.2750708539997504, 1.5104139889999715, [[29429, 29435, 1.5104139889999715, 2.665036097999291], [29572, 29591, 2.665036097999291, 3.2750708539997504]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'correlation', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 7, 2.6057268360000307, 1.5212544939995496, [[29429, 29435, 1.5212544939995496, 2.6057268360000307]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 8, 3.7114240050000262, 3.227034360000289, [[29429, 29435, 3.227034360000289, 3.7114240050000262]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 9, 2.6670874330002334, 1.367151794000165, [[29429, 29435, 1.394243098500283, 2.500172876000306], [29768, 29776, 2.500172876000306, 2.6670874330002334]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 10, 2.613872798000557, 2.1499179414995524, [[29429, 29435, 2.1499179414995524, 2.613872798000557]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 11, 2.116926750499715, 1.0954036029997951, [[29429, 29435, 1.0954036029997951, 1.9836563979997663], [29776, 29783, 1.9836563979997663, 2.116926750499715]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'manhattan', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.8", "cython": ""}, 13, 1.3542568210000354, 1.0587421519994678, [[29429, 29435, 1.0587421519994678, 1.3542568210000354]]], ["decomposition.DictionaryLearningBenchmark.track_train_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 0, -0.07231885939836502, -0.07231886145768542, [[29808, 29813, -0.07231886145768542, -0.07231886144906298], [30028, 30035, -0.07231886144906298, -0.07231886144287691], [null, 30502, -0.07231886144287691, -0.07231885939836502]]], ["decomposition.DictionaryLearningBenchmark.track_train_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 1, -0.07231886145064417, -0.07231886146221082, [[30028, 30035, -0.07231886146221082, -0.07231886145064417]]], ["decomposition.DictionaryLearningBenchmark.track_train_score('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 2, -0.07231885939836502, -0.07231886156090023, [[30028, 30035, -0.07231886156090023, -0.07231886156066476], [null, 30502, -0.07231886156066476, -0.07231885939836502]]], ["svm.SVCBenchmark.time_predict('linear')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.7379378209989227, 0.4336090870001499, [[29768, 29776, 0.4336090870001499, 0.7379378209989227]]], ["svm.SVCBenchmark.time_predict('poly')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.7377982245006933, 0.4378497059988149, [[29768, 29776, 0.4378497059988149, 0.7377982245006933]]], ["svm.SVCBenchmark.time_predict('sigmoid')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.736312139999427, 0.43831788200077426, [[29768, 29776, 0.43831788200077426, 0.736312139999427]]], ["linear_model.LassoBenchmark.time_fit('dense', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 1.3532190169999012, 0.7728853464998338, [[29425, 29429, 0.7728853464998338, 1.283576799499997]]], ["linear_model.LassoBenchmark.time_fit('dense', False)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.5789366555000015, 0.8136002810001628, [[29429, 29435, 0.8136002810001628, 1.4818555120002657], [29783, 29788, 1.4818555120002657, 1.5789366555000015]]], ["model_selection.GridSearchBenchmark.time_fit(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 76.34837349199915, 66.27560593599992, [[29429, 29435, 66.27560593599992, 76.34837349199915]]], ["cluster.KMeansBenchmark.time_fit('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 2.6487308000000667, 1.555339187999948, [[29768, 29776, 1.8251347794999333, 2.6487308000000667]]], ["linear_model.LinearRegressionBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LinearRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 3.1949284400000124, 1.0697697784996762, [[28497, 29215, 1.0697697784996762, 1.1204848459997265], [30890, 30904, 2.2272244540001793, 3.1949284400000124]]], ["linear_model.LinearRegressionBenchmark.time_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LinearRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.5362763814998743, 0.5499250379998557, [[29429, 29435, 0.5888377334999859, 1.201512325000067], [30890, 30904, 1.3145294084997659, 1.5362763814998743]]], ["model_selection.CrossValidationBenchmark.time_crossval(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.time_crossval.json", {"python": "3.8", "cython": ""}, 1, 13.437568640999416, 11.55077611500019, [[29429, 29435, 11.55077611500019, 13.437568640999416]]], ["decomposition.DictionaryLearningBenchmark.time_fit('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 20.96365941099998, 11.686320630999944, [[29429, 29435, 11.686320630999944, 20.96365941099998]]], ["decomposition.DictionaryLearningBenchmark.time_fit('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 12.623588757999869, 7.625391940500094, [[29429, 29435, 7.625391940500094, 10.978311945000087], [null, 29808, 10.978311945000087, 12.623588757999869]]], ["linear_model.SGDRegressorBenchmark.peakmem_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 96911360.0, 83673088.0, [[31041, 32090, 85041152.0, 96911360.0]]], ["ensemble.HistGradientBoostingClassifierBenchmark.time_predict", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, null, 0.09166909100008525, 0.06920451249993675, [[29768, 29776, 0.08349480000015319, 0.09166909100008525]]], ["ensemble.RandomForestClassifierBenchmark.peakmem_predict('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 183767040.0, 169633792.0, [[31041, 32090, 171216896.0, 183767040.0]]], ["ensemble.RandomForestClassifierBenchmark.peakmem_predict('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 191209472.0, 177053696.0, [[31041, 32090, 178663424.0, 191209472.0]]], ["ensemble.RandomForestClassifierBenchmark.peakmem_predict('sparse', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 407543808.0, 382615552.0, [[31041, 32090, 384073728.0, 407543808.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 0, -0.07506927847862244, -0.07510037399771871, [[28497, 29215, -0.07510037399771871, -0.07506970316171646], [30665, 30670, -0.07506970316171646, -0.07506927847862244]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 1, -0.07506933907442145, -0.07510037399771871, [[28497, 29215, -0.07510037399771871, -0.07506938750741735], [30665, 30670, -0.07506938750741735, -0.07506933907442145]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 2, -0.07509581744670868, -0.07513441131092331, [[30002, 30010, -0.07513441131092331, -0.07509581744670868]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 3, -0.0750967908033854, -0.07513441131091578, [[30002, 30010, -0.07513441131091578, -0.07509702921597634], [30665, 30670, -0.07509702921597634, -0.0750967908033854]]], ["decomposition.DictionaryLearningBenchmark.peakmem_fit('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 142299136.0, 128606208.0, [[31041, 32090, 129718272.0, 142299136.0]]], ["svm.SVCBenchmark.time_fit('linear')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 0.9549204214999918, 0.6676248109997687, [[29768, 29776, 0.6676248109997687, 0.9549204214999918]]], ["svm.SVCBenchmark.time_fit('poly')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 0.9526650339994376, 0.6656067194999196, [[29768, 29776, 0.6697120789995097, 0.9526650339994376]]], ["svm.SVCBenchmark.time_fit('rbf')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 0.955368300000373, 0.6764446990000579, [[null, 29294, 0.6961092275000738, 0.6764446990000579]]], ["svm.SVCBenchmark.time_fit('sigmoid')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 0.9532537739996769, 0.6729825549991801, [[null, 29551, 0.8879308570003559, 0.6729825549991801]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 99069952.0, 86284288.0, [[31041, 32090, 87101440.0, 99069952.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 99373056.0, 86315008.0, [[31041, 32090, 86843392.0, 99373056.0]]], ["decomposition.DictionaryLearningBenchmark.peakmem_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 98844672.0, 86226944.0, [[31041, 32090, 86906880.0, 98844672.0]]], ["ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, null, 98570240.0, 84518912.0, [[31041, 32090, 86597632.0, 98570240.0]]], ["manifold.TSNEBenchmark.peakmem_fit('exact')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/manifold.TSNEBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 99151872.0, 85667840.0, [[31041, 32090, 86941696.0, 99151872.0]]], ["linear_model.SGDRegressorBenchmark.time_predict('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.06927924100000382, 0.0416322764999677, [[29429, 29435, 0.0416322764999677, 0.06457441049997215], [29768, 29776, 0.06457441049997215, 0.06927924100000382]]], ["linear_model.SGDRegressorBenchmark.time_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.0028513947499959613, 0.0020094605833567885, [[29429, 29435, 0.0020094605833567885, 0.0028513947499959613]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 4, 0.941246193000552, 0.6924204100005227, [[29429, 29435, 0.7239697439999873, 0.941246193000552]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 5, 2.5587522334990354, 0.7722874989995034, [[29429, 29435, 0.8071847430001071, 1.625175291999767], [29768, 29776, 1.625175291999767, 2.5587522334990354]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 6, 8.099321813000643, 5.71836935400006, [[29429, 29435, 6.1424575720002395, 8.099321813000643]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 7, 9.311504750001404, 5.3428612119996615, [[29768, 29776, 5.3428612119996615, 9.311504750001404]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 8, 1.8560742700001356, 1.259906507499636, [[29429, 29435, 1.3675167944993518, 1.8560742700001356]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 10, 7.459379219500079, 5.234896867999851, [[29429, 29435, 5.234896867999851, 7.459379219500079]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 11, 10.010013914999945, 4.5771756980002465, [[29768, 29776, 4.5771756980002465, 10.010013914999945]]], ["decomposition.PCABenchmark.time_fit('full')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 1.9829450105000888, 1.1255870280000408, [[29429, 29435, 1.1255870280000408, 1.8539050950003002]]], ["decomposition.PCABenchmark.time_fit('arpack')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.1924363670000275, 1.0004457000000002, [[29776, 29783, 1.0004457000000002, 1.1924363670000275]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 0, -0.07244396209716797, -0.0724489969415666, [[30002, 30010, -0.0724489969415666, -0.07244396209716797]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 1, -0.07244398094095815, -0.0724489969415666, [[30002, 30010, -0.0724489969415666, -0.07244398094095815]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 2, -0.0724455937743187, -0.07246800406583326, [[28497, 29215, -0.07246800406583326, -0.0724455937743187]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 3, -0.07244561411419302, -0.072468004065939, [[28497, 29215, -0.072468004065939, -0.07244563316074562], [30665, 30670, -0.07244563316074562, -0.07244561411419302]]], ["linear_model.ElasticNetBenchmark.time_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.002437477200010108, 0.002127209099990068, [[29776, 29783, 0.002127209099990068, 0.002437477200010108]]], ["ensemble.GradientBoostingClassifierBenchmark.time_predict('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.056121019500096736, 0.04575886599991463, [[29429, 29435, 0.04575886599991463, 0.056121019500096736]]], ["ensemble.GradientBoostingClassifierBenchmark.time_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.05286075050003092, 0.03754658399998334, [[29429, 29435, 0.03754658399998334, 0.05286075050003092]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 0, 0.10278367200010052, 0.06730766499993024, [[29429, 29435, 0.06730766499993024, 0.0945217194999941], [29768, 29776, 0.0945217194999941, 0.10278367200010052]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.10242281449995971, 0.0678365380000514, [[29429, 29435, 0.0678365380000514, 0.09472550850011885], [29768, 29776, 0.09472550850011885, 0.10242281449995971]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 6.944649688499908, 5.944078384000022, [[29429, 29435, 5.944078384000022, 6.944649688499908]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 3, 6.9146122589999095, 5.989741488999925, [[29429, 29435, 5.989741488999925, 6.9146122589999095]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 0.0013805179999378326, 0.0007659814285554083, [[29429, 29435, 0.0007688613571385108, 0.0013130286249634082], [29768, 29776, 0.0013130286249634082, 0.0013805179999378326]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 0.0013767745000829261, 0.0007682408928368595, [[29429, 29435, 0.0007682408928368595, 0.0009858626363810881], [30545, 30550, 0.0009858626363810881, 0.0013767745000829261]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 0.0015072048333119406, 0.000974174045454261, [[29429, 29435, 0.000974174045454261, 0.0015072048333119406]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('brute', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 0.001758898749964525, 0.0009750611363663418, [[29429, 29435, 0.0009750611363663418, 0.001758898749964525]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 9, 0.012407672000335879, 0.007881215499992322, [[29429, 29435, 0.007881215499992322, 0.008835557749989675], [30945, 30949, 0.008835557749989675, 0.012407672000335879]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 10, 0.033569565499419696, 0.029447855500166042, [[29429, 29435, 0.029447855500166042, 0.033569565499419696]]], ["neighbors.KNeighborsClassifierBenchmark.time_fit('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 11, 0.03338413749952451, 0.02946141600023111, [[29429, 29435, 0.02946141600023111, 0.03338413749952451]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 0, -0.07475552707910538, -0.07475553179776506, [[null, 30502, -0.07475553179776506, -0.07475552707910538]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 1, -0.07475553052041055, -0.07475553176565611, [[29808, 29813, -0.07475553176565611, -0.07475553081876116], [30028, 30035, -0.07475553081876116, -0.07475553052041055]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 2, -0.07475553452968597, -0.07475553497618004, [[30028, 30035, -0.07475553497618004, -0.07475553497247069], [null, 30502, -0.07475553497247069, -0.07475553452968597]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 103350272.0, 90861568.0, [[31041, 32090, 92123136.0, 103350272.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 87556096.0, 74616832.0, [[31041, 32090, 76148736.0, 87556096.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 89333760.0, 75927552.0, [[31041, 32090, 77529088.0, 89333760.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 4, 561745920.0, 522616832.0, [[29572, 29591, 522616832.0, 541575168.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 5, 126636032.0, 113799168.0, [[31041, 32090, 115187712.0, 126636032.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 6, 108130304.0, 95338496.0, [[31041, 32090, 96980992.0, 108130304.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_fit('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 7, 108695552.0, 95617024.0, [[31041, 32090, 97185792.0, 108695552.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 98217984.0, 87117824.0, [[31041, 32090, 88268800.0, 98217984.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 98213888.0, 87093248.0, [[31041, 32090, 88244224.0, 98213888.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 113737728.0, 101203968.0, [[31041, 32090, 102363136.0, 113737728.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_predict('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 113737728.0, 101203968.0, [[31041, 32090, 102363136.0, 113737728.0]]], ["cluster.MiniBatchKMeansBenchmark.track_test_score('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 0, -3.940943717956543, -5.135444641113281, [[28497, 29215, -5.135444641113281, -3.940943717956543]]], ["cluster.MiniBatchKMeansBenchmark.track_test_score('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_test_score.json", {"python": "3.8", "cython": ""}, 1, -3.108213186264038, -3.1083624362945557, [[28497, 29215, -3.1083624362945557, -3.108213186264038]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 80945152.0, 67645440.0, [[31041, 32090, 69120000.0, 80945152.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 80949248.0, 67649536.0, [[31041, 32090, 69120000.0, 80949248.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 84459520.0, 71041024.0, [[31041, 32090, 72617984.0, 84459520.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('brute', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 84443136.0, 71036928.0, [[31041, 32090, 72622080.0, 84443136.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 4, 83550208.0, 70078464.0, [[31041, 32090, 71768064.0, 83550208.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 5, 83550208.0, 70086656.0, [[31041, 32090, 71755776.0, 83550208.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 6, 92094464.0, 78336000.0, [[31041, 32090, 79966208.0, 92094464.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 7, 92094464.0, 78336000.0, [[31041, 32090, 79966208.0, 92094464.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 8, 83517440.0, 70066176.0, [[31041, 32090, 71716864.0, 83517440.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 9, 83517440.0, 70062080.0, [[31041, 32090, 71725056.0, 83517440.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 10, 91856896.0, 78139392.0, [[31041, 32090, 79757312.0, 91856896.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_fit('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 11, 91856896.0, 78139392.0, [[31041, 32090, 79757312.0, 91856896.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 4, 85250048.0, 71094272.0, [[31041, 32090, 72650752.0, 85250048.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 5, 88010752.0, 74592256.0, [[31041, 32090, 76038144.0, 88010752.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 6, 95232000.0, 81330176.0, [[31041, 32090, 82948096.0, 95232000.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 7, 98312192.0, 81231872.0, [[31041, 32090, 82960384.0, 98312192.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 8, 85028864.0, 70955008.0, [[31041, 32090, 72501248.0, 85028864.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 9, 87773184.0, 74440704.0, [[31041, 32090, 75870208.0, 87773184.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 10, 94744576.0, 80932864.0, [[31041, 32090, 82599936.0, 94744576.0]]], ["neighbors.KNeighborsClassifierBenchmark.peakmem_predict('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 11, 97861632.0, 81006592.0, [[31041, 32090, 82552832.0, 97861632.0]]], ["metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'cosine', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json", {"python": "3.8", "cython": ""}, 1, 995737600.0, 881528832.0, [[29443, 29446, 881528832.0, 995737600.0]]], ["metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'manhattan', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json", {"python": "3.8", "cython": ""}, 4, 257814528.0, 244285440.0, [[30145, 30155, 245489664.0, 245960704.0]]], ["metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('dense', 'correlation', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json", {"python": "3.8", "cython": ""}, 6, 251781120.0, 237273088.0, [[31041, 32090, 239529984.0, 251781120.0]]], ["metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances('sparse', 'manhattan', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.peakmem_pairwise_distances.json", {"python": "3.8", "cython": ""}, 12, 195002368.0, 181387264.0, [[31041, 32090, 182956032.0, 195002368.0]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'auto')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 0.1839239480004835, 0.16990794200000892, [[29768, 29776, 0.16990794200000892, 0.1839239480004835]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'svd')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 0.9384877170004984, 0.7077082870000595, [[29429, 29435, 0.7077082870000595, 0.8721067125002264], [29768, 29776, 0.8721067125002264, 0.9384877170004984]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'cholesky')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 0.1816674939996119, 0.16969983799981492, [[29768, 29776, 0.16969983799981492, 0.1816674939996119]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'sparse_cg')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 4, 0.20515116199931072, 0.17772288449987172, [[29768, 29776, 0.17772288449987172, 0.20515116199931072]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'saga')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 8.221493384000496, 6.566381228500177, [[29429, 29435, 6.566381228500177, 8.221493384000496]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'auto')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 7, 0.12927607850042477, 0.10852525499990406, [[29429, 29435, 0.10852525499990406, 0.12927607850042477]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'cholesky')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 9, 5.194330158999946, 4.426838388500073, [[29429, 29435, 4.426838388500073, 5.194330158999946]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'lsqr')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 10, 0.1145862319999651, 0.0909436879999248, [[29429, 29435, 0.0909436879999248, 0.11134417650009709]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'sparse_cg')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 11, 0.12983924199988905, 0.10884381050004777, [[29429, 29435, 0.10884381050004777, 0.12983924199988905]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'saga')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 13, 1.2060327659992254, 0.9948669144998803, [[29429, 29435, 0.9948669144998803, 1.2060327659992254]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 100106240.0, 88055808.0, [[31041, 32090, 88055808.0, 100106240.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 99553280.0, 87676928.0, [[31041, 32090, 87676928.0, 99553280.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 99844096.0, 87941120.0, [[31041, 32090, 87941120.0, 99844096.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 99913728.0, 87957504.0, [[31041, 32090, 87957504.0, 99913728.0]]], ["linear_model.ElasticNetBenchmark.peakmem_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 128458752.0, 115314688.0, [[31041, 32090, 116367360.0, 128458752.0]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 4, 10.377584896999906, 5.7189132469998185, [[29429, 29435, 5.7189132469998185, 8.790683242999876], [30679, 30694, 9.405624714999703, 10.377584896999906]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 5, 12.635107517999131, 6.988539030500306, [[29429, 29435, 6.988539030500306, 11.869692158999896]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 6, 2.75509055800012, 1.852105071500091, [[29429, 29435, 1.852105071500091, 2.75509055800012]]], ["linear_model.LogisticRegressionBenchmark.time_fit('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 7, 3.0337587310000345, 1.8472522849999677, [[29429, 29435, 1.8472522849999677, 3.0337587310000345]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.25424427599978117, 0.19696048499986318, [[29429, 29435, 0.19696048499986318, 0.25424427599978117]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.15377317899992704, 0.06864178599994375, [[29429, 29435, 0.06864178599994375, 0.13039021200006573], [29776, 29783, 0.13039021200006573, 0.15377317899992704]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('sparse', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 1.8535161529998732, 1.2419844685000498, [[29429, 29435, 1.2419844685000498, 1.8535161529998732]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('sparse', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.7554132919999574, 0.32528277099982006, [[29429, 29435, 0.32528277099982006, 0.6583188555000561], [29768, 29776, 0.6583188555000561, 0.7554132919999574]]], ["linear_model.LinearRegressionBenchmark.time_predict('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LinearRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.07332005749981363, 0.02999779849983497, [[29429, 29435, 0.02999779849983497, 0.07332005749981363]]], ["ensemble.GradientBoostingClassifierBenchmark.time_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 12.053724431999854, 4.695657648499946, [[29429, 29435, 4.695657648499946, 12.053724431999854]]], ["cluster.KMeansBenchmark.time_predict('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.009837056000037592, 0.007327421500008313, [[29429, 29435, 0.007327421500008313, 0.008976847250011133]]], ["cluster.KMeansBenchmark.time_predict('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.009865871750037059, 0.007280855499999461, [[29429, 29435, 0.007280855499999461, 0.009061120000012579]]], ["cluster.KMeansBenchmark.time_predict('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 5, 0.03096969550006179, 0.019307464000007712, [[null, 30156, 0.019307464000007712, 0.03096969550006179]]], ["cluster.KMeansBenchmark.time_predict('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 7, 0.03092300699995576, 0.01521101999998109, [[29790, 29795, 0.016851793499995438, 0.03092300699995576]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 12.15160157199989, 6.181946199000095, [[29429, 29435, 6.181946199000095, 10.234541518999777], [29776, 29783, 10.234541518999777, 11.299374638000018]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 12.2896960449998, 8.333827376000045, [[29429, 29435, 8.333827376000045, 12.2896960449998]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 3.436805663500081, 2.0184760459999325, [[29429, 29435, 2.0184760459999325, 3.436805663500081]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 10.596280627999931, 6.671095888499963, [[29429, 29435, 6.671095888499963, 10.596280627999931]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'auto')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.04865560800044477, 0.04527986250059257, [[29768, 29776, 0.04527986250059257, 0.04865560800044477]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'svd')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.04873439250013689, 0.04537838099986402, [[29768, 29776, 0.04537838099986402, 0.04873439250013689]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'cholesky')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.04875643650029815, 0.04508350249989235, [[29768, 29776, 0.04508350249989235, 0.04875643650029815]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'lsqr')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.048763901500024076, 0.044978951499615505, [[29768, 29776, 0.044978951499615505, 0.048763901500024076]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'sparse_cg')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 4, 0.04886832699958177, 0.04498280000007071, [[29768, 29776, 0.04498280000007071, 0.04886832699958177]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'sag')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 5, 0.04870970399952057, 0.04517217400007212, [[29768, 29776, 0.04517217400007212, 0.04870970399952057]]], ["linear_model.RidgeBenchmark.time_predict('dense', 'saga')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 6, 0.048838410999906046, 0.04518474350015822, [[29768, 29776, 0.04518474350015822, 0.048838410999906046]]], ["linear_model.RidgeBenchmark.time_predict('sparse', 'auto')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 7, 0.008774279999897772, 0.007123232500021004, [[29429, 29435, 0.007123232500021004, 0.008774279999897772]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 2.2086317100001907, 1.6445342565000374, [[29429, 29435, 1.6445342565000374, 2.2086317100001907]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('sparse', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 2, 11.68485020900016, 9.329817396999715, [[29429, 29435, 9.329817396999715, 11.339105372000176]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('sparse', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 3, 4.1254891919998045, 2.5183323590003965, [[29429, 29435, 2.5183323590003965, 3.7254366419997496], [29783, 29788, 3.7254366419997496, 4.1254891919998045]]], ["ensemble.RandomForestClassifierBenchmark.peakmem_fit('sparse', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 415879168.0, 382615552.0, [[31041, 32090, 384073728.0, 415879168.0]]], ["ensemble.RandomForestClassifierBenchmark.peakmem_fit('sparse', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 583557120.0, 382621696.0, [[31041, 32090, 384073728.0, 583557120.0]]], ["cluster.MiniBatchKMeansBenchmark.time_predict('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.011599520000004304, 0.007076670499998272, [[29429, 29435, 0.007076670499998272, 0.009678551000092739], [30002, 30010, 0.009678551000092739, 0.011599520000004304]]], ["cluster.MiniBatchKMeansBenchmark.time_predict('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.01003910399998631, 0.007175752499961163, [[29429, 29435, 0.007175752499961163, 0.008954720500014446], [29768, 29776, 0.008954720500014446, 0.01003910399998631]]], ["cluster.MiniBatchKMeansBenchmark.time_predict('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.04333704450004916, 0.02026937499988435, [[null, 29454, 0.02026937499988435, 0.04333704450004916]]], ["cluster.MiniBatchKMeansBenchmark.time_predict('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.04323968300002434, 0.020301649000089128, [[29443, 29446, 0.020301649000089128, 0.04323968300002434]]], ["model_selection.CrossValidationBenchmark.peakmem_crossval(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.peakmem_crossval.json", {"python": "3.8", "cython": ""}, 0, 222187520.0, 208627712.0, [[31041, 32090, 210403328.0, 222187520.0]]], ["model_selection.CrossValidationBenchmark.peakmem_crossval(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.peakmem_crossval.json", {"python": "3.8", "cython": ""}, 1, 122601472.0, 109465600.0, [[31041, 32090, 110780416.0, 122601472.0]]], ["cluster.MiniBatchKMeansBenchmark.track_train_score('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 0, -3.95550537109375, -5.140804767608643, [[28497, 29215, -5.140804767608643, -3.95550537109375]]], ["cluster.MiniBatchKMeansBenchmark.track_train_score('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 1, -3.1156556606292725, -3.1158313751220703, [[28497, 29215, -3.1158313751220703, -3.1156556606292725]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 103108608.0, 90646528.0, [[31041, 32090, 92213248.0, 103108608.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 93667328.0, 81596416.0, [[31041, 32090, 82665472.0, 93667328.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 93736960.0, 81616896.0, [[31041, 32090, 82776064.0, 93736960.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 4, 104148992.0, 91480064.0, [[31041, 32090, 92934144.0, 104148992.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 5, 104144896.0, 91471872.0, [[31041, 32090, 92934144.0, 104144896.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 6, 91873280.0, 79282176.0, [[31041, 32090, 80656384.0, 91873280.0]]], ["linear_model.LogisticRegressionBenchmark.peakmem_predict('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 7, 91877376.0, 79286272.0, [[31041, 32090, 80662528.0, 91877376.0]]], ["svm.SVCBenchmark.peakmem_fit('linear')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 280915968.0, 266887168.0, [[29572, 29591, 266887168.0, 268001280.0]]], ["svm.SVCBenchmark.peakmem_fit('poly')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 280920064.0, 266878976.0, [[29572, 29591, 266878976.0, 268001280.0]]], ["svm.SVCBenchmark.peakmem_fit('rbf')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 280928256.0, 266878976.0, [[29572, 29591, 266878976.0, 267997184.0]]], ["svm.SVCBenchmark.peakmem_fit('sigmoid')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 280907776.0, 266878976.0, [[29572, 29591, 266878976.0, 267997184.0]]], ["linear_model.LassoBenchmark.peakmem_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 128458752.0, 115302400.0, [[31041, 32090, 116492288.0, 128458752.0]]], ["linear_model.LassoBenchmark.peakmem_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 100855808.0, 87793664.0, [[31041, 32090, 89329664.0, 100855808.0]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.0037360741666816466, 0.0033110036667191407, [[29768, 29776, 0.0033110036667191407, 0.0037360741666816466]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.003479095833275399, 0.0029587079999942034, [[29742, 29750, 0.0029587079999942034, 0.003479095833275399]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.002068962900011684, 0.0015545652500274323, [[29429, 29435, 0.0015545652500274323, 0.002068962900011684]]], ["linear_model.LogisticRegressionBenchmark.time_predict('dense', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 3, 0.002073254599872598, 0.001594828666649543, [[29429, 29435, 0.001594828666649543, 0.002073254599872598]]], ["linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'lbfgs', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 4, 0.008229826249930738, 0.006104737249984282, [[29425, 29429, 0.006104737249984282, 0.008229826249930738]]], ["linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'lbfgs', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 5, 0.010718544499923155, 0.006156468000085624, [[29429, 29435, 0.006156468000085624, 0.010718544499923155]]], ["linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 6, 0.006497366000075999, 0.0031171457500249744, [[29429, 29435, 0.0031171457500249744, 0.006497366000075999]]], ["linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 7, 0.006472251249988403, 0.003108011125050325, [[29429, 29435, 0.003108011125050325, 0.006472251249988403]]], ["linear_model.SGDRegressorBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.SGDRegressorBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 3.6811428874998455, 2.868250787000079, [[29429, 29435, 2.868250787000079, 3.6811428874998455]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 97042432.0, 82796544.0, [[31041, 32090, 84553728.0, 97042432.0]]], ["ensemble.GradientBoostingClassifierBenchmark.peakmem_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 137732096.0, 123445248.0, [[31041, 32090, 125181952.0, 137732096.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 0, 131710976.0, 118521856.0, [[31041, 32090, 120074240.0, 131710976.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 1, 131584000.0, 118448128.0, [[31041, 32090, 120064000.0, 131584000.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 2, 129400832.0, 115208192.0, [[31041, 32090, 116719616.0, 129400832.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_transform('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_transform.json", {"python": "3.8", "cython": ""}, 3, 129404928.0, 115171328.0, [[31041, 32090, 116727808.0, 129404928.0]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 0, 0.35336302799987607, 0.14268698000000768, [[29429, 29435, 0.14472420250001505, 0.21666642600007435], [null, 30502, 0.21666642600007435, 0.35336302799987607]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.33678162400019573, 0.19031749699990996, [[29429, 29435, 0.19031749699990996, 0.2791712099999586], [null, 30502, 0.2791712099999586, 0.33678162400019573]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 0.34903030400028, 0.14430166950000967, [[null, 30502, 0.21973356249986864, 0.34903030400028]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 3, 0.3328575200002888, 0.18915657349998583, [[29429, 29435, 0.18915657349998583, 0.2806294154997886], [null, 30260, 0.2806294154997886, 0.3328575200002888]]], ["decomposition.DictionaryLearningBenchmark.time_transform('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.33597187700001996, 0.21053998650006633, [[29429, 29435, 0.21053998650006633, 0.33597187700001996]]], ["decomposition.DictionaryLearningBenchmark.time_transform('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 0.3605742634999842, 0.17617045400004372, [[28497, 29215, 0.17629199900000003, 0.17617045400004372]]], ["decomposition.DictionaryLearningBenchmark.time_transform('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 3, 0.33594549300005383, 0.21017575449991455, [[29429, 29435, 0.21017575449991455, 0.33594549300005383]]], ["manifold.TSNEBenchmark.time_fit('exact')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/manifold.TSNEBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 11.320914042999902, 5.088630448500226, [[29429, 29435, 5.088630448500226, 11.320914042999902]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 0, 101826560.0, 87252992.0, [[31041, 32090, 89260032.0, 101826560.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('dense', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 102715392.0, 89346048.0, [[31041, 32090, 91041792.0, 102715392.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('sparse', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 2, 183271424.0, 147341312.0, [[28497, 29215, 147341312.0, 170203136.0], [31041, 32090, 171456512.0, 183271424.0]]], ["cluster.MiniBatchKMeansBenchmark.peakmem_fit('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.MiniBatchKMeansBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 3, 185290752.0, 148074496.0, [[28497, 29215, 148074496.0, 171051008.0], [31041, 32090, 172433408.0, 185290752.0]]], ["ensemble.HistGradientBoostingClassifierBenchmark.time_fit", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, null, 2.5009271564999835, 1.879087534999826, [[null, 29415, 1.879087534999826, 2.1288411184998495]]], ["linear_model.ElasticNetBenchmark.time_fit('dense', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 0, 1.3423465609998857, 0.8082962149997002, [[29425, 29429, 0.8082962149997002, 1.3423465609998857]]], ["linear_model.ElasticNetBenchmark.time_fit('dense', False)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.8", "cython": ""}, 1, 1.5426730259998749, 0.8214312485001756, [[29425, 29429, 0.8214312485001756, 1.5426730259998749]]], ["cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 0.10267154099994968, 0.06435031950002212, [[29429, 29435, 0.06435031950002212, 0.09706874549999611], [29766, 29768, 0.09706874549999611, 0.10267154099994968]]], ["cluster.KMeansBenchmark.time_transform('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 3, 0.10241049249998468, 0.07129803300000503, [[29429, 29435, 0.07129803300000503, 0.10241049249998468]]], ["linear_model.LassoBenchmark.time_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LassoBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 2, 0.0028186511249828072, 0.00211358219999056, [[29429, 29435, 0.00211358219999056, 0.0028186511249828072]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 0, -4.988476276397705, -4.988476753234863, [[null, 31040, -4.988476753234863, -4.988476276397705]]], ["cluster.KMeansBenchmark.track_train_score('sparse', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 4, -0.9219751358032227, -0.9219752550125122, [[31009, 31019, -0.9219752550125122, -0.9219752550125122]]], ["cluster.KMeansBenchmark.track_train_score('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.8", "cython": ""}, 6, -0.9219751358032227, -0.9219752550125122, [[null, 31041, -0.9219752550125122, -0.9219751358032227]]], ["svm.SVCBenchmark.peakmem_predict('linear')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 0, 214925312.0, 201424896.0, [[31041, 32090, 203014144.0, 214925312.0]]], ["svm.SVCBenchmark.peakmem_predict('poly')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 1, 214925312.0, 201424896.0, [[31041, 32090, 203014144.0, 214925312.0]]], ["svm.SVCBenchmark.peakmem_predict('rbf')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 214925312.0, 201451520.0, [[31041, 32090, 203014144.0, 214925312.0]]], ["svm.SVCBenchmark.peakmem_predict('sigmoid')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 3, 214925312.0, 201424896.0, [[31041, 32090, 203014144.0, 214925312.0]]], ["linear_model.LinearRegressionBenchmark.peakmem_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.LinearRegressionBenchmark.peakmem_fit.json", {"python": "3.8", "cython": ""}, 1, 312299520.0, 294404096.0, [[31041, 32090, 297058304.0, 312299520.0]]], ["linear_model.ElasticNetBenchmark.peakmem_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/linear_model.ElasticNetBenchmark.peakmem_predict.json", {"python": "3.8", "cython": ""}, 2, 100864000.0, 87785472.0, [[31041, 32090, 89325568.0, 100864000.0]]], ["model_selection.GridSearchBenchmark.time_predict(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 0, 0.07944053849996635, 0.04805837400044766, [[29429, 29435, 0.04805837400044766, 0.061927900000227964], [29795, 29798, 0.061927900000227964, 0.07944053849996635]]], ["model_selection.GridSearchBenchmark.time_predict(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.time_predict.json", {"python": "3.8", "cython": ""}, 1, 0.07940275800001473, 0.04805780200013032, [[29429, 29435, 0.04805780200013032, 0.06160099299995636], [29795, 29798, 0.06160099299995636, 0.07940275800001473]]], ["decomposition.PCABenchmark.time_transform('full')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 0, 0.1835508125002434, 0.09774972349998734, [[29429, 29435, 0.09774972349998734, 0.1755720655000914]]], ["decomposition.PCABenchmark.time_transform('arpack')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 1, 0.1826529350000783, 0.08935556799997357, [[29371, 29376, 0.08935556799997357, 0.09930157899998449], [29429, 29435, 0.09930157899998449, 0.17445163200000025]]], ["decomposition.PCABenchmark.time_transform('randomized')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas-null/python-3.8/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_transform.json", {"python": "3.8", "cython": ""}, 2, 0.1826093990002846, 0.09633852199999637, [[29429, 29435, 0.09633852199999637, 0.1746349420000115]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'cosine', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.11", "cython": ""}, 0, 2.068716466999831, 1.0737004809998325, [[null, 33338, 1.0737004809998325, 2.015810868000699]]], ["decomposition.DictionaryLearningBenchmark.track_train_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 1, -0.07231886142615113, -0.07231886144615562, [[null, 33338, -0.07231886144615562, -0.07231886142615113]]], ["decomposition.DictionaryLearningBenchmark.track_train_score('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 3, -0.07231886152126107, -0.07231886154495859, [[null, 33338, -0.07231886154495859, -0.07231886152126107]]], ["svm.SVCBenchmark.time_predict('sigmoid')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 3, 0.7031137019985181, 0.6139816905006228, [[33543, 33546, 0.6139816905006228, 0.7031137019985181]]], ["model_selection.GridSearchBenchmark.time_fit(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 0, 945.3629577170013, 341.92955999100013, [[33546, 33648, 341.92955999100013, 945.3629577170013]]], ["model_selection.GridSearchBenchmark.time_fit(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/model_selection.GridSearchBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 1, 275.2593120170004, 104.69993370100019, [[33546, 33648, 104.69993370100019, 275.2593120170004]]], ["model_selection.CrossValidationBenchmark.time_crossval(1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.time_crossval.json", {"python": "3.11", "cython": ""}, 0, 145.80456604399933, 56.59311816300033, [[33546, 33648, 56.59311816300033, 145.80456604399933]]], ["model_selection.CrossValidationBenchmark.time_crossval(4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/model_selection.CrossValidationBenchmark.time_crossval.json", {"python": "3.11", "cython": ""}, 1, 43.13186384200162, 18.011856807000186, [[33546, 33648, 18.011856807000186, 43.13186384200162]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 3, -0.07509114984802133, -0.07509371825113932, [[null, 33338, -0.07509371825113932, -0.07509114984802133]]], ["svm.SVCBenchmark.time_fit('rbf')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/svm.SVCBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 2, 1.5799147024990816, 1.4258665469988046, [[33359, 33361, 1.4258665469988046, 1.5799147024990816]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 6, 13.704112094001175, 8.217527961000087, [[33546, 33648, 8.217527961000087, 13.704112094001175]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 7, 118.892867655999, 7.752664515001015, [[33546, 33648, 7.752664515001015, 118.892867655999]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'low', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 8, 9.494422158000816, 1.893763650999972, [[33546, 33648, 1.893763650999972, 9.494422158000816]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 9, 89.47836760599967, 5.274313496500326, [[33546, 33648, 5.274313496500326, 89.47836760599967]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 10, 15.559124529001565, 7.032794542999909, [[33546, 33648, 7.032794542999909, 15.559124529001565]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 11, 10.55756757800009, 4.015357905000201, [[33359, 33361, 4.015357905000201, 10.55756757800009]]], ["decomposition.PCABenchmark.time_fit('randomized')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.PCABenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 2, 1.3684700034998514, 1.09559860499985, [[null, 33310, 1.09559860499985, 1.3684700034998514]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 0, -0.07244318723678589, -0.07244402170181274, [[null, 33338, -0.07244402170181274, -0.07244318723678589]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 1, -0.0724431814750343, -0.0724439081840023, [[null, 33338, -0.0724439081840023, -0.0724431814750343]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('lars', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 0, -0.07475551962852478, -0.07475553452968597, [[null, 33338, -0.07475553452968597, -0.07475551962852478]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('lars', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 1, -0.07475552729939185, -0.07475553216947851, [[null, 33338, -0.07475553216947851, -0.07475552729939185]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 2, -0.07475553452968597, -0.07475554198026657, [[null, 33338, -0.07475554198026657, -0.07475553452968597]]], ["decomposition.DictionaryLearningBenchmark.track_test_score('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.DictionaryLearningBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 3, -0.0747555306627162, -0.07475553654479, [[null, 33338, -0.07475553654479, -0.0747555306627162]]], ["linear_model.RidgeBenchmark.time_fit('dense', 'saga')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 6, 12.958227949000502, 12.102378384000076, [[33546, 33648, 12.102378384000076, 12.958227949000502]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.11", "cython": ""}, 2, -4.109885215759277, -4.109886169433594, [[33712, 33715, -4.109886169433594, -4.109885215759277]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 1, 0.1538074810002854, 0.13355942049997793, [[33437, 33444, 0.13355942049997793, 0.1538074810002854]]], ["ensemble.GradientBoostingClassifierBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/ensemble.GradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 0, 6.9965942435001125, 3.234195917999841, [[33546, 33648, 3.234195917999841, 6.9965942435001125]]], ["cluster.KMeansBenchmark.time_predict('sparse', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.time_predict.json", {"python": "3.11", "cython": ""}, 5, 0.028549803000032625, 0.01591946000007738, [[33537, 33543, 0.01591946000007738, 0.028549803000032625]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 3, 16.97975306599983, 9.980928548000065, [[33437, 33444, 9.980928548000065, 16.97975306599983]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 0, 18.63268166999933, 7.890376977999949, [[33546, 33551, 7.890376977999949, 18.63268166999933]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('sparse', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, 3, 103.97959800199988, 3.8619773030000033, [[33546, 33551, 3.8619773030000033, 103.97959800199988]]], ["ensemble.HistGradientBoostingClassifierBenchmark.time_fit", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/ensemble.HistGradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": ""}, null, 7.549271686999873, 2.372120019000022, [[33546, 33551, 2.372120019000022, 7.549271686999873]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 1, -3.0780560970306396, -3.0780563354492188, [[null, 33708, -3.0780563354492188, -3.0780560970306396]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython/joblib/machine-sklearn-benchmark/num_cpu-8/numpy/os-Linux 4.15.0-20-generic/pandas/python-3.11/ram-16424684/scipy/threadpoolctl/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": ""}, 3, -3.0780560970306396, -3.0780563354492188, [[null, 33518, -3.0780563354492188, -3.0780563354492188]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'manhattan', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.11", "cython": "3.0.3"}, 5, 2.623034252999787, 2.1561904800000775, [[34113, 34115, 2.1561904800000775, 2.623034252999787]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.11", "cython": "3.0.3"}, 8, 4.127793399999973, 3.6725709250004, [[null, 34141, 3.6725709250004, 4.127793399999973]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_transform.json", {"python": "3.11", "cython": "3.0.3"}, 6, 3.781139291000045, 3.521388963999925, [[null, 34140, 3.521388963999925, 3.781139291000045]]], ["cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_transform.json", {"python": "3.11", "cython": "3.0.3"}, 7, 3.8138180620001094, 3.5410637559998577, [[null, 34140, 3.5410637559998577, 3.8138180620001094]]], ["linear_model.LassoBenchmark.time_predict('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.3"}, 2, 0.003087816833309868, 0.002283395899985408, [[null, 34140, 0.0026101646999904917, 0.002283395899985408]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": "3.0.3"}, 3, -3.0780560970306396, -3.0780563354492188, [[34162, 34164, -3.0780563354492188, -3.0780560970306396]]], ["cluster.KMeansBenchmark.track_train_score('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.3/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": "3.0.3"}, 7, -0.9221000075340271, -0.9221000671386719, [[34113, 34115, -0.9221000671386719, -0.9221000075340271]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('brute', 'low', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": "0.29.36"}, 1, 0.086020061000454, 0.08140420650033775, [[33813, 33818, 0.08140420650033775, 0.086020061000454]]], ["cluster.MiniBatchKMeansBenchmark.time_transform('sparse', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.MiniBatchKMeansBenchmark.time_transform.json", {"python": "3.11", "cython": "0.29.36"}, 3, 7.531629993500019, 6.888835698500088, [[33820, 33826, 6.888835698500088, 7.531629993500019]]], ["linear_model.RidgeBenchmark.time_fit('sparse', 'sag')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.RidgeBenchmark.time_fit.json", {"python": "3.11", "cython": "0.29.36"}, 12, 2.7997688129999005, 2.5590021950001756, [[33818, 33820, 2.5590021950001756, 2.7997688129999005]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('dense', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": "0.29.36"}, 1, 0.16475128400020367, 0.15381539999998495, [[33826, 33833, 0.15381539999998495, 0.16475128400020367]]], ["cluster.KMeansBenchmark.time_predict('sparse', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_predict.json", {"python": "3.11", "cython": "0.29.36"}, 6, 0.02846665949994076, 0.014001588500036632, [[33818, 33820, 0.014001588500036632, 0.02846665949994076]]], ["linear_model.SGDRegressorBenchmark.time_fit('dense')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.SGDRegressorBenchmark.time_fit.json", {"python": "3.11", "cython": "0.29.36"}, 0, 5.71938168899942, 5.068996183999843, [[33766, 33802, 5.068996183999843, 5.71938168899942]]], ["linear_model.ElasticNetBenchmark.time_fit('dense', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.ElasticNetBenchmark.time_fit.json", {"python": "3.11", "cython": "0.29.36"}, 0, 1.4990876480001134, 1.347287838000284, [[null, 33734, 1.347287838000284, 1.4990876480001134]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-0.29.36/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": "0.29.36"}, 1, -3.0780560970306396, -3.0780563354492188, [[33808, 33813, -3.0780563354492188, -3.0780560970306396]]], ["metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'euclidean', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/metrics.PairwiseDistancesBenchmark.time_pairwise_distances.json", {"python": "3.11", "cython": "3.0.2"}, 11, 2.0897179319995303, 1.865396010999575, [[34031, 34034, 1.865396010999575, 2.0897179319995303]]], ["linear_model.LassoBenchmark.time_fit('sparse', True)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LassoBenchmark.time_fit.json", {"python": "3.11", "cython": "3.0.2"}, 2, 2.7477894640005616, 2.3575837060002414, [[34058, 34065, 2.3575837060002414, 2.7477894640005616]]], ["neighbors.KNeighborsClassifierBenchmark.time_predict('kd_tree', 'high', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/neighbors.KNeighborsClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.2"}, 7, 123.64697125900057, 117.0689821349988, [[34058, 34065, 117.0689821349988, 123.64697125900057]]], ["decomposition.PCABenchmark.time_fit('arpack')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.PCABenchmark.time_fit.json", {"python": "3.11", "cython": "3.0.2"}, 1, 1.46766711950022, 1.0839253939998343, [[34031, 34034, 1.0839253939998343, 1.46766711950022]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.11", "cython": "3.0.2"}, 0, -4.1098856925964355, -4.109886169433594, [[34049, 34052, -4.109886169433594, -4.109886169433594]]], ["cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'random')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_test_score.json", {"python": "3.11", "cython": "3.0.2"}, 2, -4.109885215759277, -4.109886169433594, [[34046, 34049, -4.109886169433594, -4.109886169433594], [34075, 34079, -4.1098856925964355, -4.109885215759277]]], ["ensemble.RandomForestClassifierBenchmark.time_predict('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.2"}, 0, 0.2703902740004196, 0.2379772194999532, [[34052, 34058, 0.2379772194999532, 0.2703902740004196]]], ["ensemble.GradientBoostingClassifierBenchmark.time_fit('sparse')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.GradientBoostingClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": "3.0.2"}, 1, 2.462212150500136, 2.108637685500298, [[34046, 34049, 2.108637685500298, 2.462212150500136]]], ["cluster.KMeansBenchmark.time_predict('sparse', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.2"}, 7, 0.028358634499909385, 0.015978468999946926, [[34049, 34052, 0.015978468999946926, 0.028358634499909385]]], ["decomposition.MiniBatchDictionaryLearningBenchmark.time_fit('cd', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/decomposition.MiniBatchDictionaryLearningBenchmark.time_fit.json", {"python": "3.11", "cython": "3.0.2"}, 2, 3.2055468270000347, 3.050744257500128, [[34052, 34058, 3.050744257500128, 3.2055468270000347]]], ["ensemble.RandomForestClassifierBenchmark.time_fit('dense', 1)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/ensemble.RandomForestClassifierBenchmark.time_fit.json", {"python": "3.11", "cython": "3.0.2"}, 0, 21.906948195999576, 18.536215199000253, [[34052, 34058, 18.536215199000253, 21.906948195999576]]], ["linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 4)", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/linear_model.LogisticRegressionBenchmark.time_predict.json", {"python": "3.11", "cython": "3.0.2"}, 7, 0.006289843499871495, 0.00497264433336871, [[34065, 34068, 0.00497264433336871, 0.006289843499871495]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'lloyd', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": "3.0.2"}, 1, -3.0780560970306396, -3.0780563354492188, [[34065, 34068, -3.0780563354492188, -3.0780560970306396]]], ["cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'k-means++')", "graphs/arch-x86_64/branch-main/cpu-Intel Core Processor (Haswell, no TSX)/cython-3.0.2/joblib-1.3.2/machine-sklearn-benchmark/num_cpu-8/numpy-1.25.2/os-Linux 4.15.0-20-generic/pandas-2.1.0/python-3.11/ram-16424684/scipy-1.11.2/threadpoolctl-3.2.0/cluster.KMeansBenchmark.track_train_score.json", {"python": "3.11", "cython": "3.0.2"}, 3, -3.0780560970306396, -3.0780563354492188, [[34031, 34034, -3.0780563354492188, -3.0780563354492188]]]]} \ No newline at end of file diff --git a/regressions.xml b/regressions.xml index 6d7aafe0a5..62267eb438 100644 --- a/regressions.xml +++ b/regressions.xml @@ -1,14 +1,11 @@ -tag:scikit-learn.asv,1970-01-01:/c56a199a51c70d74ba80d9fe43aea5de364a127d27912e716301f6ed0100464bAirspeed Velocityscikit-learn performance regressions2023-10-24T22:41:02Ztag:scikit-learn.asv,2023-10-24:/6f5c0d96e68ab7f4be9ea1ff2f36bda40b0999ae4fa46694759f76db8c087bc711.46% neighbors.KNeighborsClassifierBenchmark.time_predict('ball_tree', 'high', 1)2023-10-24T22:41:02Z<a href="index.html#neighbors.KNeighborsClassifierBenchmark.time_predict?python=3.11&cython=3.0.3&p-algorithm=%27ball_tree%27&p-dimension=%27high%27&p-n_jobs=1&commits=1f1329f7ecb001eda2ff8e6d6a68bc2054c4962f-e9c74a3f0a5944b1420158d36b1bfed836234b97">11.46% regression</a> on 2023-10-24 13:53:12 in commits <a href="https://github.com/scikit-learn/scikit-learn/commit/../compare/1f1329f7ecb001eda2ff8e6d6a68bc2054c4962f...e9c74a3f0a5944b1420158d36b1bfed836234b97">1f1329f7...e9c74a3f</a>.<br> - New value: 8.20s, old value: 7.36s.<br> - Latest value: 8.20s (11.46% worse - than best value 7.36s).tag:scikit-learn.asv,2023-10-22:/d650ec026940237e1add3fed1442ad225f58931b5e57d2a8231b050eeebd1fba12.40% metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 1)2023-10-22T21:34:55Z<a href="index.html#metrics.PairwiseDistancesBenchmark.time_pairwise_distances?python=3.11&cython=3.0.3&p-representation=%27sparse%27&p-metric=%27cosine%27&p-n_jobs=1&commits=c6d0d29b1903e40c9947c5aa1a2f420fb7f4f004">12.40% regression</a> on 2023-10-22 17:54:01 in commit <a href="https://github.com/scikit-learn/scikit-learn/commit/c6d0d29b1903e40c9947c5aa1a2f420fb7f4f004">c6d0d29b</a>.<br> +tag:scikit-learn.asv,1970-01-01:/c56a199a51c70d74ba80d9fe43aea5de364a127d27912e716301f6ed0100464bAirspeed Velocityscikit-learn performance regressions2023-10-27T20:30:56Ztag:scikit-learn.asv,2023-10-27:/17d893f5f5692eb8888cb9b435874f179edeafd7442a903fffb21e695250522f-0.00% cluster.KMeansBenchmark.track_train_score('dense', 'elkan', 'k-means++')2023-10-27T20:30:56Z<a href="index.html#cluster.KMeansBenchmark.track_train_score?python=3.11&cython=3.0.3&p-representation=%27dense%27&p-algorithm=%27elkan%27&p-init=%27k-means%2B%2B%27&commits=dcebbc4c5c97f886a57b0684a5e943f94db1bd58-5fc67aeb092d636895b599921283221a68c7a2ad">-0.00% regression</a> on 2023-10-27 12:06:01 in commits <a href="https://github.com/scikit-learn/scikit-learn/commit/../compare/dcebbc4c5c97f886a57b0684a5e943f94db1bd58...5fc67aeb092d636895b599921283221a68c7a2ad">dcebbc4c...5fc67aeb</a>.<br> + New value: -3.0780560970306396, old value: -3.0780563354492188.<br> + Latest value: -3.0780560970306396 (-0.00% worse + than best value -3.0780563354492188).tag:scikit-learn.asv,2023-10-22:/d650ec026940237e1add3fed1442ad225f58931b5e57d2a8231b050eeebd1fba12.40% metrics.PairwiseDistancesBenchmark.time_pairwise_distances('sparse', 'cosine', 1)2023-10-22T21:34:55Z<a href="index.html#metrics.PairwiseDistancesBenchmark.time_pairwise_distances?python=3.11&cython=3.0.3&p-representation=%27sparse%27&p-metric=%27cosine%27&p-n_jobs=1&commits=c6d0d29b1903e40c9947c5aa1a2f420fb7f4f004">12.40% regression</a> on 2023-10-22 17:54:01 in commit <a href="https://github.com/scikit-learn/scikit-learn/commit/c6d0d29b1903e40c9947c5aa1a2f420fb7f4f004">c6d0d29b</a>.<br> New value: 4.13s, old value: 3.67s.<br> Latest value: 4.13s (12.40% worse - than best value 3.67s).tag:scikit-learn.asv,2023-10-22:/f3f6a36ad99907243ecf2e6ea1f84b3b1ab0897d79edc7c68bc2a2e7eeef8ef26.91% cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'k-means++')2023-10-22T20:27:17Z<a href="index.html#cluster.KMeansBenchmark.time_transform?python=3.11&cython=3.0.3&p-representation=%27sparse%27&p-algorithm=%27lloyd%27&p-init=%27k-means%2B%2B%27&commits=c6d0d29b1903e40c9947c5aa1a2f420fb7f4f004">6.91% regression</a> on 2023-10-22 17:54:01 in commit <a href="https://github.com/scikit-learn/scikit-learn/commit/c6d0d29b1903e40c9947c5aa1a2f420fb7f4f004">c6d0d29b</a>.<br> - New value: 3.80s, old value: 3.55s.<br> - Latest value: 3.80s (6.91% worse - than best value 3.55s).tag:scikit-learn.asv,2023-10-21:/c9daa25b61eb2e4903922fd4f67c7c72bf444b900a1724f86a7ecf5ec1ee0ce8-12.52% linear_model.LassoBenchmark.time_predict('sparse', True)2023-10-21T21:06:52Z<a href="index.html#linear_model.LassoBenchmark.time_predict?python=3.11&cython=3.0.3&p-representation=%27sparse%27&p-precompute=True&commits=b22c706c700ce4ac24ee26e21fbce8a24ef799a6">-12.52% regression</a> on 2023-10-21 09:09:43 in commit <a href="https://github.com/scikit-learn/scikit-learn/commit/b22c706c700ce4ac24ee26e21fbce8a24ef799a6">b22c706c</a>.<br> + than best value 3.67s).tag:scikit-learn.asv,2023-10-21:/c9daa25b61eb2e4903922fd4f67c7c72bf444b900a1724f86a7ecf5ec1ee0ce8-12.52% linear_model.LassoBenchmark.time_predict('sparse', True)2023-10-21T21:06:52Z<a href="index.html#linear_model.LassoBenchmark.time_predict?python=3.11&cython=3.0.3&p-representation=%27sparse%27&p-precompute=True&commits=b22c706c700ce4ac24ee26e21fbce8a24ef799a6">-12.52% regression</a> on 2023-10-21 09:09:43 in commit <a href="https://github.com/scikit-learn/scikit-learn/commit/b22c706c700ce4ac24ee26e21fbce8a24ef799a6">b22c706c</a>.<br> New value: 2.28ms, old value: 2.61ms.<br> Latest value: 3.09ms (35.23% worse than best value 2.28ms).tag:scikit-learn.asv,2023-10-21:/495e8d2bc6d3144b02ce8a1251bfb5febbbc10157a93c8a9b205fd2c06a8eca07.38% cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'random')2023-10-21T20:27:23Z<a href="index.html#cluster.KMeansBenchmark.time_transform?python=3.11&cython=3.0.3&p-representation=%27sparse%27&p-algorithm=%27elkan%27&p-init=%27random%27&commits=b22c706c700ce4ac24ee26e21fbce8a24ef799a6">7.38% regression</a> on 2023-10-21 09:09:43 in commit <a href="https://github.com/scikit-learn/scikit-learn/commit/b22c706c700ce4ac24ee26e21fbce8a24ef799a6">b22c706c</a>.<br> @@ -17,16 +14,13 @@ than best value 3.52s).tag:scikit-learn.asv,2023-10-21:/cfcd7b733a022f8fcce385fc899f813b1cded17fde05be9515c1d56e9b27f95c7.70% cluster.KMeansBenchmark.time_transform('sparse', 'elkan', 'k-means++')2023-10-21T20:27:23Z<a href="index.html#cluster.KMeansBenchmark.time_transform?python=3.11&cython=3.0.3&p-representation=%27sparse%27&p-algorithm=%27elkan%27&p-init=%27k-means%2B%2B%27&commits=b22c706c700ce4ac24ee26e21fbce8a24ef799a6">7.70% regression</a> on 2023-10-21 09:09:43 in commit <a href="https://github.com/scikit-learn/scikit-learn/commit/b22c706c700ce4ac24ee26e21fbce8a24ef799a6">b22c706c</a>.<br> New value: 3.81s, old value: 3.54s.<br> Latest value: 3.81s (7.70% worse - than best value 3.54s).tag:scikit-learn.asv,2023-10-20:/12a5a21b9208307a89c16f00f364cb9aa54222ef27e844bdd9133cf9828d236b-0.00% cluster.KMeansBenchmark.track_test_score('dense', 'lloyd', 'random')2023-10-20T20:30:33Z<a href="index.html#cluster.KMeansBenchmark.track_test_score?python=3.11&cython=3.0.3&p-representation=%27dense%27&p-algorithm=%27lloyd%27&p-init=%27random%27&commits=b93f80badd1873bf7db9c703879163a9b7aab6c4-fb6b9f59469a4ffcffee2999f531f4bb4c2128fd">-0.00% regression</a> on 2023-10-20 17:51:56 in commits <a href="https://github.com/scikit-learn/scikit-learn/commit/../compare/b93f80badd1873bf7db9c703879163a9b7aab6c4...fb6b9f59469a4ffcffee2999f531f4bb4c2128fd">b93f80ba...fb6b9f59</a>.<br> - New value: -4.109886169433594, old value: -4.109886169433594.<br> - Latest value: -4.109885215759277 (-0.00% worse - than best value -4.109886169433594).tag:scikit-learn.asv,2023-10-19:/c3fc94cced1bf9ee7d5841529b92128e1a1e32bb0b25ff71619d2e4be60f1ad16.52% cluster.KMeansBenchmark.time_transform('sparse', 'lloyd', 'random')2023-10-19T20:27:28Z<a href="index.html#cluster.KMeansBenchmark.time_transform?python=3.11&cython=3.0.3&p-representation=%27sparse%27&p-algorithm=%27lloyd%27&p-init=%27random%27&commits=65923a7850cb7aa128c2422205a1bcad732db54e-b93f80badd1873bf7db9c703879163a9b7aab6c4">6.52% regression</a> on 2023-10-19 11:52:38 in commits <a href="https://github.com/scikit-learn/scikit-learn/commit/../compare/65923a7850cb7aa128c2422205a1bcad732db54e...b93f80badd1873bf7db9c703879163a9b7aab6c4">65923a78...b93f80ba</a>.<br> - New value: 3.80s, old value: 3.57s.<br> - Latest value: 3.80s (6.52% worse - than best value 3.57s).tag:scikit-learn.asv,2023-10-17:/77480c3170662612b4cab8a3eff174bee93cbe3a09b4c914e9de95e0abec840f21.40% metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'manhattan', 4)2023-10-17T21:34:05Z<a href="index.html#metrics.PairwiseDistancesBenchmark.time_pairwise_distances?python=3.11&cython=3.0.3&p-representation=%27dense%27&p-metric=%27manhattan%27&p-n_jobs=4&commits=ebe4c7ea999a32bafc9044ebe75b4901f92037a0-b470ba1bd5c5b4955016f509a6baeb06ffbbafe9">21.40% regression</a> on 2023-10-17 16:48:26 in commits <a href="https://github.com/scikit-learn/scikit-learn/commit/../compare/ebe4c7ea999a32bafc9044ebe75b4901f92037a0...b470ba1bd5c5b4955016f509a6baeb06ffbbafe9">ebe4c7ea...b470ba1b</a>.<br> + than best value 3.54s).tag:scikit-learn.asv,2023-10-17:/77480c3170662612b4cab8a3eff174bee93cbe3a09b4c914e9de95e0abec840f21.65% metrics.PairwiseDistancesBenchmark.time_pairwise_distances('dense', 'manhattan', 4)2023-10-17T21:34:05Z<a href="index.html#metrics.PairwiseDistancesBenchmark.time_pairwise_distances?python=3.11&cython=3.0.3&p-representation=%27dense%27&p-metric=%27manhattan%27&p-n_jobs=4&commits=ebe4c7ea999a32bafc9044ebe75b4901f92037a0-b470ba1bd5c5b4955016f509a6baeb06ffbbafe9">21.65% regression</a> on 2023-10-17 16:48:26 in commits <a href="https://github.com/scikit-learn/scikit-learn/commit/../compare/ebe4c7ea999a32bafc9044ebe75b4901f92037a0...b470ba1bd5c5b4955016f509a6baeb06ffbbafe9">ebe4c7ea...b470ba1b</a>.<br> New value: 2.62s, old value: 2.16s.<br> - Latest value: 2.62s (21.40% worse - than best value 2.16s).tag:scikit-learn.asv,2023-10-03:/3c6abb18e3ca86676132cc21759d2e8f9ee0874e2a796531ab716e8ba9ccacd1-0.00% cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'random')2023-10-03T20:30:49Z<a href="index.html#cluster.KMeansBenchmark.track_test_score?python=3.11&cython=3.0.2&p-representation=%27dense%27&p-algorithm=%27elkan%27&p-init=%27random%27&commits=04e39db499afab852e4e2603807384a402a871a9-286f0c9d17019e52f532d63b5ace9f8e1beb5fe5">-0.00% regression</a> on 2023-10-03 18:25:29 in commits <a href="https://github.com/scikit-learn/scikit-learn/commit/../compare/04e39db499afab852e4e2603807384a402a871a9...286f0c9d17019e52f532d63b5ace9f8e1beb5fe5">04e39db4...286f0c9d</a>.<br> + Latest value: 2.62s (21.65% worse + than best value 2.16s).tag:scikit-learn.asv,2023-10-17:/05b8882ebaad0525848b369363fe215cd3e5806e446ab232b2a6ccb2167dd880-0.00% cluster.KMeansBenchmark.track_train_score('sparse', 'elkan', 'k-means++')2023-10-17T20:30:10Z<a href="index.html#cluster.KMeansBenchmark.track_train_score?python=3.11&cython=3.0.3&p-representation=%27sparse%27&p-algorithm=%27elkan%27&p-init=%27k-means%2B%2B%27&commits=ebe4c7ea999a32bafc9044ebe75b4901f92037a0-b470ba1bd5c5b4955016f509a6baeb06ffbbafe9">-0.00% regression</a> on 2023-10-17 16:48:26 in commits <a href="https://github.com/scikit-learn/scikit-learn/commit/../compare/ebe4c7ea999a32bafc9044ebe75b4901f92037a0...b470ba1bd5c5b4955016f509a6baeb06ffbbafe9">ebe4c7ea...b470ba1b</a>.<br> + New value: -0.9221000075340271, old value: -0.9221000671386719.<br> + Latest value: -0.9221000075340271 (-0.00% worse + than best value -0.9221000671386719).tag:scikit-learn.asv,2023-10-03:/3c6abb18e3ca86676132cc21759d2e8f9ee0874e2a796531ab716e8ba9ccacd1-0.00% cluster.KMeansBenchmark.track_test_score('dense', 'elkan', 'random')2023-10-03T20:30:49Z<a href="index.html#cluster.KMeansBenchmark.track_test_score?python=3.11&cython=3.0.2&p-representation=%27dense%27&p-algorithm=%27elkan%27&p-init=%27random%27&commits=04e39db499afab852e4e2603807384a402a871a9-286f0c9d17019e52f532d63b5ace9f8e1beb5fe5">-0.00% regression</a> on 2023-10-03 18:25:29 in commits <a href="https://github.com/scikit-learn/scikit-learn/commit/../compare/04e39db499afab852e4e2603807384a402a871a9...286f0c9d17019e52f532d63b5ace9f8e1beb5fe5">04e39db4...286f0c9d</a>.<br> New value: -4.109885215759277, old value: -4.1098856925964355.<br> Latest value: -4.109885215759277 (-0.00% worse than best value -4.109886169433594).tag:scikit-learn.asv,2023-09-29:/4fa4af95385b8fa19bd5d462646ad461a154a73ea3a7048c5f01085e0a1858c126.49% linear_model.LogisticRegressionBenchmark.time_predict('sparse', 'saga', 4)2023-10-01T21:42:55Z<a href="index.html#linear_model.LogisticRegressionBenchmark.time_predict?python=3.11&cython=3.0.2&p-representation=%27sparse%27&p-solver=%27saga%27&p-n_jobs=4&commits=bdf66d048c2113e94397b11ff17b7b5c03938ab7-9f6592f714cf1b0fb6f2d8fb636d9e458fad41d5">26.49% regression</a> on 2023-09-29 21:55:08 in commits <a href="https://github.com/scikit-learn/scikit-learn/commit/../compare/bdf66d048c2113e94397b11ff17b7b5c03938ab7...9f6592f714cf1b0fb6f2d8fb636d9e458fad41d5">bdf66d04...9f6592f7</a>.<br>