Skip to content

Commit

Permalink
update tests
Browse files Browse the repository at this point in the history
  • Loading branch information
@jackgerrits
jackgerrits committed Aug 15, 2023
1 parent 9bfc2c1 commit 043648e
Show file tree
Hide file tree
Showing 5 changed files with 30 additions and 30 deletions.
10 changes: 5 additions & 5 deletions test/pred-sets/ref/cats_save.predict
View file
Original file line number Diff line number Diff line change
@@ -1,10 +1,10 @@
0.0012017498,0.00625
0.6113522,0.40625
0.5820448,0.40625
2.2343192,0.40625
20.461426,0.00625
1.2286053,0.40625
10.350056,0.00625
22.592487,0.00625
2.2877245,0.40625
1.3163464,0.40625
2.1290207,0.40625
18.205719,0.00625
9.585819,0.00625
1.7801242,0.40625
0.8038121,0.40625
12 changes: 6 additions & 6 deletions test/train-sets/ref/0001-replay.stderr
View file
Original file line number Diff line number Diff line change
Expand Up @@ -18,18 +18,18 @@ loss last counter weight label predict feat
0.250000 0.250000 8 8.0 0.0000 0.0000 860
0.312500 0.375000 16 16.0 1.0000 0.0000 128
0.343750 0.375000 32 32.0 0.0000 0.0000 176
0.350946 0.358141 64 64.0 0.0000 0.0275 350
0.371181 0.391417 128 128.0 1.0000 0.1510 620
0.292717 0.214252 256 256.0 0.0000 0.3660 410
0.149202 0.005688 512 512.0 0.0000 0.0000 278
0.074603 0.000004 1024 1024.0 1.0000 1.0000 170
0.359375 0.375000 64 64.0 0.0000 0.0275 350
0.414062 0.468750 128 128.0 1.0000 0.1510 620
0.433594 0.453125 256 256.0 0.0000 0.3660 410
0.441406 0.449219 512 512.0 0.0000 0.0000 278
0.453125 0.464844 1024 1024.0 1.0000 1.0000 170

finished run
number of examples per pass = 200
passes used = 8
weighted example sum = 1600.000000
weighted label sum = 728.000000
average loss = 0.047746
average loss = 0.455000
best constant = 0.455000
best constant's loss = 0.247975
total feature number = 717536
14 changes: 7 additions & 7 deletions test/train-sets/ref/cats-train.stderr
View file
Original file line number Diff line number Diff line change
Expand Up @@ -15,17 +15,17 @@ Input label = CONTINUOUS
Output pred = ACTION_PDF_VALUE
average since example example current current current
loss last counter weight label predict features
0.000000 0.000000 1 1.0 {185.12,0.6... 6324.15,0 10
0.000000 0.000000 2 2.0 {772.59,0.4... 16299.34,0 10
0.226921 0.453841 4 4.0 {14122,0.02,0} 17754.81,0 10
0.321934 0.416948 8 8.0 {12715.1,0.... 17248.12,0 10
0.200445 0.078955 16 16.0 {669.12,0.4... 14987.98,0 10
0.165127 0.129809 32 32.0 {10786.7,0.... 13866.5,0 10
1.774796 1.774796 1 1.0 {185.12,0.6... 188.57,0 10
0.887398 0.000000 2 2.0 {772.59,0.4... 12189.73,0 10
0.670619 0.453841 4 4.0 {14122,0.02,0} 16299.34,0 10
0.543784 0.416948 8 8.0 {12715.1,0.... 17754.81,0 10
0.311369 0.078955 16 16.0 {669.12,0.4... 17248.12,0 10
0.256310 0.201250 32 32.0 {10786.7,0.... 14987.98,0 10

finished run
number of examples = 57
weighted example sum = 57.000000
weighted label sum = 57.000000
average loss = 0.186361
average loss = 0.231863
total feature number = 570
Learn() count per node: id=0, #l=17; id=1, #l=0; id=2, #l=0;
16 changes: 8 additions & 8 deletions test/train-sets/ref/cats_room_temp.stderr
View file
Original file line number Diff line number Diff line change
Expand Up @@ -15,18 +15,18 @@ Input label = CONTINUOUS
Output pred = ACTION_PDF_VALUE
average since example example current current current
loss last counter weight label predict features
1095.824 1095.824 1 1.0 {0,25,0} 2.14,0.09 3
547.9122 0.000000 2 2.0 {4.07,21.1,... 41.54,0 3
273.9561 0.000000 4 4.0 {72.94,5.26,0} 88.24,0 3
136.9780 0.000000 8 8.0 {67.13,2.93... 71.98,0 3
68.48903 0.000000 16 16.0 {6.01,19.35,0} 51.44,0.09 3
34.30662 0.124206 32 32.0 {59.57,0.92... 49.41,0.09 3
18.39109 2.475568 64 64.0 {23.4,7.08,0} 50.56,0.09 3
1095.824 1095.824 1 1.0 {0,25,0} 0,0 3
582.1616 68.49878 2 2.0 {4.07,21.1,... 2.14,0.09 3
291.0808 0.000000 4 4.0 {72.94,5.26,0} 41.54,0 3
145.5404 0.000000 8 8.0 {67.13,2.93... 88.24,0 3
72.80454 0.068661 16 16.0 {6.01,19.35,0} 71.98,0 3
36.48046 0.156381 32 32.0 {59.57,0.92... 51.44,0.09 3
18.24775 0.015050 64 64.0 {23.4,7.08,0} 49.41,0.09 3

finished run
number of examples = 100
weighted example sum = 100.000000
weighted label sum = 100.000000
average loss = 11.778620
average loss = 11.691978
total feature number = 300
Learn() count per node: id=0, #l=32; id=1, #l=18; id=2, #l=44; id=3, #l=10; id=4, #l=20; id=5, #l=48; id=6, #l=12; id=7, #l=8; id=8, #l=6; id=9, #l=7; id=10, #l=18; id=11, #l=28; id=12, #l=9; id=13, #l=9; id=14, #l=3; id=15, #l=0;
8 changes: 4 additions & 4 deletions test/train-sets/ref/cats_save.stderr
View file
Original file line number Diff line number Diff line change
Expand Up @@ -17,10 +17,10 @@ Input label = CONTINUOUS
Output pred = ACTION_PDF_VALUE
average since example example current current current
loss last counter weight label predict features
0.000000 0.000000 1 1.0 {0,0,0.01} 0.61,0.41 6
0.000000 0.000000 2 2.0 {0.58,0,0.41} 2.23,0.41 6
0.000000 0.000000 4 4.0 {10.35,0,0.01} 22.59,0.01 6
0.000000 0.000000 8 8.0 {2.41,0,0.41} 9.59,0.01 6
0.000000 0.000000 1 1.0 {0,0,0.01} 0,0.01 6
0.000000 0.000000 2 2.0 {0.58,0,0.41} 0.61,0.41 6
0.000000 0.000000 4 4.0 {10.35,0,0.01} 2.23,0.41 6
0.000000 0.000000 8 8.0 {2.41,0,0.41} 22.59,0.01 6

finished run
number of examples = 10
Expand Down

0 comments on commit 043648e

Please