docs updates [skip ci] (1237)

dev/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 527b5840c3454457e2b962b627e1a759
+config: 962629305630707192acd85740e4005f
 tags: 645f666f9bcd5a90fca523b33c5a78b7

dev/_modules/sktree/ensemble/_honest_forest.html

@@ -394,8 +394,7 @@ <h1>Source code for sktree.ensemble._honest_forest</h1><div class="highlight"><p
 <span class="kn">from</span> <span class="nn">sklearn.ensemble._base</span> <span class="kn">import</span> <span class="n">_partition_estimators</span>
 <span class="kn">from</span> <span class="nn">sklearn.utils.validation</span> <span class="kn">import</span> <span class="n">check_is_fitted</span><span class="p">,</span> <span class="n">check_X_y</span>
 
-<span class="kn">from</span> <span class="nn">sktree._lib.sklearn.ensemble._forest</span> <span class="kn">import</span> <span class="n">ForestClassifier</span>
-
+<span class="kn">from</span> <span class="nn">.._lib.sklearn.ensemble._forest</span> <span class="kn">import</span> <span class="n">ForestClassifier</span>
 <span class="kn">from</span> <span class="nn">.._lib.sklearn.tree</span> <span class="kn">import</span> <span class="n">_tree</span> <span class="k">as</span> <span class="n">_sklearn_tree</span>
 <span class="kn">from</span> <span class="nn">..tree</span> <span class="kn">import</span> <span class="n">HonestTreeClassifier</span>
 

dev/_modules/sktree/ensemble/_supervised_forest.html

@@ -386,16 +386,15 @@
   <h1>Source code for sktree.ensemble._supervised_forest</h1><div class="highlight"><pre>
 <span></span><span class="kn">from</span> <span class="nn">sklearn.utils._param_validation</span> <span class="kn">import</span> <span class="n">StrOptions</span>
 
-<span class="kn">from</span> <span class="nn">sktree._lib.sklearn.ensemble._forest</span> <span class="kn">import</span> <span class="n">ForestClassifier</span><span class="p">,</span> <span class="n">ForestRegressor</span>
-<span class="kn">from</span> <span class="nn">sktree.tree</span> <span class="kn">import</span> <span class="p">(</span>
+<span class="kn">from</span> <span class="nn">.._lib.sklearn.ensemble._forest</span> <span class="kn">import</span> <span class="n">ForestClassifier</span><span class="p">,</span> <span class="n">ForestRegressor</span>
+<span class="kn">from</span> <span class="nn">..tree</span> <span class="kn">import</span> <span class="p">(</span>
     <span class="n">ExtraObliqueDecisionTreeClassifier</span><span class="p">,</span>
     <span class="n">ExtraObliqueDecisionTreeRegressor</span><span class="p">,</span>
     <span class="n">ObliqueDecisionTreeClassifier</span><span class="p">,</span>
     <span class="n">ObliqueDecisionTreeRegressor</span><span class="p">,</span>
     <span class="n">PatchObliqueDecisionTreeClassifier</span><span class="p">,</span>
     <span class="n">PatchObliqueDecisionTreeRegressor</span><span class="p">,</span>
 <span class="p">)</span>
-
 <span class="kn">from</span> <span class="nn">..tree._neighbors</span> <span class="kn">import</span> <span class="n">SimMatrixMixin</span>
 
 

dev/_modules/sktree/ensemble/_unsupervised_forest.html

@@ -409,10 +409,9 @@ <h1>Source code for sktree.ensemble._unsupervised_forest</h1><div class="highlig
 <span class="kn">from</span> <span class="nn">sklearn.utils.parallel</span> <span class="kn">import</span> <span class="n">Parallel</span><span class="p">,</span> <span class="n">delayed</span>
 <span class="kn">from</span> <span class="nn">sklearn.utils.validation</span> <span class="kn">import</span> <span class="n">_check_sample_weight</span><span class="p">,</span> <span class="n">check_is_fitted</span><span class="p">,</span> <span class="n">check_random_state</span>
 
-<span class="kn">from</span> <span class="nn">sktree._lib.sklearn.ensemble._forest</span> <span class="kn">import</span> <span class="n">BaseForest</span>
-<span class="kn">from</span> <span class="nn">sktree._lib.sklearn.tree._tree</span> <span class="kn">import</span> <span class="n">DTYPE</span>
-<span class="kn">from</span> <span class="nn">sktree.tree</span> <span class="kn">import</span> <span class="n">UnsupervisedDecisionTree</span><span class="p">,</span> <span class="n">UnsupervisedObliqueDecisionTree</span>
-
+<span class="kn">from</span> <span class="nn">.._lib.sklearn.ensemble._forest</span> <span class="kn">import</span> <span class="n">BaseForest</span>
+<span class="kn">from</span> <span class="nn">.._lib.sklearn.tree._tree</span> <span class="kn">import</span> <span class="n">DTYPE</span>
+<span class="kn">from</span> <span class="nn">..tree</span> <span class="kn">import</span> <span class="n">UnsupervisedDecisionTree</span><span class="p">,</span> <span class="n">UnsupervisedObliqueDecisionTree</span>
 <span class="kn">from</span> <span class="nn">..tree._neighbors</span> <span class="kn">import</span> <span class="n">SimMatrixMixin</span>
 
 

dev/_modules/sktree/tree/_honest_tree.html

@@ -394,8 +394,8 @@ <h1>Source code for sktree.tree._honest_tree</h1><div class="highlight"><pre>
 <span class="kn">from</span> <span class="nn">sklearn.utils.multiclass</span> <span class="kn">import</span> <span class="n">_check_partial_fit_first_call</span><span class="p">,</span> <span class="n">check_classification_targets</span>
 <span class="kn">from</span> <span class="nn">sklearn.utils.validation</span> <span class="kn">import</span> <span class="n">check_is_fitted</span><span class="p">,</span> <span class="n">check_X_y</span>
 
-<span class="kn">from</span> <span class="nn">sktree._lib.sklearn.tree</span> <span class="kn">import</span> <span class="n">DecisionTreeClassifier</span>
-<span class="kn">from</span> <span class="nn">sktree._lib.sklearn.tree._classes</span> <span class="kn">import</span> <span class="n">BaseDecisionTree</span>
+<span class="kn">from</span> <span class="nn">.._lib.sklearn.tree</span> <span class="kn">import</span> <span class="n">DecisionTreeClassifier</span>
+<span class="kn">from</span> <span class="nn">.._lib.sklearn.tree._classes</span> <span class="kn">import</span> <span class="n">BaseDecisionTree</span>
 
 
 <div class="viewcode-block" id="HonestTreeClassifier">

dev/auto_examples/plot_extended_isolation_forest.html

@@ -653,8 +653,8 @@ <h2>References<a class="headerlink" href="#references" title="Link to this headi
 </aside>
 </aside>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 9.156 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  9 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 8.487 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  10 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-extended-isolation-forest-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/eb7a2353d9db47038439f571ba87ba60/plot_extended_isolation_forest.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_extended_isolation_forest.py</span></code></a></p>

dev/auto_examples/plot_extra_oblique_random_forest.html

@@ -510,16 +510,16 @@ <h2>References<a class="headerlink" href="#references" title="Link to this headi
 n_repeats        1
                                     time_taken
 dataset          dimension   model
-PhishingWebsites (2000, 30)  EORF     1.051757
-                             ORF      1.012484
-cnae-9           (864, 856)  EORF     2.045270
-                             ORF      2.465740
-har              (2000, 561) EORF     1.862489
-                             ORF      5.695959
-lsvt             (100, 310)  EORF     1.109698
-                             ORF      1.333007
-wdbc             (455, 30)   EORF     0.752730
-                             ORF      1.067983
+PhishingWebsites (2000, 30)  EORF     0.976945
+                             ORF      0.998603
+cnae-9           (864, 856)  EORF     1.921912
+                             ORF      2.187879
+har              (2000, 561) EORF     1.556118
+                             ORF      5.214936
+lsvt             (100, 310)  EORF     0.859620
+                             ORF      0.991344
+wdbc             (455, 30)   EORF     0.726950
+                             ORF      1.063367
 /home/circleci/.pyenv/versions/3.9.18/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
   if pd.api.types.is_categorical_dtype(vector):
 /home/circleci/.pyenv/versions/3.9.18/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
@@ -771,8 +771,8 @@ <h2>References<a class="headerlink" href="#references" title="Link to this headi
 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 53.612 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  133 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 35.880 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  127 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-extra-oblique-random-forest-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/fe83a26431a514151ddfc59a4b25896a/plot_extra_oblique_random_forest.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_extra_oblique_random_forest.py</span></code></a></p>

dev/auto_examples/plot_extra_orf_sample_size.html

@@ -607,8 +607,8 @@ <h2>References<a class="headerlink" href="#references" title="Link to this headi
 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (2 minutes 54.742 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  174 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (3 minutes 16.784 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  158 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-extra-orf-sample-size-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/47a0f99ed91a41ad89e274c306824ef4/plot_extra_orf_sample_size.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_extra_orf_sample_size.py</span></code></a></p>

dev/auto_examples/plot_iris_dtc.html

@@ -539,7 +539,7 @@
 <li><img src="../_images/sphx_glr_plot_iris_dtc_003.png" srcset="../_images/sphx_glr_plot_iris_dtc_003.png" alt="Axis-aligned decision tree trained on all the iris features" class = "sphx-glr-multi-img"/></li>
 <li><img src="../_images/sphx_glr_plot_iris_dtc_004.png" srcset="../_images/sphx_glr_plot_iris_dtc_004.png" alt="Oblique decision tree trained on all the iris features" class = "sphx-glr-multi-img"/></li>
 </ul>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 4.204 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 4.363 seconds)</p>
 <p><strong>Estimated memory usage:</strong>  9 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-iris-dtc-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">

dev/auto_examples/plot_oblique_axis_aligned_forests_sparse_parity.html

@@ -424,7 +424,7 @@
 of the sum of data <code class="docutils literal notranslate"><span class="pre">X</span></code> across first <code class="docutils literal notranslate"><span class="pre">p*</span></code> features that are greater than 0,
 otherwise the label is defined as 0. The simulation is further detailed
 in this [publication](<a class="reference external" href="https://epubs.siam.org/doi/epdf/10.1137/1.9781611974973.56">https://epubs.siam.org/doi/epdf/10.1137/1.9781611974973.56</a>).</p>
-<img src="../_images/sphx_glr_plot_oblique_axis_aligned_forests_sparse_parity_001.png" srcset="../_images/sphx_glr_plot_oblique_axis_aligned_forests_sparse_parity_001.png" alt="Sparse Parity" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>It took 13 seconds to run the script
+<img src="../_images/sphx_glr_plot_oblique_axis_aligned_forests_sparse_parity_001.png" srcset="../_images/sphx_glr_plot_oblique_axis_aligned_forests_sparse_parity_001.png" alt="Sparse Parity" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>It took 12 seconds to run the script
 /home/circleci/.pyenv/versions/3.9.18/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
   if pd.api.types.is_categorical_dtype(vector):
 /home/circleci/.pyenv/versions/3.9.18/lib/python3.9/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
@@ -535,8 +535,8 @@
 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span>
 </pre></div>
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-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 14.257 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  9 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 13.176 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  10 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-oblique-axis-aligned-forests-sparse-parity-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/8790845c18cb6b37069e014b150a7cb1/plot_oblique_axis_aligned_forests_sparse_parity.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_oblique_axis_aligned_forests_sparse_parity.py</span></code></a></p>

dev/auto_examples/plot_oblique_forests_iris.html

@@ -571,8 +571,8 @@
 <span class="c1"># and ExtraObliqueDecisionTree result in distinct decision boundaries.</span>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 34.629 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  134 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 29.032 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  128 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-oblique-forests-iris-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/dc083ccdf5b4abd93884efac359614b5/plot_oblique_forests_iris.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_oblique_forests_iris.py</span></code></a></p>

dev/auto_examples/plot_oblique_random_forest.html

@@ -613,8 +613,8 @@
     <a href="https://numpy.org/devdocs/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">ax</span></a><span class="p">[</span><a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">i</span></a><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">&quot;&quot;</span><span class="p">)</span>
 </pre></div>
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-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 27.814 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  273 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 27.442 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  274 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-oblique-random-forest-py">
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 <p><a class="reference download internal" download="" href="../_downloads/31e055577373b3e8c688c3fcf1304e84/plot_oblique_random_forest.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_oblique_random_forest.py</span></code></a></p>

dev/auto_examples/plot_overlapping_gaussians.html

@@ -603,8 +603,8 @@ <h2>References<a class="headerlink" href="#references" title="Link to this headi
 <span class="c1"># curve, compared to RF which is shown below.</span>
 </pre></div>
 </div>
-<img src="../_images/sphx_glr_plot_overlapping_gaussians_001.png" srcset="../_images/sphx_glr_plot_overlapping_gaussians_001.png" alt="plot overlapping gaussians" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 24.015 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  53 MB</p>
+<img src="../_images/sphx_glr_plot_overlapping_gaussians_001.png" srcset="../_images/sphx_glr_plot_overlapping_gaussians_001.png" alt="plot overlapping gaussians" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 22.769 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  54 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-overlapping-gaussians-py">
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 <p><a class="reference download internal" download="" href="../_downloads/ed8294c8526ffbb9799792531e2f729f/plot_overlapping_gaussians.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_overlapping_gaussians.py</span></code></a></p>