[ci skip] FIX HistGradientBoosting fitting time too long (INRIA#860) 55577e5

Author: pull[bot]

_sources/python_scripts/ensemble_hist_gradient_boosting.py

@@ -58,7 +58,7 @@
     data,
     target,
     scoring="neg_mean_absolute_error",
-    n_jobs=2,
+    # n_jobs=2,  # Uncomment this line if you run locally
 )
 
 # %%
@@ -122,7 +122,7 @@
     data,
     target,
     scoring="neg_mean_absolute_error",
-    n_jobs=2,
+    # n_jobs=2,  # Uncomment this line if you run locally
 )
 
 # %%
@@ -161,7 +161,7 @@
     data,
     target,
     scoring="neg_mean_absolute_error",
-    n_jobs=2,
+    # n_jobs=2,  # Uncomment this line if you run locally
 )
 
 # %%

_sources/python_scripts/ensemble_hyperparameters.py

@@ -96,7 +96,7 @@
     scoring="neg_mean_absolute_error",
     n_iter=10,
     random_state=0,
-    n_jobs=2,
+    # n_jobs=2,  # Uncomment this line if you run locally
 )
 search_cv.fit(data_train, target_train)
 
@@ -184,7 +184,7 @@
     scoring="neg_mean_absolute_error",
     n_iter=20,
     random_state=0,
-    n_jobs=2,
+    # n_jobs=2, # Uncomment this line if you run locally
 )
 search_cv.fit(data_train, target_train)
 

_sources/python_scripts/ensemble_sol_04.py

@@ -70,7 +70,12 @@
 
 cv = KFold(n_splits=5, shuffle=True, random_state=0)
 results = cross_validate(
-    search, data, target, cv=cv, return_estimator=True, n_jobs=2
+    search,
+    data,
+    target,
+    cv=cv,
+    return_estimator=True,
+    # n_jobs=2  # Uncomment this if you run locally
 )
 
 # %% [markdown]

appendix/notebook_timings.html

@@ -935,15 +935,15 @@ <h1>Notebook timings<a class="headerlink" href="#notebook-timings" title="Link t
 <td><p>✅</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="xref doc reference internal" href="../python_scripts/ensemble_hist_gradient_boosting.html"><span class="doc">python_scripts/ensemble_hist_gradient_boosting</span></a></p></td>
-<td><p>2025-09-10 17:40</p></td>
+<td><p>2025-09-17 11:34</p></td>
 <td><p>cache</p></td>
-<td><p>41.85</p></td>
+<td><p>64.74</p></td>
 <td><p>✅</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="xref doc reference internal" href="../python_scripts/ensemble_hyperparameters.html"><span class="doc">python_scripts/ensemble_hyperparameters</span></a></p></td>
-<td><p>2025-09-10 17:41</p></td>
+<td><p>2025-09-17 11:36</p></td>
 <td><p>cache</p></td>
-<td><p>59.13</p></td>
+<td><p>91.64</p></td>
 <td><p>✅</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="xref doc reference internal" href="../python_scripts/ensemble_introduction.html"><span class="doc">python_scripts/ensemble_introduction</span></a></p></td>
@@ -977,9 +977,9 @@ <h1>Notebook timings<a class="headerlink" href="#notebook-timings" title="Link t
 <td><p>✅</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="xref doc reference internal" href="../python_scripts/ensemble_sol_04.html"><span class="doc">python_scripts/ensemble_sol_04</span></a></p></td>
-<td><p>2025-09-10 17:44</p></td>
+<td><p>2025-09-17 11:37</p></td>
 <td><p>cache</p></td>
-<td><p>38.47</p></td>
+<td><p>57.64</p></td>
 <td><p>✅</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="xref doc reference internal" href="../python_scripts/feature_selection_ex_01.html"><span class="doc">python_scripts/feature_selection_ex_01</span></a></p></td>

python_scripts/ensemble_hist_gradient_boosting.html

@@ -744,7 +744,7 @@ <h1>Speeding-up gradient-boosting<a class="headerlink" href="#speeding-up-gradie
     <span class="n">data</span><span class="p">,</span>
     <span class="n">target</span><span class="p">,</span>
     <span class="n">scoring</span><span class="o">=</span><span class="s2">&quot;neg_mean_absolute_error&quot;</span><span class="p">,</span>
-    <span class="n">n_jobs</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
+    <span class="c1"># n_jobs=2,  # Uncomment this line if you run locally</span>
 <span class="p">)</span>
 </pre></div>
 </div>
@@ -767,8 +767,8 @@ <h1>Speeding-up gradient-boosting<a class="headerlink" href="#speeding-up-gradie
 </div>
 <div class="cell_output docutils container">
 <div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Gradient Boosting Decision Tree
-Mean absolute error via cross-validation: 46.441 ± 2.910 k$
-Average fit time: 7.191 seconds
+Mean absolute error via cross-validation: 46.414 ± 2.914 k$
+Average fit time: 7.233 seconds
 Average score time: 0.008 seconds
 </pre></div>
 </div>
@@ -852,26 +852,28 @@ <h1>Speeding-up gradient-boosting<a class="headerlink" href="#speeding-up-gradie
     <span class="n">data</span><span class="p">,</span>
     <span class="n">target</span><span class="p">,</span>
     <span class="n">scoring</span><span class="o">=</span><span class="s2">&quot;neg_mean_absolute_error&quot;</span><span class="p">,</span>
-    <span class="n">n_jobs</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
+    <span class="c1"># n_jobs=2,  # Uncomment this line if you run locally</span>
 <span class="p">)</span>
 </pre></div>
 </div>
 </div>
 <div class="cell_output docutils container">
 <div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 1 are removed. Consider decreasing the number of bins.
   warnings.warn(
-/opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 1 are removed. Consider decreasing the number of bins.
-  warnings.warn(
-/opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
-  warnings.warn(
 /opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
   warnings.warn(
 /opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 6 are removed. Consider decreasing the number of bins.
   warnings.warn(
-/opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 6 are removed. Consider decreasing the number of bins.
-  warnings.warn(
 /opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 7 are removed. Consider decreasing the number of bins.
   warnings.warn(
+</pre></div>
+</div>
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 1 are removed. Consider decreasing the number of bins.
+  warnings.warn(
+/opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
+  warnings.warn(
+/opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 6 are removed. Consider decreasing the number of bins.
+  warnings.warn(
 /opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 7 are removed. Consider decreasing the number of bins.
   warnings.warn(
 </pre></div>
@@ -884,7 +886,9 @@ <h1>Speeding-up gradient-boosting<a class="headerlink" href="#speeding-up-gradie
   warnings.warn(
 /opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 7 are removed. Consider decreasing the number of bins.
   warnings.warn(
-/opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 1 are removed. Consider decreasing the number of bins.
+</pre></div>
+</div>
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 1 are removed. Consider decreasing the number of bins.
   warnings.warn(
 /opt/hostedtoolcache/Python/3.9.23/x64/lib/python3.9/site-packages/sklearn/preprocessing/_discretization.py:306: UserWarning: Bins whose width are too small (i.e., &lt;= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
   warnings.warn(
@@ -923,8 +927,8 @@ <h1>Speeding-up gradient-boosting<a class="headerlink" href="#speeding-up-gradie
 </div>
 <div class="cell_output docutils container">
 <div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Gradient Boosting Decision Tree with KBinsDiscretizer
-Mean absolute error via cross-validation: 45.781 ± 2.019 k$
-Average fit time: 4.459 seconds
+Mean absolute error via cross-validation: 45.771 ± 2.026 k$
+Average fit time: 4.466 seconds
 Average score time: 0.010 seconds
 </pre></div>
 </div>
@@ -952,7 +956,7 @@ <h1>Speeding-up gradient-boosting<a class="headerlink" href="#speeding-up-gradie
     <span class="n">data</span><span class="p">,</span>
     <span class="n">target</span><span class="p">,</span>
     <span class="n">scoring</span><span class="o">=</span><span class="s2">&quot;neg_mean_absolute_error&quot;</span><span class="p">,</span>
-    <span class="n">n_jobs</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
+    <span class="c1"># n_jobs=2,  # Uncomment this line if you run locally</span>
 <span class="p">)</span>
 </pre></div>
 </div>
@@ -976,7 +980,7 @@ <h1>Speeding-up gradient-boosting<a class="headerlink" href="#speeding-up-gradie
 <div class="cell_output docutils container">
 <div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Histogram Gradient Boosting Decision Tree
 Mean absolute error via cross-validation: 43.758 ± 2.694 k$
-Average fit time: 0.509 seconds
+Average fit time: 0.506 seconds
 Average score time: 0.061 seconds
 </pre></div>
 </div>