Pushing the docs to dev/ for branch: master, commit 3a6c8c4b6ce17b84b01d47b66ead1797c04931bc

Author: sklearn-ci

dev/_downloads/3409d9766d352cc9f9b169d4a799a87a/auto_examples_python.zip

@@ -98,7 +98,6 @@
 # which will plot the partial dependence curves of each model on the same axes.
 # The length of the axes list must be equal to the number of plots drawn.
 
-# Sets this image as the thumbnail for sphinx gallery
 # sphinx_gallery_thumbnail_number = 4
 fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 6))
 tree_disp.plot(ax=[ax1, ax2], line_kw={"label": "Decision Tree"})

dev/_downloads/713967aff070bffaf8a2f98a0b9c0d95/plot_partial_dependence_visualization_api.py

@@ -116,7 +116,7 @@
       },
       "outputs": [],
       "source": [
-        "# Sets this image as the thumbnail for sphinx gallery\nfig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 6))\ntree_disp.plot(ax=[ax1, ax2], line_kw={\"label\": \"Decision Tree\"})\nmlp_disp.plot(ax=[ax1, ax2], line_kw={\"label\": \"Multi-layer Perceptron\",\n                                      \"c\": \"red\"})\nax1.legend()\nax2.legend()"
+        "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 6))\ntree_disp.plot(ax=[ax1, ax2], line_kw={\"label\": \"Decision Tree\"})\nmlp_disp.plot(ax=[ax1, ax2], line_kw={\"label\": \"Multi-layer Perceptron\",\n                                      \"c\": \"red\"})\nax1.legend()\nax2.legend()"
       ]
     },
     {