scikit-learn
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diff --git a/‎dev/_images/sphx_glr_plot_agglomerative_clustering_001.png
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@@ -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: 023183ae1f8c81adaf3d63c25fbc3952
+config: 66b6375e600dade30dd955ba89cf197f
 tags: 645f666f9bcd5a90fca523b33c5a78b7
@@ -66,15 +66,16 @@
 # ---------------------------------------------------
 
 import matplotlib.pyplot as plt
+import pandas as pd
 
-n_scores = len(rfecv.cv_results_["mean_test_score"])
+cv_results = pd.DataFrame(rfecv.cv_results_)
 plt.figure()
 plt.xlabel("Number of features selected")
 plt.ylabel("Mean test accuracy")
 plt.errorbar(
-    range(min_features_to_select, n_scores + min_features_to_select),
-    rfecv.cv_results_["mean_test_score"],
-    yerr=rfecv.cv_results_["std_test_score"],
+    x=cv_results["n_features"],
+    y=cv_results["mean_test_score"],
+    yerr=cv_results["std_test_score"],
 )
 plt.title("Recursive Feature Elimination \nwith correlated features")
 plt.show()
 
@@ -58,7 +58,7 @@
       },
       "outputs": [],
       "source": [
-        "import matplotlib.pyplot as plt\n\nn_scores = len(rfecv.cv_results_[\"mean_test_score\"])\nplt.figure()\nplt.xlabel(\"Number of features selected\")\nplt.ylabel(\"Mean test accuracy\")\nplt.errorbar(\n    range(min_features_to_select, n_scores + min_features_to_select),\n    rfecv.cv_results_[\"mean_test_score\"],\n    yerr=rfecv.cv_results_[\"std_test_score\"],\n)\nplt.title(\"Recursive Feature Elimination \\nwith correlated features\")\nplt.show()"
+        "import matplotlib.pyplot as plt\nimport pandas as pd\n\ncv_results = pd.DataFrame(rfecv.cv_results_)\nplt.figure()\nplt.xlabel(\"Number of features selected\")\nplt.ylabel(\"Mean test accuracy\")\nplt.errorbar(\n    x=cv_results[\"n_features\"],\n    y=cv_results[\"mean_test_score\"],\n    yerr=cv_results[\"std_test_score\"],\n)\nplt.title(\"Recursive Feature Elimination \\nwith correlated features\")\nplt.show()"
       ]
     },
     {
Original file line number	Diff line number	Diff line change
`@@ -58,7 +58,7 @@`
`58`	`58`	`},`
`59`	`59`	`"outputs": [],`
`60`	`60`	`"source": [`
`61`		`- "import matplotlib.pyplot as plt\n\nn_scores = len(rfecv.cv_results_[\"mean_test_score\"])\nplt.figure()\nplt.xlabel(\"Number of features selected\")\nplt.ylabel(\"Mean test accuracy\")\nplt.errorbar(\n range(min_features_to_select, n_scores + min_features_to_select),\n rfecv.cv_results_[\"mean_test_score\"],\n yerr=rfecv.cv_results_[\"std_test_score\"],\n)\nplt.title(\"Recursive Feature Elimination \\nwith correlated features\")\nplt.show()"`
	`61`	`+ "import matplotlib.pyplot as plt\nimport pandas as pd\n\ncv_results = pd.DataFrame(rfecv.cv_results_)\nplt.figure()\nplt.xlabel(\"Number of features selected\")\nplt.ylabel(\"Mean test accuracy\")\nplt.errorbar(\n x=cv_results[\"n_features\"],\n y=cv_results[\"mean_test_score\"],\n yerr=cv_results[\"std_test_score\"],\n)\nplt.title(\"Recursive Feature Elimination \\nwith correlated features\")\nplt.show()"`
`62`	`62`	`]`
`63`	`63`	`},`
`64`	`64`	`{`