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diff --git a/‎dev/_sources/auto_examples/applications/plot_face_recognition.rst.txt
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diff --git a/‎dev/_sources/auto_examples/applications/plot_model_complexity_influence.rst.txt
Lines changed: 14 additions & 14 deletions b/‎dev/_sources/auto_examples/applications/plot_model_complexity_influence.rst.txt
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diff --git a/‎dev/_sources/auto_examples/applications/plot_out_of_core_classification.rst.txt
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diff --git a/‎dev/_sources/auto_examples/applications/plot_outlier_detection_housing.rst.txt
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Lines changed: 1 addition & 1 deletion
@@ -80,7 +80,7 @@
       },
       "outputs": [],
       "source": [
-        "from sklearn.metrics import precision_recall_curve\nimport matplotlib.pyplot as plt\nfrom sklearn.externals.funcsigs import signature\n\nprecision, recall, _ = precision_recall_curve(y_test, y_score)\n\n# In matplotlib < 1.5, plt.fill_between does not have a 'step' argument\nstep_kwargs = ({'step': 'post'}\n               if 'step' in signature(plt.fill_between).parameters\n               else {})\nplt.step(recall, precision, color='b', alpha=0.2,\n         where='post')\nplt.fill_between(recall, precision, alpha=0.2, color='b', **step_kwargs)\n\nplt.xlabel('Recall')\nplt.ylabel('Precision')\nplt.ylim([0.0, 1.05])\nplt.xlim([0.0, 1.0])\nplt.title('2-class Precision-Recall curve: AP={0:0.2f}'.format(\n          average_precision))"
+        "from sklearn.metrics import precision_recall_curve\nimport matplotlib.pyplot as plt\nfrom sklearn.utils.fixes import signature\n\nprecision, recall, _ = precision_recall_curve(y_test, y_score)\n\n# In matplotlib < 1.5, plt.fill_between does not have a 'step' argument\nstep_kwargs = ({'step': 'post'}\n               if 'step' in signature(plt.fill_between).parameters\n               else {})\nplt.step(recall, precision, color='b', alpha=0.2,\n         where='post')\nplt.fill_between(recall, precision, alpha=0.2, color='b', **step_kwargs)\n\nplt.xlabel('Recall')\nplt.ylabel('Precision')\nplt.ylim([0.0, 1.05])\nplt.xlim([0.0, 1.0])\nplt.title('2-class Precision-Recall curve: AP={0:0.2f}'.format(\n          average_precision))"
       ]
     },
     {
 
@@ -137,7 +137,7 @@
 # ................................
 from sklearn.metrics import precision_recall_curve
 import matplotlib.pyplot as plt
-from sklearn.externals.funcsigs import signature
+from sklearn.utils.fixes import signature
 
 precision, recall, _ = precision_recall_curve(y_test, y_score)
Original file line number	Diff line number	Diff line change
`@@ -80,7 +80,7 @@`
`80`	`80`	`},`
`81`	`81`	`"outputs": [],`
`82`	`82`	`"source": [`
`83`		- "from sklearn.metrics import precision_recall_curve\nimport matplotlib.pyplot as plt\nfrom sklearn.externals.funcsigs import signature\n\nprecision, recall, _ = precision_recall_curve(y_test, y_score)\n\n# In matplotlib < 1.5, plt.fill_between does not have a 'step' argument\nstep_kwargs = ({'step': 'post'}\n if 'step' in signature(plt.fill_between).parameters\n else {})\nplt.step(recall, precision, color='b', alpha=0.2,\n where='post')\nplt.fill_between(recall, precision, alpha=0.2, color='b', **step_kwargs)\n\nplt.xlabel('Recall')\nplt.ylabel('Precision')\nplt.ylim([0.0, 1.05])\nplt.xlim([0.0, 1.0])\nplt.title('2-class Precision-Recall curve: AP={0:0.2f}'.format(\n average_precision))"
	`83`	+ "from sklearn.metrics import precision_recall_curve\nimport matplotlib.pyplot as plt\nfrom sklearn.utils.fixes import signature\n\nprecision, recall, _ = precision_recall_curve(y_test, y_score)\n\n# In matplotlib < 1.5, plt.fill_between does not have a 'step' argument\nstep_kwargs = ({'step': 'post'}\n if 'step' in signature(plt.fill_between).parameters\n else {})\nplt.step(recall, precision, color='b', alpha=0.2,\n where='post')\nplt.fill_between(recall, precision, alpha=0.2, color='b', **step_kwargs)\n\nplt.xlabel('Recall')\nplt.ylabel('Precision')\nplt.ylim([0.0, 1.05])\nplt.xlim([0.0, 1.0])\nplt.title('2-class Precision-Recall curve: AP={0:0.2f}'.format(\n average_precision))"
`84`	`84`	`]`
`85`	`85`	`},`
`86`	`86`	`{`