[MRG] DOC solve rendering set_params in Voting and Stacking (#15074)

scikit-learn · Sep 24, 2019 · 6ea1873 · 6ea1873
1 parent 93c628e
commit 6ea1873
Show file tree

Hide file tree

Showing 2 changed files with 22 additions and 10 deletions.
diff --git a/sklearn/ensemble/_stacking.py b/sklearn/ensemble/_stacking.py
@@ -80,11 +80,17 @@ def set_params(self, **params):
 
         Examples
         --------
-        # In this example, the RandomForestClassifier is removed
-        clf1 = LogisticRegression()
-        clf2 = RandomForestClassifier()
-        eclf = StackingClassifier(estimators=[('lr', clf1), ('rf', clf2)]
-        eclf.set_params(rf='drop')
+        In this example, the RandomForestClassifier is removed.
+
+        >>> from sklearn.linear_model import LogisticRegression
+        >>> from sklearn.ensemble import RandomForestClassifier
+        >>> from sklearn.ensemble import VotingClassifier
+        >>> clf1 = LogisticRegression()
+        >>> clf2 = RandomForestClassifier()
+        >>> eclf = StackingClassifier(estimators=[('lr', clf1), ('rf', clf2)])
+        >>> eclf.set_params(rf='drop')
+        StackingClassifier(estimators=[('lr', LogisticRegression()),
+                                        ('rf', 'drop')])
         """
         super()._set_params('estimators', **params)
         return self

diff --git a/sklearn/ensemble/voting.py b/sklearn/ensemble/voting.py
@@ -109,11 +109,17 @@ def set_params(self, **params):
 
         Examples
         --------
-        # In this example, the RandomForestClassifier is removed
-        clf1 = LogisticRegression()
-        clf2 = RandomForestClassifier()
-        eclf = VotingClassifier(estimators=[('lr', clf1), ('rf', clf2)]
-        eclf.set_params(rf=None)
+        In this example, the RandomForestClassifier is removed.
+
+        >>> from sklearn.linear_model import LogisticRegression
+        >>> from sklearn.ensemble import RandomForestClassifier
+        >>> from sklearn.ensemble import VotingClassifier
+        >>> clf1 = LogisticRegression()
+        >>> clf2 = RandomForestClassifier()
+        >>> eclf = VotingClassifier(estimators=[('lr', clf1), ('rf', clf2)])
+        >>> eclf.set_params(rf=None)
+        VotingClassifier(estimators=[('lr', LogisticRegression()),
+                                     ('rf', None)])
         """
         return self._set_params('estimators', **params)