DOC Ensure StackingClassifier pass numpydoc validation (scikit-learn#21135)

EricEllwanger · frellwan · glemaitre · glemaitre · commit 9f50ed782748 · 2021-10-23T12:01:05.000+02:00
Co-authored-by: frellwan &lt;frellwan@hotmail.com&gt;
Co-authored-by: Guillaume Lemaitre &lt;g.lemaitre58@gmail.com&gt;
diff --git a/maint_tools/test_docstrings.py b/maint_tools/test_docstrings.py
@@ -37,7 +37,6 @@
     "SpectralCoclustering",
     "SpectralEmbedding",
     "SplineTransformer",
-    "StackingClassifier",
     "StackingRegressor",
     "TransformedTargetRegressor",
 ]
diff --git a/sklearn/ensemble/_stacking.py b/sklearn/ensemble/_stacking.py
@@ -387,6 +387,10 @@ class StackingClassifier(ClassifierMixin, _BaseStacking):
     stack_method_ : list of str
         The method used by each base estimator.
 
+    See Also
+    --------
+    StackingRegressor : Stack of estimators with a final regressor.
+
     Notes
     -----
     When `predict_proba` is used by each estimator (i.e. most of the time for
@@ -424,7 +428,6 @@ class StackingClassifier(ClassifierMixin, _BaseStacking):
     ... )
     >>> clf.fit(X_train, y_train).score(X_test, y_test)
     0.9...
-
     """
 
     def __init__(
@@ -477,6 +480,7 @@ def fit(self, X, y, sample_weight=None):
         Returns
         -------
         self : object
+            Returns a fitted instance of estimator.
         """
         check_classification_targets(y)
         self._le = LabelEncoder().fit(y)
@@ -509,8 +513,7 @@ def predict(self, X, **predict_params):
 
     @if_delegate_has_method(delegate="final_estimator_")
     def predict_proba(self, X):
-        """Predict class probabilities for X using
-        `final_estimator_.predict_proba`.
+        """Predict class probabilities for `X` using the final estimator.
 
         Parameters
         ----------
@@ -529,8 +532,7 @@ def predict_proba(self, X):
 
     @if_delegate_has_method(delegate="final_estimator_")
     def decision_function(self, X):
-        """Predict decision function for samples in X using
-        `final_estimator_.decision_function`.
+        """Decision function for samples in `X` using the final estimator.
 
         Parameters
         ----------

Original file line number	Diff line number	Diff line change
`@@ -37,7 +37,6 @@`
`37`	`37`	`"SpectralCoclustering",`
`38`	`38`	`"SpectralEmbedding",`
`39`	`39`	`"SplineTransformer",`
`40`		`- "StackingClassifier",`
`41`	`40`	`"StackingRegressor",`
`42`	`41`	`"TransformedTargetRegressor",`
`43`	`42`	`]`