DOC fix docsting of fit_transform in Voting estimator
@@ -91,6 +91,30 @@ class _BaseVoting(TransformerMixin, _BaseHeterogeneousEnsemble):
return self
+ def fit_transform(self, X, y=None, **fit_params):
+ """Return class labels or probabilities for each estimator.
+
+ Return predictions for X for each estimator.
+
+ Parameters
+ ----------
+ X : {array-like, sparse matrix, dataframe} of shape \
+ (n_samples, n_features)
+ Input samples
+
+ y : ndarray of shape (n_samples,), default=None
+ Target values (None for unsupervised transformations).
+
+ **fit_params : dict
+ Additional fit parameters.
+
+ Returns
+ -------
+ X_new : ndarray array of shape (n_samples, n_features_new)
+ Transformed array.
+ """
+ return super().fit_transform(X, y, **fit_params)
+
@property
def n_features_in_(self):
# For consistency with other estimators we raise a AttributeError so
