e970678d95f88bf5a793c4686f3a5a341bfb002c,sklearn/cluster/_feature_agglomeration.py,AgglomerationTransform,transform,#AgglomerationTransform#Any#,24

Before Change

        
        check_is_fitted(self)

        X = check_array(X)
        if len(self.labels_) != X.shape[1]:
            raise ValueError("X has a different number of features than "
                             "during fitting.")
        if self.pooling_func == np.mean and not issparse(X):

After Change

        
        check_is_fitted(self)

        X = self._validate_data(X, reset=False)
        if self.pooling_func == np.mean and not issparse(X):
            size = np.bincount(self.labels_)
            n_samples = X.shape[0]
            // a fast way to compute the mean of grouped features

Instances