2e7c0700d00da702cdccb7c19b6fe1857b5bd1b7,imblearn/under_sampling/prototype_generation/cluster_centroids.py,ClusterCentroids,_sample,#ClusterCentroids#Any#Any#,111

Before Change

        X_resampled = np.concatenate((centroids))

        if sparse.issparse(X):
            X_resampled = sparse.vstack([sparse.csr_matrix(X_resampled),
                                         safe_indexing(X, idx_under)])
        else:
            X_resampled = np.vstack((X_resampled, safe_indexing(X, idx_under)))
        y_resampled = np.hstack((y_resampled, safe_indexing(y, idx_under)))

After Change

        
        self._validate_estimator()

        if self.voting == "auto":
            if sparse.issparse(X):
                self.voting_ = "hard"
            else:
                self.voting_ = "soft"
        else:
            if self.voting in VOTING_KIND:
                self.voting_ = self.voting
            else:
                raise ValueError(""voting" needs to be one of {}. Got {}"
                                 " instead.".format(VOTING_KIND, self.voting))

        X_resampled, y_resampled = [], []
        for target_class in np.unique(y):
            if target_class in self.ratio_.keys():
                n_samples = self.ratio_[target_class]

Instances