a19d398c1c974eb69d6e8e5e41d65500262089ce,imblearn/under_sampling/_prototype_selection/_edited_nearest_neighbours.py,RepeatedEditedNearestNeighbours,_fit_resample,#RepeatedEditedNearestNeighbours#Any#Any#,298

Before Change

            X_, y_, = X_enn, y_enn
            if self.return_indices:
                idx_under = idx_under[idx_enn]

            if b_conv or b_min_bec_maj or b_remove_maj_class:
                if b_conv:
                    if self.return_indices:
                        X_, y_, = X_enn, y_enn
                        idx_under = idx_under[idx_enn]
                    else:
                        X_, y_, = X_enn, y_enn
                break

        X_resampled, y_resampled = X_, y_

        if self.return_indices:
            return X_resampled, y_resampled, idx_under
        else:
            return X_resampled, y_resampled

After Change

    def _fit_resample(self, X, y):
        if self.return_indices:
            deprecate_parameter(self, "0.4", "return_indices",
                                "sample_indices_")
        self._validate_estimator()

        X_, y_ = X, y
        self.sample_indices_ = np.arange(X.shape[0], dtype=int)

Instances