neighbors.py 文件源码

def decision_function(self, X):
        """Compute the distances to the nearest centroid for
        an array of test vectors X.

        Parameters
        ----------
        X : array-like, shape = [n_samples, n_features]
        Returns
        -------
        C : array, shape = [n_samples]
        """
        from sklearn.metrics.pairwise import pairwise_distances
        from sklearn.utils.validation import check_array, check_is_fitted

        check_is_fitted(self, 'centroids_')

        X = check_array(X, accept_sparse='csr')

        return pairwise_distances(X, self.centroids_,
                                  metric=self.metric).min(axis=1)