birch.py 文件源码

def predict(self, X):
        """
        Predict data using the ``centroids_`` of subclusters.

        Avoid computation of the row norms of X.

        Parameters
        ----------
        X : {array-like, sparse matrix}, shape (n_samples, n_features)
            Input data.

        Returns
        -------
        labels : ndarray, shape(n_samples)
            Labelled data.
        """
        X = check_array(X, accept_sparse='csr')
        self._check_fit(X)
        reduced_distance = safe_sparse_dot(X, self.subcluster_centers_.T)
        reduced_distance *= -2
        reduced_distance += self._subcluster_norms
        return self.subcluster_labels_[np.argmin(reduced_distance, axis=1)]