def score(self, X, y=None):
        """Inertia score (sum of all distances to closest cluster).

        Parameters
        ----------
        X : {array-like, sparse matrix}, shape = [n_samples, n_features]
            New data.

        Returns
        -------
        score : float
            Larger score is better.
        """
        if self.normalize:
            X = normalize(X)

        check_is_fitted(self, "cluster_centers_")
        X = self._check_test_data(X)
        return -_labels_inertia(X, self.cluster_centers_)[1]