def METHOD_NAME(self, X, y=None) -> float:
    """Score the quality of the clusterer.
    Parameters
    ----------
    X : np.ndarray (2d or 3d array of shape (n_instances, series_length) or shape
        (n_instances, n_channels, series_length)).
        Time series instances to train clusterer and then have indexes each belong
        to return.
    y: ignored, exists for API consistency reasons.
    Returns
    -------
    score : float
        Score of the clusterer.
    """
    self.check_is_fitted()
    X = self._preprocess_collection(X)
    return self._score(X, y)