def METHOD_NAME(self, X, y):
    """Fit time series classifier to training data.
    private _fit containing the core logic, called from fit
    Writes to self:
        Sets fitted model attributes ending in "_".
    Parameters
    ----------
    X : guaranteed to be of a type in self.get_tag("X_inner_mtype")
        if self.get_tag("X_inner_mtype") = "numpy3D":
            3D np.ndarray of shape = [n_instances, n_channels, series_length]
        for list of other mtypes, see datatypes.SCITYPE_REGISTER
    y : 1D np.array of int, of shape [n_instances] - class labels for fitting
        indices correspond to instance indices in X
    Returns
    -------
    self : Reference to self.
    """
    estimator = self._get_delegate()
    estimator.fit(X=X, y=y)
    return self