Transform labels back to original encoding.

        Parameters
        ----------
        y : numpy array of shape [n_samples]
            Target values.

        Returns
        -------
        y : numpy array of shape [n_samples]

def inverse_transform(self, y):
        """Transform labels back to original encoding.

        Parameters
        ----------
        y : numpy array of shape [n_samples]
            Target values.

        Returns
        -------
        y : numpy array of shape [n_samples]
        """
        check_is_fitted(self, 'classes_')

        diff = np.setdiff1d(y, np.arange(len(self.classes_)))
        if diff:
            raise ValueError("y contains new labels: %s" % str(diff))
        y = np.asarray(y)
        return self.classes_[y]