Builds a model matrix, B, out of the spline basis for each feature

        B = [B_0, B_1, ..., B_p]

        Parameters
        ---------
        X : array-like of shape (n_samples, m_features)
            containing the input dataset
        term : int, optional
            term index for which to compute the model matrix
            if -1, will create the model matrix for all features

        Returns
        -------
        modelmat : sparse matrix of len n_samples
            containing model matrix of the spline basis for selected features

def _modelmat(self, X, term=-1):
        """
        Builds a model matrix, B, out of the spline basis for each feature

        B = [B_0, B_1, ..., B_p]

        Parameters
        ---------
        X : array-like of shape (n_samples, m_features)
            containing the input dataset
        term : int, optional
            term index for which to compute the model matrix
            if -1, will create the model matrix for all features

        Returns
        -------
        modelmat : sparse matrix of len n_samples
            containing model matrix of the spline basis for selected features
        """
        X = check_X(X, n_feats=self.statistics_['m_features'],
                    edge_knots=self.edge_knots_, dtypes=self.dtype,
                    features=self.feature, verbose=self.verbose)

        return self.terms.build_columns(X, term=term)