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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _modelmat(self, X, term=-1):
 """ Builds a model matrix, B, out of the spline basis for each feature 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)