Returns
        -------
        np.array with columns as categories and rows as terms

def get_term_count_mat(self):
        '''
        Returns
        -------
        np.array with columns as categories and rows as terms
        '''
        freq_mat = np.zeros(shape=(self.get_num_terms(), self.get_num_categories()), dtype=int)
        for cat_i in range(self.get_num_categories()):
            X = (self._X[self._y == cat_i, :] > 0).astype(int)
            freq_mat[:, cat_i] = X.sum(axis=0)
        return freq_mat