Args:
            L: An [n, m] scipy.sparse matrix of labels
        Returns:
            output: A [n, k] np.ndarray of probabilistic labels

def predict_proba(self, L):
        """
        Args:
            L: An [n, m] scipy.sparse matrix of labels
        Returns:
            output: A [n, k] np.ndarray of probabilistic labels
        """
        n = L.shape[0]
        Y_p = np.random.rand(n, self.k)
        Y_p /= Y_p.sum(axis=1).reshape(-1, 1)
        return Y_p