sparse_to_dense.py 文件源码

def sparse_dense(summary):
    text_copy = copy.deepcopy(summary)
    """
    Find a suitable value for the hyperparameter, some random value like 0.5, or based
    on some heuristic like (rank of original matrix/10), or (max_singular_value of the
    original matrix / 20)
    """
    _, s, _ = randomized_svd(summary, 1, n_iter=5)
    hyperparameter = s[0] / 50

    term_document_matrix_rank = np.linalg.matrix_rank(summary)
    iterations = int(term_document_matrix_rank / 10) 

    A_new = dense(text_copy, hyperparameter, 0.02, iterations)

    return A_new