Ejemplo n.º 1
0
def init_X(data_matrix):
    X_init = data_matrix.sample_latent_values(
        np.zeros((data_matrix.m, data_matrix.n)), 1.)
    svd_K = min(20, data_matrix.m // 4, data_matrix.n // 4)
    svd_K = max(svd_K, 2)  # 0 and 1 cause it to crash
    _, _, _, _, _, X_init = low_rank.fit_model(data_matrix, svd_K, 10)
    return X_init
def init_X(data):
    svd_K = min(20, data.shape[0] // 4, data.shape[1] // 4)
    svd_K = max(svd_K, 2)   # 1 and 0 cause it to crash
    dummy = observations.DataMatrix(data)
    _, _, _, _, _, X = low_rank.fit_model(dummy, svd_K, 10)
    return X
def init_X(data_matrix):
    X_init = data_matrix.sample_latent_values(np.zeros((data_matrix.m, data_matrix.n)), 1.)
    svd_K = min(20, data_matrix.m // 4, data_matrix.n // 4)
    svd_K = max(svd_K, 2)  # 0 and 1 cause it to crash
    _, _, _, _, _, X_init = low_rank.fit_model(data_matrix, svd_K, 10)
    return X_init
Ejemplo n.º 4
0
def init_X(data):
    svd_K = min(20, data.shape[0] // 4, data.shape[1] // 4)
    svd_K = max(svd_K, 2)  # 1 and 0 cause it to crash
    dummy = observations.DataMatrix(data)
    _, _, _, _, _, X = low_rank.fit_model(dummy, svd_K, 10)
    return X