evaluation.py 文件源码

def kendall(y, z, nb_sample=100000):
    """Compute Kendall's correlation coefficient."""
    if len(y) > nb_sample:
        idx = np.arange(len(y))
        np.random.shuffle(idx)
        idx = idx[:nb_sample]
        y = y[idx]
        z = z[idx]
    return kendalltau(y, z)[0]