txmeans.py 文件源码

def loglikelihood(num_points, num_dims, clusters, distances_dict_values_cl):
    ll = 0
    variance = cluster_variance(num_points, clusters, distances_dict_values_cl) or np.nextafter(0, 1)
    # print 'var', variance
    for cluster in clusters:
        fRn = len(cluster)
        t1 = fRn * np.log(fRn)
        t2 = fRn * np.log(num_points)
        t3 = ((fRn * num_dims) / 2.0) * np.log((2.0 * np.pi) * variance)
        t4 = (fRn - 1.0) / 2.0
        ll += t1 - t2 - t3 - t4
    return ll