test.py 文件源码

def column_average_ari(Zv, Zc, cc_state_object):
    from sklearn.metrics import adjusted_rand_score
    ari = 0
    n_cols = len(Zv)
    for col in xrange(n_cols):
        view_t = Zv[col]
        Zc_true = Zc[view_t]

        view_i = cc_state_object.Zv[col]
        Zc_inferred = cc_state_object.views[view_i].Z.tolist()
        ari += adjusted_rand_score(Zc_true, Zc_inferred)

    return ari/float(n_cols)