本文简要介绍python语言中 sklearn.metrics.adjusted_mutual_info_score 的用法。 用法: sklearn.metrics.adjusted_mutual_info_score(labels_true, labels_pred, *, average_method='arithmetic') 两个聚类之间的调整互信息。 调整后的互信息 (AMI) 是对互
python 复制 import numpy as np from sklearn.feature_selection importmutual_info_regression from sc...
在 sklearn 的文档中，很明显函数 normalized_mutual_info_score 应该只输出 0 到 1 之间的值。但是...
def benchmarking(gtlabels, labels): # TODO: Please note that the AMI definition used in the paper differs from that in the sklearn python package. # TODO: Please modify it accordingly. numeval = len(gtlabels) ari = metrics.adjusted_rand_score(gtlabels[:numeval], labels[:numeval]) ami...
本文简要介绍python语言中sklearn.metrics.normalized_mutual_info_score的用法。 用法: sklearn.metrics.normalized_mutual_info_score(labels_true, labels_pred, *, average_method='arithmetic') 两个聚类之间的标准化互信息。 归一化互信息 (NMI) 是互信息 (MI) 分数的归一化,用于在 0(无互信息)和 1(完全...