摘要： 利用Chameleon算法进行K值选择、相似度函数阈值选择时需要人为给出一些参数，在没有先验知识的情况下，人为确定此类参数难度较大。针对该问题介绍模块度概念，根据结构等价相似度和模块度概念提出一种聚类算法——M-Chameleon。实验结果证明，M-Chameleon可以客观地反映实际聚类情况。

关键词: 聚类算法, Chameleon算法, 结构等价相似度, 模块度

Abstract: It is found that some parameters should be determined by hand when using Chameleon algorithm to choose K value and the threshold value of similarity degree function. It is difficult to determine these parameters without any prior domain knowledge. Aiming at this problem, this paper introduces modularity theory and proposes a clustering algorithm——M-Chameleon according to the structural equivalence similarity degree and modularity theory. Experimental results confirm that M-Chameleon can reflect the actual clustering situation objectively.

Key words: clustering algorithm, Chameleon algorithm, structural equivalence similarity degree, modularity

中图分类号: 

• TP301.6