An Adaptive Cluster Validity Index for the Fuzzy C-means

被引：0
|
作者：
Chen Duo [1 ,2 ]
Li Xue [1 ,3 ]
Cui Du-Wu [1 ]
机构：
[1] Xian Univ Technol, Sch Comp Sci & Engn, Xian 710048, Shaanxi, Peoples R China
[2] TangShan Coll, Comp Ctr, Tangshan 063000, Peoples R China
[3] Shaanxi Normal Univ, Int Business Sch, Xian 710062, Shaanxi, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2007年 / 7卷 / 02期
关键词：
Cluster Analysis; Cluster Validity Index; Fuzzy C-means Clustering; Fuzzy Set;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Based on the basic theory of fuzzy set, this paper suggests the notion of FCM fuzzy set, which is subject to the constraint condition of fuzzy c-means clustering algorithm. The cluster fuzzy degree and the lattice degree of approaching for the FCM fuzzy set are presented, and their functions in the validation process of fuzzy clustering are deeply analyzed. A new cluster validity index is proposed, in which the two factors such as the cluster fuzzy degree and the lattice degree of approaching are taken into comprehensive account. The notable advantage of the index is that it can adaptively adjust the relative significance levels of the two factors. Also, this paper gives the algorithm to apply the cluster validity index to the cluster validation for the fuzzy c-means algorithm. The experimental results indicate the effectiveness and adaptability of the proposed cluster validity index.
引用
收藏
页码：146 / 156
页数：11
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