A cluster validity index for fuzzy clustering

被引：88
|
作者：
Zhang, Yunjie [1 ]
Wang, Weina [1 ,2 ]
Zhang, Xiaona [1 ]
Li, Yi [3 ]
机构：
[1] Dalian Maritime Univ, Dept Math, Dalian 116026, Peoples R China
[2] Jilin Inst Chem Technol, Dept Math, Jilin 132022, Peoples R China
[3] Heilongjiang Inst Sci & Technol, Dept Comp & Informat Engn, Harbin 150027, Peoples R China
来源：
INFORMATION SCIENCES | 2008年 / 178卷 / 04期
基金：
中国国家自然科学基金;
关键词：
fuzzy clustering; cluster validity; fuzzy c-means;
D O I：
10.1016/j.ins.2007.10.004
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new cluster validity index is proposed for the validation of partitions of object data produced by the fuzzy c-means algorithm. The proposed validity index uses a variation measure and a separation measure between two fuzzy clusters. A good fuzzy partition is expected to have a low degree of variation and a large separation distance. Testing of the proposed index and nine previously formulated indices on well-known data sets shows the superior effectiveness and reliability of the proposed index in comparison to other indices and the robustness of the proposed index in noisy environments. (c) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码：1205 / 1218
页数：14
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