A New Clustering Validity Function for the Fuzzy C-means Algorithm

被引：5

作者：

Wang, Jiesheng ^{[1
]}

机构：

[1] Liaoning Univ Sci & Technol, Sch Elect & Informat Engn, Anshan 114051, Peoples R China

来源：

2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11 | 2008年

关键词：

Fuzzy Partition; Fuzzy C-means Clustering; Clustering Validity Function;

D O I：

10.1109/CCDC.2008.4597770

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Fuzzy C-means (FCM) clustering algorithm is the unsupervised extraction of groups from an unlabelled data set with no prior knowledge of the underlying data structure. However there is a major limitation that exists in this method. A predefined number of clusters must be given in advance. In this paper, we propose a new validity index to deal with this situation. The performance evaluation of the proposed cluster validity index compares favorably with that of several validity functions and shows the effectiveness.

引用

页码：2477 / 2480

页数：4

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