A RELAXATION APPROACH TO THE FUZZY CLUSTERING PROBLEM

被引：19

作者：

KAMEL, MS ^{[1
]}

SELIM, SZ ^{[1
]}

机构：

[1] KING FAHD UNIV PETR & MINERALS,DEPT SYST ENGN,DHAHRAN,SAUDI ARABIA

来源：

FUZZY SETS AND SYSTEMS | 1994年 / 61卷 / 02期

关键词：

FUZZY C-MEANS ALGORITHM; FUZZY CLUSTERING; RELAXATION TECHNIQUES; CLUSTER ANALYSIS; PATTERN RECOGNITION;

D O I：

10.1016/0165-0114(94)90232-1

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper a new algorithm for fuzzy clustering is presented. The proposed algorithm utilizes the idea of relaxation. Convergence of the proposed algorithm is proved and limits on the relaxation parameter are derived. Stopping criteria and resulting convergence behaviour of the algorithms are discussed. The performance of the new algorithm is compared to the fuzzy c-means algorithm by testing both on three published data sets. Theoretical and empirical results reported in this paper show that the new algorithm is more efficient and leads to significant computational savings.

引用

页码：177 / 188

页数：12