Unsupervised fuzzy clustering

被引：39

作者：

Zahid, N ^{[1
]}

Abouelala, O ^{[1
]}

Limouri, M ^{[1
]}

Essaid, A ^{[1
]}

机构：

[1] Univ Mohammed V, AGDAL, Fac Sci, Lab Concept & Syst, Rabat, Morocco

来源：

PATTERN RECOGNITION LETTERS | 1999年 / 20卷 / 02期

关键词：

fuzzy clustering; pattern recognition; K-nearest neighbours; cluster-validity;

D O I：

10.1016/S0167-8655(98)00142-1

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a new algorithm is proposed to carry out fuzzy clustering without making assumptions on initial guesses. The search for good clustering is made by a specific cluster-validity criterion. This tool has been tested on six data sets. (C) 1999 Elsevier Science B.V. All rights reserved.

引用

页码：123 / 129

页数：7

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