A clustering algorithm using an evolutionary programming-based approach

被引：84

作者：

Sarkar, M ^{[1
]}

Yegnanarayana, B ^{[1
]}

Khemani, D ^{[1
]}

机构：

[1] Indian Inst Technol, Dept Comp Sci & Engn, Madras 600036, Tamil Nadu, India

来源：

PATTERN RECOGNITION LETTERS | 1997年 / 18卷 / 10期

关键词：

clustering; K-means; optimization; evolutionary programming;

D O I：

10.1016/S0167-8655(97)00122-0

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, an evolutionary programming-based clustering algorithm is proposed. The algorithm effectively groups a given set of data into an optimum number of clusters. The proposed method is applicable for clustering tasks where clusters are crisp and spherical. This algorithm determines the number of clusters and the cluster centers in such a way that locally optimal solutions are avoided. The result of the algorithm does not depend critically on the choice of the initial cluster centers. (C) 1997 Published by Elsevier Science B.V.

引用

页码：975 / 986

页数：12

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