In search of optimal clusters using genetic algorithms

被引：220
|
作者：
Murthy, CA [1 ]
Chowdhury, N [1 ]
机构：
[1] RAMAKRISHNA MISSION SHILPAPITHA,CALCUTTA,W BENGAL,INDIA
来源：
PATTERN RECOGNITION LETTERS | 1996年 / 17卷 / 08期
关键词：
pattern recognition; clustering; K-means; genetic algorithms;
D O I：
10.1016/0167-8655(96)00043-8
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Genetic Algorithms (GAs) are generally portrayed as search procedures which can optimize functions based on a limited sample of function values. In this paper, GAs have been used in an attempt to optimize a specified objective function related to a clustering problem. Several experiments on synthetic and real life data sets show the utility of the proposed method. K-Means is one of the most popular methods adopted to solve the clustering problem. Analysis of the experimental results shows that the proposed method may improve the final output of K-Means where an improvement is possible.
引用
收藏
页码：825 / 832
页数：8
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