A genetic algorithm that exchanges neighboring centers for k-means clustering

被引：118

作者：

Laszlo, Michael ^{[1
]}

Mukherjee, Sumitra ^{[1
]}

机构：

[1] Nova SE Univ, Grad Sch Comp & Informat Sci, Ft Lauderdale, FL 33314 USA

来源：

PATTERN RECOGNITION LETTERS | 2007年 / 28卷 / 16期

关键词：

k-means algorithm; clustering; genetic algorithms; optimal partition; center selection;

D O I：

10.1016/j.patrec.2007.08.006

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a genetic algorithm for selecting centers to seed the popular k-means method for clustering. Using a novel crossover operator that exchanges neighboring centers, our GA identifies superior partitions using both benchmark and large simulated data sets. (c) 2007 Elsevier B.V. All rights reserved.

引用

页码：2359 / 2366

页数：8

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