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

被引：115
|
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
收藏
页码：2359 / 2366
页数：8
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