Paper Info
Title
A genetic algorithm that exchanges neighboring centers for k-means clustering
Abstract
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.
Year
DOI
Venue
2007
10.1016/j.patrec.2007.08.006
Pattern Recognition Letters
Keywords
DocType
Volume
optimal partition,genetic algorithms,genetic algorithm,center selection,k -means algorithm,superior partition,popular k-means method,k-means clustering,k-means algorithm,large simulated data set,clustering,novel crossover operator,k means clustering,k means,k means algorithm
Journal
28
Issue
ISSN
Citations 
16
Pattern Recognition Letters
46
PageRank 
References 
Authors
2.15
16
2
Name
Order
Citations
PageRank
Michael Laszlo121410.76
Sumitra Mukherjee231131.75