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

Michael J Laszlo; Sumitra Mukherjee

doi:10.1016/j.patrec.2007.08.006

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

Research output: Contribution to journal › Article › peer-review

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.

Original language	American English
Pages (from-to)	2359-2366
Number of pages	8
Journal	Pattern Recognition Letters
Volume	28
Issue number	16
DOIs	https://doi.org/10.1016/j.patrec.2007.08.006
State	Published - Dec 1 2007

ASJC Scopus Subject Areas

Software
Signal Processing
Computer Vision and Pattern Recognition
Artificial Intelligence

Keywords

k-means algorithm
Clustering
Genetic algorithms
Optimal partition
Center selection

Disciplines

Computer Sciences

Access to Document

10.1016/j.patrec.2007.08.006

http://dx.doi.org/10.1016/j.patrec.2007.08.006

Cite this

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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.",

keywords = "k-means algorithm, Clustering, Genetic algorithms, Optimal partition, Center selection",

author = "Laszlo, \{Michael J\} and Sumitra Mukherjee",

year = "2007",

month = dec,

day = "1",

doi = "10.1016/j.patrec.2007.08.006",

language = "American English",

volume = "28",

pages = "2359--2366",

journal = "Pattern Recognition Letters",

publisher = "Elsevier B.V.",

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T1 - A genetic algorithm that exchanges neighboring centers for k-means clustering

AU - Laszlo, Michael J

AU - Mukherjee, Sumitra

PY - 2007/12/1

Y1 - 2007/12/1

N2 - 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.

AB - 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.

KW - k-means algorithm

KW - Clustering

KW - Genetic algorithms

KW - Optimal partition

KW - Center selection

UR - https://nsuworks.nova.edu/gscis_facarticles/5

UR - http://dx.doi.org/10.1016/j.patrec.2007.08.006

U2 - 10.1016/j.patrec.2007.08.006

DO - 10.1016/j.patrec.2007.08.006

M3 - Article

VL - 28

SP - 2359

EP - 2366

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 16

ER -

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

Abstract

ASJC Scopus Subject Areas

Keywords

Disciplines

Access to Document

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