This Title All WIREs
How to cite this WIREs title:
WIREs Data Mining Knowl Discov
Impact Factor: 7.250

Genetic algorithms for clustering and fuzzy clustering

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract Clustering has been an area of intensive research for several decades because of its multifaceted applications in innumerable domains. Clustering can be either Boolean, where a single data point belongs to exactly one cluster, or fuzzy, where a single data point can have nonzero belongingness to more than one cluster. Traditionally, optimization of some well‐defined objective function has been the standard approach in both clustering and fuzzy clustering. Hence, researchers have investigated the utility of evolutionary computing and related techniques in this regard. The different approaches differ in their choice of the objective function and/or the optimization strategy used. In particular, clustering using genetic algorithms (GAs) has attracted attention of researchers, and has been studied extensively. This paper presents a short review of some of different approaches of GA‐based clustering methods. Two techniques, one with fixed number of clusters and another with a variable number of fuzzy clusters, are described along with some experimental results on numerical as well as image data sets. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 524–531 DOI: 10.1002/widm.47 This article is categorized under: Algorithmic Development > Structure Discovery Technologies > Structure Discovery and Clustering

Clustered image of Calcutta using (a) FVGA‐clustering (b) FCM clustering.24

[ Normal View | Magnified View ]

Related Articles

Genetic algorithms for clustering and fuzzy clustering

Browse by Topic

Technologies > Structure Discovery and Clustering
Algorithmic Development > Structure Discovery

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts