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International Journal of

Recent Trends in Engineering

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International Journal of Recent Trends in Engineering (IJRTE)

ISSN 1797-9617

Volume 1,† Number 1,† May 2009

Issue on Computer Science

Page(s): 269-273

Comparison of SGA and RGA based Clustering Algorithm for Pattern Recognition

†††††††††† Kumar Dhiraj, Santanu Kumar Rath

Full text:† PDF

Abstract

In this paper Genetic Algorithm based clustering Algorithm has been studied for pattern recognition. The searching capability of genetic algorithms is exploited in order to search for appropriate/optimal cluster as well as clusterís center in the feature space such that inter-cluster distance (Homogeneity) and intra-cluster distances (Separation) are optimized. We use H-S ratio for computation of fitness function. We use Andersonís IRIS data to illustrate our method. We have implemented six clustering algorithm (k-means, Hierarchical, GLVQ, SOM, FCM and GA-based clustering algorithm) and compare clustering accuracy using IRIS data.

Index Terms

K-means, Hierarchical clustering, GLVQ, SOM, FCM, GA, Homogeneity and Separation, Iris

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