ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

A near-optimal initial seed value selection in K-means means algorithm using a genetic algorithm

Babu, Phanendra G and Murty, Narasimha M (1993) A near-optimal initial seed value selection in K-means means algorithm using a genetic algorithm. In: Pattern Recognition Letters, 14 (10). pp. 763-769.

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/0167-8655(93)90058-L

Abstract

The K-means algorithm for clustering is very much dependent on the initial seed values. We use a genetic algorithm to find a near-optimal partitioning of the given data set by selecting proper initial seed values in the K-means algorithm. Results obtained are very encouraging and in most of the cases, on data sets having well separated clusters, the proposed scheme reached a global minimum.

Item Type: Journal Article
Additional Information: Copyright of this article belongs to Elsevier Science.
Keywords: Clustering;seed values;optimal partition;genetic algorithms; K-means algorithm.
Department/Centre: Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)
Date Deposited: 31 Jan 2011 11:50
Last Modified: 31 Jan 2011 11:50
URI: http://eprints.iisc.ernet.in/id/eprint/35287

Actions (login required)

View Item View Item