Leaders-Subleaders: An efficient hierarchical clustering algorithm for large data sets

Vijaya, PA and Murty, Narasimha M and Subramanian, DK (2004) Leaders-Subleaders: An efficient hierarchical clustering algorithm for large data sets. In: Pattern Recognition Letters, 25 (4). pp. 505-513.

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Abstract

In this paper, an efficient hierarchical clustering algorithm, suitable for large data sets is proposed for effective clustering and prototype selection for pattern classification. It is another simple and efficient technique which uses incremental clustering principles to generate a hierarchical structure for finding the subgroups/subclusters within each cluster. As an example, a two level clustering algorithm-`Leaders-Subleaders', an extension of the leader algorithm is presented. Classification accuracy (CA) obtained using the representatives generated by the Leaders-Subleaders method is found to be better than that of using leaders as representatives. Even if more number of prototypes are generated, classification time is less as only a part of the hierarchical structure is searched

Item Type:	Journal Article
Publication:	Pattern Recognition Letters
Publisher:	Elsevier
Additional Information:	Copyright for this article belongs to Elsevier.
Keywords:	Incremental clustering;Leaders and subleaders;Hierarchical structure; Subgroups/subclusters;Prototypes/representatives
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	25 Nov 2005
Last Modified:	19 Sep 2010 04:21
URI:	http://eprints.iisc.ac.in/id/eprint/4164

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