Disaggregative Clustering Using the Concept of Mutual Nearest Neighborhood

Gowda, KC and Krishna, G (1978) Disaggregative Clustering Using the Concept of Mutual Nearest Neighborhood. In: IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 8 (12). 888-895 .

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Abstract

A nonparametric, hierarchical, disaggregative clustering algorithm is developed using a novel similarity measure, called the mutual neighborhood value (MNV), which takes into account the conventional nearest neighbor ranks of two samples with respect to each other. The algorithm is simple, noniterative, requires low storage, and needs no specification of the expected number of clusters. The algorithm appears very versatile as it is capable of discerning spherical and nonspherical clusters, linearly nonseparable clusters, clusters with unequal populations, and clusters with lowdensity bridges. Changing of the neighborhood size enables discernment of strong or weak patterns.

Item Type:	Journal Article
Publication:	IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans
Publisher:	IEEE
Additional Information:	Copyright 1978 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	08 Oct 2010 11:00
Last Modified:	08 Oct 2010 11:01
URI:	http://eprints.iisc.ac.in/id/eprint/33103

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