Gowda , K Chidananda and Krishnan, Girish (1978) Agglomerative clustering using the concept of mutual nearest neighbourhood. In: Pattern Recognition, 10 (2). 105-112 .Full text not available from this repository.
A method for determining the mutual nearest neighbours (MNN) and mutual neighbourhood value (mnv) of a sample point, using the conventional nearest neighbours, is suggested. A nonparametric, hierarchical, agglomerative clustering algorithm is developed using the above concepts. The algorithm is simple, deterministic, noniterative, requires low storage and is able to discern spherical and nonspherical clusters. The method is applicable to a wide class of data of arbitrary shape, large size and high dimensionality. The algorithm can discern mutually homogenous clusters. Strong or weak patterns can be discerned by properly choosing the neighbourhood width.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Elsevier Science.|
|Keywords:||Nonparametric; Agglomerative; Clustering; Mutual nearest neighbour; Mutual neighbourhood value; Mutually homogeneous; Pattern recognition.|
|Department/Centre:||Division of Electrical Sciences > Electrical Engineering|
|Date Deposited:||11 Oct 2010 06:01|
|Last Modified:||11 Oct 2010 06:01|
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