Fuzzy measures in determining seed points in clustering

Pal, S. K. ; Pramanik, P. K. (1986) Fuzzy measures in determining seed points in clustering Pattern Recognition Letters, 4 (3). pp. 159-164. ISSN 0167-8655

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Official URL: http://linkinghub.elsevier.com/retrieve/pii/016786...

Related URL: http://dx.doi.org/10.1016/0167-8655(86)90014-0


Algorithms for automatic selection of seed points for clustering are described using the terms 'index of fuzziness', 'entropy', and 'π-ness' of a fuzy set. Two membership functions R in have been defined such that the fuzzy measures posses maximum values when the crossover points/central points of the membership functions correspond to the points around which the data has a tendency to cluster. The effectiveness of the algorithm is demonstrated on a set of speech data.

Item Type:Article
Source:Copyright of this article belongs to International Association for Pattern Recognition.
Keywords:Clustering; Fuzzy Measures
ID Code:26100
Deposited On:06 Dec 2010 13:06
Last Modified:13 Jun 2011 06:12

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