Relational partitioning fuzzy clustering algorithms based on multiple dissimilarity matrices

This paper introduces fuzzy clustering algorithms that can partition objects taking into account simultaneously their relational descriptions given by multiple dissimilarity matrices. The aim is to obtain a collaborative role of the different dissimilarity matrices to get a final consensus partition...

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Bibliographic Details
Published in:	Fuzzy sets and systems Vol. 215; pp. 1 - 28
Main Authors:	de Carvalho, Francisco de A.T., Lechevallier, Yves, de Melo, Filipe M.
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 16.03.2013 Elsevier
Subjects:	Algorithms Clusters Collaborative clustering Fuzzy Fuzzy clustering Fuzzy logic Fuzzy medoids Fuzzy set theory Machine Learning Mathematical analysis Matrices Matrix methods Multiple dissimilarity matrices Relational data Relevance weight Statistics Collaborative clustering Fuzzy medoids Fuzzy clustering Relevance weight Relational data Multiple dissimilarity matrices
ISSN:	0165-0114, 1872-6801
Online Access:	Get full text
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