Partitional fuzzy clustering methods based on adaptive quadratic distances

Abstract

This paper presents partitional fuzzy clustering methods based on adaptive quadratic distances. The methods presented furnish a fuzzy partition and a prototype for each cluster by optimizing an adequacy criterion based on adaptive quadratic distances. These distances change at each algorithm iteration and can either be the same for all clusters or different… (More)
DOI: 10.1016/j.fss.2006.06.004

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Cite this paper

@article{Carvalho2006PartitionalFC, title={Partitional fuzzy clustering methods based on adaptive quadratic distances}, author={Francisco de A. T. de Carvalho and Camilo P. Tenorio and Nicomedes L. Cavalcanti Junior}, journal={Fuzzy Sets and Systems}, year={2006}, volume={157}, pages={2833-2857} }