Distributed fuzzy clustering with automatic detection of the number of clusters

L. Vendramin*, R. J.G.B. Campello, L. F.S. Coletta, E. R. Hruschka

*Kontaktforfatter

Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Abstract

We present a consensus-based algorithm to distributed fuzzy clustering that allows automatic estimation of the number of clusters. Also, a variant of the parallel Fuzzy c-Means algorithm that is capable of estimating the number of clusters is introduced. This variant, named DFCM, is applied for clustering data distributed across different data sites. DFCM makes use of a new, distributed version of the Xie-Beni validity criterion. Illustrative experiments show that for sites having data from different populations the developed consensus-based algorithm can provide better results than DFCM.

OriginalsprogEngelsk
TitelInternational Symposium on Distributed Computing and Artificial Intelligence
RedaktørerAjith Abraham, Juan M. Corchado Rodriguez, Sara Rodriguez Gonzalez, Juan Paz Santana
UdgivelsesstedBerlin
ForlagSpringer
Publikationsdato2011
Sider133-140
ISBN (Trykt)9783642199332
DOI
StatusUdgivet - 2011
Udgivet eksterntJa
NavnAdvances in Intelligent and Soft Computing
Vol/bind91
ISSN1867-5662

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