Towards a fast evolutionary algorithm for clustering

Vinícius S. Alves, Ricardo J.G.B. Campello, Eduardo R. Hruschka*

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

Abstract

This paper elaborates on the improvement of an evolutionary algorithm for clustering (EAC) introduced in previous work. Four new features are proposed and empirically assessed in seven datasets, using two fitness functions. Statistical analyses allow concluding that two proposed features lead to significant improvements on the original EAC. Such features have been incorporated into the EAC, resulting in a more computationally efficient algorithm called F-EAC (Fast EAC). We describe as an additional contribution a methodology for evaluating evolutionary algorithms for clustering in such a way that the influence of the fitness function is lessened in the assessment process, what yields analyses specially focused on the evolutionary operators.

OriginalsprogEngelsk
Titel2006 IEEE Congress on Evolutionary Computation, CEC 2006
ForlagIEEE
Publikationsdato2006
Sider1776-1783
Artikelnummer1688522
ISBN (Trykt)0780394879, 9780780394872
DOI
StatusUdgivet - 2006
Udgivet eksterntJa
Begivenhed2006 IEEE Congress on Evolutionary Computation, CEC 2006 - Vancouver, BC, Canada
Varighed: 16. jul. 200621. jul. 2006

Konference

Konference2006 IEEE Congress on Evolutionary Computation, CEC 2006
Land/OmrådeCanada
ByVancouver, BC
Periode16/07/200621/07/2006
NavnIEEE Transactions on Evolutionary Computation
ISSN1089-778X

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