The synergistic combination of particle swarm optimization and fuzzy sets to design granular classifier

•This paper proposes a granular classifier to discover hyperboxes in three phases.•The first phase of the proposed model uses the set calculus to build the hyperboxes.•The second phase develops the geometry of hyperboxes using PSO algorithm.•The PSO is used to optimize the classification rate and ex...

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Bibliographic Details
Published in:	Knowledge-based systems Vol. 76; pp. 200 - 218
Main Authors:	Salehi, Saber, Selamat, Ali, Reza Mashinchi, M., Fujita, Hamido
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.03.2015
Subjects:	Algorithms Bundling Classifiers Construction DBSCAN clustering algorithm Fuzzy Fuzzy set theory Granular classifier Hyperbox geometry of classifiers Knowledge base Mathematical analysis Membership functions Particle swarm optimization Swarm intelligence Hyperbox geometry of classifiers Membership functions Granular classifier Particle swarm optimization DBSCAN clustering algorithm
ISSN:	0950-7051, 1872-7409
Online Access:	Get full text
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