A novel multi population based particle swarm optimization for feature selection

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dc.authoridKilic, Fatih/0000-0002-8550-1562
dc.contributor.authorKılıç, Fatih
dc.contributor.authorKaya, Yasin
dc.contributor.authorYildirim, Serdar
dc.date.accessioned2025-01-06T17:43:52Z
dc.date.available2025-01-06T17:43:52Z
dc.date.issued2021
dc.description.abstractFeature selection is an integral part of any machine learning system and the success of such systems highly depends on the relevance of features with the target domain. Feature selection can be classified as NP-Hard problem since a large number of possible solutions exists especially when the feature space is high dimensional. In addition to standard feature selection algorithms, evolutionary algorithms have also yielded promising results. In this paper, a novel multi population based particle swarm optimization (MPPSO) is proposed for feature selection. In this method, multi population start with initial solutions generated by random and Relieff based initialization and searches solution space simultaneously using both populations. 26 UCI and 3 ASU datasets are used to evaluate the performance of the method. The results show that MPPSO generally achieves better average classification accuracies than the other algorithms. Specifically, for the datasets with a large number of features, MPPSO achieves the smallest number of selected features with highest classification accuracies compared to other algorithms. (c) 2021 Elsevier B.V. All rights reserved.
dc.identifier.doi10.1016/j.knosys.2021.106894
dc.identifier.issn0950-7051
dc.identifier.issn1872-7409
dc.identifier.scopus2-s2.0-85102040315
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.knosys.2021.106894
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2846
dc.identifier.volume219
dc.identifier.wosWOS:000634868700013
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofKnowledge-Based Systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectParticle swarm optimization
dc.subjectMulti-population initialization
dc.subjectMeta-heuristics
dc.subjectTransfer functions
dc.titleA novel multi population based particle swarm optimization for feature selection
dc.typeArticle

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