Pruning Optimum-Path Forest Ensembles Using Quaternion-based Optimization

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dc.contributor.authorNachif Fernandes, Silas Evandro
dc.contributor.authorPapa, Joao Paulo [UNESP]
dc.contributor.authorIEEE
dc.contributor.institutionUniversidade Federal de São Carlos (UFSCar)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-11-26T17:48:36Z
dc.date.available2018-11-26T17:48:36Z
dc.date.issued2017-01-01
dc.description.abstractMachine learning techniques have been actively pursued in the last years, mainly due to the great number of applications that make use of some sort of intelligent mechanism for decision-making processes. In this context, we shall highlight pruning strategies, which provide heuristics to select from a collection of classifiers the ones that can really improve recognition rates when working together. In this paper, we present an ensemble pruning approach of Optimum-Path Forest classifiers based on metaheuristics, as well as we introduced the concept of quaternions in ensemble pruning strategies. Experimental results over synthetic and real datasets showed the effectiveness and efficiency of the proposed approach for classification problems.en
dc.description.affiliationUniv Fed Sao Carlos, Dept Comp, Rod Washington Luis,Km 235, BR-13565905 Sao Carlos, SP, Brazil
dc.description.affiliationSao Paulo State Univ, Dept Comp, Av Eng Luiz Edmundo Carrijo Coube 14-01, BR-17033360 Bauru, SP, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Dept Comp, Av Eng Luiz Edmundo Carrijo Coube 14-01, BR-17033360 Bauru, SP, Brazil
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipIdFAPESP: 2014/16250-9
dc.description.sponsorshipIdFAPESP: 2014/12236-1
dc.description.sponsorshipIdCNPq: 306166/2014-3
dc.format.extent984-991
dc.identifier.citation2017 International Joint Conference On Neural Networks (ijcnn). New York: Ieee, p. 984-991, 2017.
dc.identifier.fileWOS000426968701033.pdf
dc.identifier.issn2161-4393
dc.identifier.urihttp://hdl.handle.net/11449/163968
dc.identifier.wosWOS:000426968701033
dc.language.isoeng
dc.publisherIeee
dc.relation.ispartof2017 International Joint Conference On Neural Networks (ijcnn)
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.titlePruning Optimum-Path Forest Ensembles Using Quaternion-based Optimizationen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIeee
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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