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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/73832
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dc.contributor.authorNakamura, R. Y M-
dc.contributor.authorPereira, L. A M-
dc.contributor.authorCosta, K. A.-
dc.contributor.authorRodrigues, D.-
dc.contributor.authorPapa, João Paulo-
dc.contributor.authorYang, X. S.-
dc.date.accessioned2014-05-27T11:27:18Z-
dc.date.accessioned2016-10-25T18:40:04Z-
dc.date.available2014-05-27T11:27:18Z-
dc.date.available2016-10-25T18:40:04Z-
dc.date.issued2012-12-01-
dc.identifierhttp://dx.doi.org/10.1109/SIBGRAPI.2012.47-
dc.identifier.citationBrazilian Symposium of Computer Graphic and Image Processing, p. 291-297.-
dc.identifier.issn1530-1834-
dc.identifier.urihttp://hdl.handle.net/11449/73832-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/73832-
dc.description.abstractFeature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be in-viable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the bats behaviour, which has never been applied to this context so far. The wrapper approach combines the power of exploration of the bats together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in five public datasets have demonstrated that the proposed approach can outperform some well-known swarm-based techniques. © 2012 IEEE.en
dc.format.extent291-297-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectbat algorithm-
dc.subjectfeature selection-
dc.subjectoptimum-path forest-
dc.subjectData sets-
dc.subjectExhaustive search-
dc.subjectOptimization problems-
dc.subjectOptimum-path forests-
dc.subjectSelection techniques-
dc.subjectWrapper approach-
dc.subjectFeature extraction-
dc.subjectForestry-
dc.subjectAlgorithms-
dc.subjectAutomatic Control-
dc.subjectOptimization-
dc.subjectProblem Solving-
dc.subjectTechniques-
dc.titleBBA: A binary bat algorithm for feature selectionen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionNational Physical Laboratory-
dc.description.affiliationDepartment of Computing São Paulo State University, Bauru-
dc.description.affiliationNational Physical Laboratory, London-
dc.description.affiliationUnespDepartment of Computing São Paulo State University, Bauru-
dc.identifier.doi10.1109/SIBGRAPI.2012.47-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofBrazilian Symposium of Computer Graphic and Image Processing-
dc.identifier.scopus2-s2.0-84872367831-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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