An evolutionary algorithm with acceleration operator to generate a subset of typical testors

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dc.contributor.authorSánchez-Díaz, Guillermo
dc.contributor.authorDíaz-Sánchez, Germán
dc.contributor.authorMora-González, Miguel
dc.contributor.authorAguirre-Salado, Carlos A.
dc.contributor.authorHuerta-Cuéllar, Guillermo
dc.contributor.authorPiza-Dávila, Hugo I.
dc.contributor.authorReyes-Cárdenas, Óscar
dc.contributor.authorCárdenas-Tristán, Abraham
dc.date.accessioned2014-03-14T18:13:16Z
dc.date.available2014-03-14T18:13:16Z
dc.date.issued2014-05-01
dc.descriptionThis paper is focused on introducing a Hill-Climbing algorithm as a way to solve the problem of generating typical testors – or non-reducible descriptors – from a training matrix. All the algorithms reported in the state-of-the-art have exponential complexity. However, there are problems for which there is no need to generate the whole set of typical testors, but it suffices to find only a subset of them. For this reason, we introduce a Hill-Climbing algorithm that incorporates an acceleration operation at the mutation step, providing a more efficient exploration of the search space. The experiments have shown that, under the same circumstances, the proposed algorithm performs better than other related algorithms reported so far.es
dc.description.sponsorshipITESO, A.C.es
dc.identifier.citationSanchez-Diaz, G.; Diaz-Sanchez, G.; Mora-Gonzalez, M; Piza-Davila, H.I.; Aguirre-Salado, C.A.; Huerta-Cuellar, G; Reyes-Cardenas, O.; Cardenas-Tristan, A. (2014). "An evolutionary algorithm with acceleration operator to generate a subset of typical testors". Pattern Recognition Letters. Volume 41, 1 May, pp.34-42.es
dc.identifier.issn0167-8655
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0167865513004297
dc.identifier.urihttp://hdl.handle.net/11117/1217
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofseriesPattern Recognition Letters;41
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdfes
dc.subjectHill Climberses
dc.subjectFeature Selectiones
dc.subjectTypical Testorses
dc.subjectPattern Recognitiones
dc.titleAn evolutionary algorithm with acceleration operator to generate a subset of typical testorses
dc.typeinfo:eu-repo/semantics/articlees
rei.peerreviewedYeses
rei.revisorPattern Recognition Letters

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