Fuzzy prototype selection-based classifiers for imbalanced data. Case study

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dc.contributor.authorYanela Rodríguez Álvarez
dc.contributor.authorMaría Matilde García Lorenzo
dc.contributor.authorYailé Caballero Mota
dc.contributor.authorYaima Filiberto
dc.contributor.authorIsabel M. García Hilarión
dc.contributor.authorDaniela Machado Montes de
dc.contributor.authorRafael Bello
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T15:11:04Z
dc.date.available2026-03-22T15:11:04Z
dc.date.issued2022
dc.descriptionCitaciones: 5
dc.identifier.doi10.1016/j.patrec.2022.07.003
dc.identifier.urihttps://doi.org/10.1016/j.patrec.2022.07.003
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/50873
dc.language.isoen
dc.publisherElsevier BV
dc.relation.ispartofPattern Recognition Letters
dc.sourceUniversity of Camagüey
dc.subjectArtificial intelligence
dc.subjectFuzzy logic
dc.subjectComputer science
dc.subjectMachine learning
dc.subjectSelection (genetic algorithm)
dc.subjectSimilarity (geometry)
dc.subjectData mining
dc.subjectClass (philosophy)
dc.titleFuzzy prototype selection-based classifiers for imbalanced data. Case study
dc.typearticle

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