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Ensemble method based on individual evolving classifiers

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Control, Aprendizaje y Optimización de Sistemas (CAOS)es
dc.contributor.authorIglesias Martínez, José Antonio
dc.contributor.authorLedezma Espino, Agapito Ismael
dc.contributor.authorSanchis de Miguel, María Araceli
dc.date.accessioned2016-09-22T10:48:35Z
dc.date.available2016-09-22T10:48:35Z
dc.date.issued2013
dc.description.abstractAbstract: Humans often seek a second or third opinion about an important matter. Then, a final decision is reached after weighing and combining these opinions. This idea is the base of the ensemble based systems. Ensembles of classifiers are well established as a method for obtaining highly accurate classifiers by combining less accurate ones. On the other hand, evolving classifiers are inspired by the idea of evolve their structure in order to adapt to the changes of the environment. In this paper, we present a proof-of-concept method for constructing an ensemble system based on Evolving Fuzzy Systems. The main contribution of this approach is that the base-classifiers are self-developing (evolving) Fuzzy-rule-based (FRB) classifiers. Thus, we present an ensemble system which is based on evolving classifiers and keeps the properties of the evolving approach classification of streaming data. It is important to clarify that the evolving classifiers are gradually developing but they are not genetic or evolutionary.en
dc.description.sponsorshipThis work has been supported by the Spanish Government under i-Support (Intelligent Agent Based Driver Decision Support) Project (TRA2011-29454-C03-03).en
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationEvolving and Adaptive Intelligent Systems (EAIS), 2013 IEEE Conference on. : Ieee Computer Society. Pp. 56-61en
dc.identifier.isbn978-1-4673-5855-2
dc.identifier.publicationfirstpage56
dc.identifier.publicationlastpage61
dc.identifier.publicationtitleEvolving and Adaptive Intelligent Systems (EAIS), 2013 IEEE Conference onen
dc.identifier.urihttps://hdl.handle.net/10016/23613
dc.identifier.uxxiCC/0000023044
dc.language.isoeng
dc.publisherIEEE Computer Societyen
dc.relation.eventdate16-19 April 2013en
dc.relation.eventplaceSingapore
dc.relation.eventtitle2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)en
dc.relation.projectIDGobierno de España. TRA2011-29454-C03-03es
dc.relation.projectIDGobierno de España. TRA2013-48314-C3-1-Res
dc.relation.publisherversionhttp://dx.doi.org/10.1109/EAIS.2013.6604105
dc.rights© 2013 IEEE
dc.rights.accessRightsopen access
dc.subject.ecienciaInformáticaes
dc.subject.otherBaggingen
dc.subject.otherTrainingen
dc.subject.otherBoostingen
dc.subject.otherTraining dataen
dc.subject.otherConferencesen
dc.subject.otherAdaptive systemsen
dc.subject.otherIntelligent systemsen
dc.titleEnsemble method based on individual evolving classifiers
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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