Dealing with Missing Data using a Selection Algorithm on Rough Sets

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dc.citation.journalTitleINTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
dc.contributor.authorPrieto-Cubides, J
dc.contributor.authorArgoty, C
dc.contributor.departmentUniversidad EAFIT. Departamento de Cienciasspa
dc.contributor.researchgroupLógica y Computaciónspa
dc.creatorPrieto-Cubides, J
dc.creatorArgoty, C
dc.date.accessioned2021-03-26T21:32:05Z
dc.date.available2021-03-26T21:32:05Z
dc.date.issued2018-01-01
dc.description.abstractThis paper discusses the so-called missing data problem, i.e. the problem of imputing missing values in information systems. A new algorithm, called the ARSI algorithm, is proposed to address the imputation problem of missing values on categorical databases using the framework of rough set theory. This algorithm can be seen as a refinement of the ROUSTIDA algorithm and combines the approach of a generalized non-symmetric similarity relation with a generalized discernibility matrix to predict the missing values on incomplete information systems. Computational experiments show that the proposed algorithm is as efficient and competitive as other imputation algorithms.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8509
dc.identifier.doi10.2991/ijcis.11.1.97
dc.identifier.issn18756891
dc.identifier.issn18756883
dc.identifier.otherWOS;000454694400031
dc.identifier.otherSCOPUS;2-s2.0-85062682581
dc.identifier.urihttp://hdl.handle.net/10784/27351
dc.languageeng
dc.publisherATLANTIS PRESS
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85062682581&doi=10.2991%2fijcis.11.1.97&partnerID=40&md5=3762923d6cfc2da783855fd77fe9d704
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/1875-6891
dc.sourceINTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
dc.subjectCategoricaleng
dc.subjectImputationeng
dc.subjectMissing Valueseng
dc.subjectRough Setseng
dc.titleDealing with Missing Data using a Selection Algorithm on Rough Setseng
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localArtículospa

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