dc.creatorBeausoleil,Ricardo P.
dc.date2020-12-01
dc.date.accessioned2023-09-25T14:23:08Z
dc.date.available2023-09-25T14:23:08Z
dc.identifierhttp://www.scielo.sa.cr/scielo.php?script=sci_arttext&pid=S1409-24332020000200333
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8818814
dc.descriptionAbstract This paper presents an application of Tabu Search algorithm to association rule mining. We focus our attention specifically on classification rule mining, often called associative classification, where the consequent part of each rule is a class label. Our approach is based on seek a rule set handled as an individual. A Tabu search algorithm is used to search for Pareto-optimal rule sets with respect to some evaluation criteria such as accuracy and complexity. We apply a called Apriori algorithm for an association rules mining and then a multiobjective tabu search to a selection rules. We report experimental results where the effect of our multiobjective selection rules is examined for some well-known benchmark data sets from the UCI machine learning repository.
dc.formattext/html
dc.languageen
dc.publisherCentro de Investigaciones en Matemática Pura y Aplicada (CIMPA) y Escuela de Matemática, San José, Costa Rica.
dc.relation10.15517/rmta.v27i2.42438artículo
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceRevista de Matemática Teoría y Aplicaciones v.27 n.2 2020
dc.subjectcombinatorial data analysis
dc.subjectassociative classification
dc.subjecttabu search
dc.subjectmultiobjective optimization.
dc.titleAssociative classification with multiobjective tabu search
dc.typeinfo:eu-repo/semantics/article


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