Automatic Design of Decision-Tree Algorithms with Evolutionary Algorithms

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dc.contributor.authorBarros, Rodrigo C.
dc.contributor.authorBasgalupp, Marcio P. [UNIFESP]
dc.contributor.authorCarvalho, Andre C. P. L. F. de
dc.contributor.authorFreitas, Alex A.
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Federal de São Paulo (UNIFESP)
dc.contributor.institutionUniv Kent
dc.date.accessioned2016-01-24T14:34:42Z
dc.date.available2016-01-24T14:34:42Z
dc.date.issued2013-11-01
dc.description.abstractThis study reports the empirical analysis of a hyper-heuristic evolutionary algorithm that is capable of automatically designing top-down decision-tree induction algorithms. Top-down decision-tree algorithms are of great importance, considering their ability to provide an intuitive and accurate knowledge representation for classification problems. the automatic design of these algorithms seems timely, given the large literature accumulated over more than 40 years of research in the manual design of decision-tree induction algorithms. the proposed hyper-heuristic evolutionary algorithm, HEAD-DT, is extensively tested using 20 public UCI datasets and 10 microarray gene expression datasets. the algorithms automatically designed by HEAD-DT are compared with traditional decision-tree induction algorithms, such as C4.5 and CART. Experimental results show that HEAD-DT is capable of generating algorithms which are significantly more accurate than C4.5 and CART.en
dc.description.affiliationUniv São Paulo, Sao Carlos, SP, Brazil
dc.description.affiliationUniversidade Federal de São Paulo, Sao Jose Dos Campos, Brazil
dc.description.affiliationUniv Kent, Canterbury, Kent, England
dc.description.affiliationUnifespUniversidade Federal de São Paulo, ICT, Sao Jose Dos Campos, Brazil
dc.description.sourceWeb of Science
dc.format.extent659-684
dc.identifierhttp://dx.doi.org/10.1162/EVCO_a_00101
dc.identifier.citationEvolutionary Computation. Cambridge: Mit Press, v. 21, n. 4, p. 659-684, 2013.
dc.identifier.doi10.1162/EVCO_a_00101
dc.identifier.issn1063-6560
dc.identifier.urihttp://repositorio.unifesp.br/handle/11600/36964
dc.identifier.wosWOS:000326579700005
dc.language.isoeng
dc.publisherMit Press
dc.relation.ispartofEvolutionary Computation
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectDecision treesen
dc.subjecthyper-heuristicsen
dc.subjectautomatic algorithm designen
dc.subjectsupervised machine learningen
dc.subjectdata miningen
dc.titleAutomatic Design of Decision-Tree Algorithms with Evolutionary Algorithmsen
dc.typeinfo:eu-repo/semantics/article
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