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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributor.authorLlorà Fàbrega, Xavier
dc.contributor.authorGarrell i Guiu, Josep Maria
dc.date.accessioned2021-05-07T06:51:50Z
dc.date.accessioned2023-07-13T09:52:22Z
dc.date.available2021-05-07T06:51:50Z
dc.date.available2023-07-13T09:52:22Z
dc.date.created2001-10
dc.date.issued2001-10
dc.identifier.urihttp://hdl.handle.net/20.500.14342/2914
dc.description.abstractThis paper addresses the issue of the induction of orthogonal, oblique and mul­tivariate decision trees. Algorithms pro­posed by other researchers use heuristic, usually based on the information gain con­cept, to induce decision trees greedily. These algorithms are often tailored for a given tree type ( e.g orthogonal), not be­ing able to induce other types of decision trees. Our work presents an alternative way. We propase to induce a decision trees ( without regarding the type) with an uni­fied algorithm based on artificial evolution. Experiments were performed with GALE, our fine-grained parallel Evolutionary Al­gorithm, and another well-known induc­tion technique on several datasets. Re­sults suggest that Evolutionary Algorithms are competitive and robust for inducing ali kinds of decision trees, achieving sorne­times better performance than traditional approaches.eng
dc.format.extent8 p.cat
dc.language.isoengcat
dc.publisher4rt Congrés Català d'Intel.ligència Artificial, Barcelona, 24-25 d'octubre de 2001cat
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights© ACIA
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceRECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.otherAlgorismes genèticscat
dc.subject.otherAbres (Teoria de grafs)cat
dc.titleEvolution of Decision Treescat
dc.typeinfo:eu-repo/semantics/conferenceObjectcat
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapcat
dc.subject.udc004
dc.subject.udc519.1
dc.subject.udc62


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Attribution-NonCommercial-NoDerivatives 4.0 International
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