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dc.date.accessioned 2012-10-18T18:00:59Z
dc.date.available 2012-10-18T18:00:59Z
dc.date.issued 2006-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/22626
dc.description.abstract This article proposes a method for achieving an appropriate balance between the parameters of support, precision, and simplicity during the evolution of classification rules by means of genetic programming. The method includes an adaptive procedure in order to achieve such balance. This work lies within the data mining context, more precisely, it focuses on the extraction of comprehensible knowledge where the approach introduced plays a predominant role. Experimental results demonstrate the advantages of using the proposed method en
dc.format.extent 1175-1184 es
dc.language en es
dc.subject Data mining es
dc.subject classification rules en
dc.subject ranking en
dc.subject genetic programming en
dc.subject comprehensible knowledge en
dc.title Achieving an appropriate balance between precision, support, and comprehensibility in the evolution of classification rules en
dc.type Objeto de conferencia es
sedici.creator.person Carreño, Emiliano es
sedici.creator.person Leguizamón, Guillermo es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2006-10
sedici.relation.event XII Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)