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dc.contributor.authorNúñez Esquer, Gustavo
dc.contributor.authorCortés García, Claudio Ulises
dc.contributor.authorBelanche Muñoz, Luis Antonio
dc.contributor.authorAlvarado Mentado, Matías
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2020-09-30T09:33:34Z
dc.date.available2020-09-30T09:33:34Z
dc.date.issued1991-03
dc.identifier.citationNuñez, G.; Cortés, U.; Belanche, L. About the attribute relevance's nature. 1991.
dc.identifier.urihttp://hdl.handle.net/2117/329527
dc.description.abstractThe notion of relevance of an attribute in machine learning is of common use in the construction of classfication rules in inductive learning processes. In this work a formal definition of the relevance concept for a given set of attributes is proposed, which includes the special case of non-relevant attributes or nought attributes. We establish the theoretical conditions that must satisfy the heuristics used to select the potentially more useful attribute to a classification, showing that some of the problems some classical heuristics based upon the information theory present, are actually due to the fact that they do not fulfill those conditions. We propose an heuristic that does satisfy them, and not enhance attributes with a lot of values more accurate than the rest.
dc.format.extent23 p.
dc.language.isoeng
dc.relation.ispartofseriesLSI-91-6
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshMachine learning
dc.titleAbout the attribute relevance's nature
dc.typeExternal research report
dc.subject.lemacAprenentatge automàtic
dc.contributor.groupUniversitat Politècnica de Catalunya. SOCO - Soft Computing
dc.rights.accessOpen Access
local.identifier.drac29469291
dc.description.versionPostprint (published version)
local.citation.authorNuñez, G.; Cortés, U.; Belanche, Ll.


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