A comparative study between feature selection algorithms

dc.contributor.authorMedina Garcia, Víctor Hugo
dc.contributor.authorRodriguez Rodriguez, Jorge
dc.contributor.authorOspina Usaquén, Miguel Angel
dc.date.accessioned2019-07-08T13:56:28Z
dc.date.available2019-07-08T13:56:28Z
dc.date.issued2018-06-10
dc.description.abstractIn this paper, we show a comparative study between four algorithms used in features selection; these are: decision trees, entropy measure for ranking features, estimation of distribution algorithms, and the bootstrapping algorithm. Likewise, the features selection is highlighted as the most representative task in the elimination of noise, in order to improve the quality of the dataset. Subsequently, each algorithm is described in order that the reader understands its function. Then the algorithms are applied using different data sets and obtaining the results in the selection. Finally, the conclusions of this investigation are presented.spa
dc.description.domainhttp://unidadinvestigacion.usta.edu.cospa
dc.format.mimetypeapplication/pdf
dc.identifier.citationMedina Garcia, V. H., Rodriguez Rodriguez, J., & Ospina Usaquén, M. A. (2018). A comparative study between feature selection algorithms. Bogotá: doi:10.1007/978-3-319-93803-5_7spa
dc.identifier.doihttps://doi.org/10.1007/978-3-319-93803-5_7spa
dc.identifier.urihttp://hdl.handle.net/11634/17502
dc.publisher.branchCRAI-USTA Bogotáspa
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dc.rightsAtribución-NoComercial-CompartirIgual 2.5 Colombia
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/2.5/co/
dc.subject.keywordFeatures selectionspa
dc.subject.keywordBootstrapping algorithmspa
dc.subject.keywordDecision treesspa
dc.subject.keywordEntropy theoryspa
dc.subject.keywordEstimation of distribution algorithmsspa
dc.titleA comparative study between feature selection algorithmsspa
dc.type.categoryGeneración de Nuevo Conocimiento: Artículos publicados en revistas especializadas - Electrónicosspa

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