Medina Garcia, Víctor HugoRodriguez Rodriguez, JorgeOspina Usaquén, Miguel Angel2019-07-082019-07-082018-06-10Medina 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_7http://hdl.handle.net/11634/17502In 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.application/pdfAtribución-NoComercial-CompartirIgual 2.5 Colombiahttp://creativecommons.org/licenses/by-nc-sa/2.5/co/Features selectionBootstrapping algorithmDecision treesEntropy theoryEstimation of distribution algorithmshttps://doi.org/10.1007/978-3-319-93803-5_7Generación de Nuevo Conocimiento: Artículos publicados en revistas especializadas - Electrónicos