RT Journal Article T1 Map-elites algorithm for features selection problem A1 Quiñonez, Brenda A1 Pinto Roa, Diego Pedro A1 García Torres, Miguel A1 García-Diaz, María E. A1 Núñez Castillo, Carlos Heriberto A1 Divina, Federico A2 Universidad Nacional de Asunción - Facultad Politécnica AB In the High-dimensional data analysis there are several challenges in the fields of machine learning and data mining. Typically, feature selection is considered as a combinatorial optimization problem which seeks to remove irrelevant and redundant data by reducing computation time and improve learning measures. Given the complexity of this problem, we propose a novel Map-Elites based Algorithm that determines the minimum set of features maximizing learning accuracy simultaneously. Experimental results, on several data based from real scenarios, show the effectiveness of the proposed algorithm. YR 2019 FD 2019 LK http://hdl.handle.net/20.500.14066/3734 UL http://hdl.handle.net/20.500.14066/3734 LA eng NO CONACYT – Consejo Nacional de Ciencia y Tecnología DS MINDS@UW RD 16-jun-2024