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 03-nov-2024