research article
Map-elites algorithm for features selection problem
Autor
Quiñonez, Brenda
Pinto Roa, Diego Pedro
García Torres, Miguel
García-Diaz, María E.
Núñez Castillo, Carlos Heriberto
Divina, Federico
Resumen
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. CONACYT – Consejo Nacional de Ciencia y Tecnología PROCIENCIA