Feature Selection and Outliers Detection with Genetic Algorithms and Neural Networks

Identificador:  imarina:4131800

Handle: https://hdl.handle.net/20.500.11797/imarina4131800

Autores:  Solanas, A; Romero, E; Gomez, S; Sopena, JM; Alquezar, R; Domingo-Ferrer, J

Resumen:
This paper presents a new feature selection method and an outliers detection algorithm The presented method is based on using a genetic algorithm combined with a problem specific designed neural network The dimensional reduction and the outliers detection makes the resulting dataset more suitable for training neural networks A comparative analysis between different kind of proposed criteria to select the features is reported A number of experimental results have been carried out to demonstrate the usefulness of the presented technique