Feature Selection and Outliers Detection with Genetic Algorithms and Neural Networks

Abstract. 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. Keywords. Feature Selection, Genetic Algorithms, Neural Networks,

• Type: Conference
• Year: 2005
• Where: CCIA
• Authors: Agusti Solanas, Enrique Romero, Sergio Gómez, Josep M. Sopena, René Alquézar, Josep Domingo-Ferrer
• Keywords: Artificial Intelligence, CCIA 2005, Genetic Algorithms, Neural Networks, Outliers Detection