Feature Selection and Outliers Detection with Genetic Algorithms and Neural Networks

  • Authors:

  • Agusti Solanas;Enrique Romero;Sergio Gómez;Josep M. Sopena;Rene Alquézar;Josep Domingo-Ferrer

  • Affiliations:

  • Universitat Rovira i Virgili;Universitat Politècnica de Catalunya;Universitat Rovira i Virgili;Universitat de Barcelona;Universitat Politècnica de Catalunya;Universitat Rovira i Virgili

  • Venue:
  • Proceedings of the 2005 conference on Artificial Intelligence Research and Development
  • Year:
  • 2005

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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.