A First Study on the Use of Coevolutionary Algorithms for Instance and Feature Selection

  • Authors:
  • Joaquín Derrac;Salvador García;Francisco Herrera

  • Affiliations:
  • Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain 18071;Department of Computer Science, University of Jaén, Jaén, Spain 23071;Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain 18071

  • Venue:
  • HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
  • Year:
  • 2009

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Abstract

Cooperative Coevolution is a technique in the area of Evolutionary Computation. It has been applied to many combinatorial problems with great success. This contribution proposes a Cooperative Coevolution model for simultaneous performing some data reduction processes in classification with nearest neighbours methods through feature and instance selection. In order to check its performance, we have compared the proposal with other evolutionary approaches for performing data reduction. Results have been analyzed and contrasted by using non-parametric statistical tests, finally showing that the proposed model outperforms the non-cooperative evolutionary techniques.