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Towards designing neural network ensembles by evolution

  • Yong Liu
  • Xin Yao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1498)

Abstract

This paper proposes a co-evolutionary learning system, i.e., CELS, to design neural network (NN) ensembles. CELS addresses the issue of automatic determination of the number of individual NNs in an ensemble and the exploitation of the interaction between individual NN design and combination. The idea of CELS is to encourage different individual NNs in the ensemble to learn different parts or aspects of the training data so that the ensemble can learn the whole training data better. The cooperation and specialisation among different individual NNs are considered during the individual NN design. This provides an opportunity for different NNs to interact with each other and to specialise. Experiments on two real-world problems demonstrate that CELS can produce NN ensembles with good generalisation ability.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Yong Liu
    • 1
  • Xin Yao
    • 1
  1. 1.Computational Intelligence Group, School of Computer Science University CollegeThe University of New South Wales Australian Defence Force AcademyCanberraAustralia

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