Building Optimal Committees of Genetic Programs

  • Byoung-Tak Zhang
  • Je-Gun Joung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1917)


Committee machines are known to improve the performance of individual learners. Evolutionary algorithms generate multiple individuals that can be combined to build committee machines. However, it is not easy to decide how big the committee should be and what members constitute the best committee. In this paper, we present a probabilistic search method for determining the size and members of the committees of individuals that are evolved by a standard GP engine. Applied to a suite of benchmark learning tasks, the GP committees achieved significant improvement in prediction accuracy.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Byoung-Tak Zhang
    • 1
  • Je-Gun Joung
    • 1
  1. 1.Artificial Intelligence Lab (SCAI) School of Computer Science and EngineeringSeoul National UniversitySeoulKorea

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