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by Byoung-tak Zhang, Je-gun Joung
in Parallel Problem Solving from Nature – PPSN VI
http://bi.snu.ac.kr/Publications/Journals/International/LNCS1917.ps
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Abstract:
Abstract. 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 signi-cant improvement in prediction accuracy. 1
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