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Improving Generalisation Performance Through Multiobjective Parsimony Enforcement
Yaniv Bernstein, Xiaodong Li, Vic Ciesielski, and Andy Song
School of Computer Science and Information Technology, RMIT University, VIC 3001, Melbourne, AustraliaAbstract. This paper describes POPE-GP, a system that makes use of the NSGA-II multiobjective evolutionary algorithm as an alternative, parameter-free technique for eliminating program bloat. We test it on a classification problem and find that while vastly reducing program size, the technique does improve generalisation performance.
LNCS 3103, p. 702 f.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2004