Titlebook: Genetic Programming; European Conference, Riccardo Poli,Wolfgang Banzhaf,Terence C. Fogarty Conference proceedings 2000 Springer-Verlag Ber

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https://doi.org/10.1007/978-3-0348-6598-2ark classification problems. Using GP we are able to induce decision trees with a linear combination of variables in each function node. A new representation of decision trees using strong typing in GP is introduced. With this representation it is possible to let the GP classify into any number of c

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https://doi.org/10.1007/b75085Adaptive Systems; Automat; Evolutionary Computation; Evolutionary Programming; Genetic Algorithms; Geneti

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Riccardo Poli,Wolfgang Banzhaf,Terence C. FogartyIncludes supplementary material:

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Der Stand des normalen Zwerchfells,offers an introduction to bias/variance decomposition of mean squared error, as well as a presentation of experimental results of the application of genetic programming. Finally ensemble methods such as bagging and boosting are discussed that can reduce the generalization error in genetic programming.

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Das Blau in der Tradition der Moderne, applying fitness sharing to genetic programs, in analogy with fitness sharing applied to genetic algorithms. The experimental results for several parameter settings are discussed. We observe that by applying fitness sharing the code growth of genetic programs could be limited.

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