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Titlebook: Genetic Programming; 16th European Confe Krzysztof Krawiec,Alberto Moraglio,Bin Hu Conference proceedings 2013 Springer-Verlag Berlin Heid

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Gerhard Lippe,Jörn Esemann,Thomas Tänzermming algorithm for solving multi-label classification problems using IF-THEN classification rules. This algorithm, called G3P-ML, is evaluated and compared to other multi-label classification techniques in different application domains. Computational experiments show that G3P-ML often obtains bette
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978-3-642-37206-3Springer-Verlag Berlin Heidelberg 2013
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Adaptive Distance Metrics for Nearest Neighbour Classification Based on Genetic Programminge neighbourhood along the directions for which the class conditional probabilities don’t change much. Initial empirical results on a set of real-world classification datasets showed that the proposed method enhances the generalisation performance of standard NN algorithm, and that it is a competent
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Automated Design of Probability Distributions as Mutation Operators for Evolutionary Programming Usiy distribution over a set of functions). The mutation probability distribution is trained on a set of function instances drawn from a given function class. It is then tested on a separate independent test set of function instances to confirm that the evolved probability distribution has indeed gener
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Robustness and Evolvability of Recombination in Linear Genetic Programmingerties. Utilizing a population evolution experiment, we demonstrate that recombination significantly accelerates the evolutionary search process and particularly promotes robust phenotypes that innovative phenotypic explorations.
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A New Implementation of Geometric Semantic GP and Its Application to Problems in Pharmacokineticslications, like the two problems in pharmacokinetics that we address here. Our results confirm the excellent evolvability of geometric semantic operators, demonstrated by the good results obtained on training data. Furthermore, we have also achieved a surprisingly good generalization ability, a fact
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