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Machine Learning Approach to Evolutionary Computation

  • Hitoshi IbaEmail author
Chapter

Abstract

This chapter gives several methods of evolutionary computation enhanced with machine learning techniques. The employed machine learning schemes are bagging, boosting, Gröbner bases, relevance vector machine, affinity propagation, SVM, and k-nearest neighbors. These are applied to the extension of GP (Genetic Programming), DE (Differential Evolution), and PSO (Particle Swarm Optimization).

Keywords

BagGP BoostGP Vanishing ideal GP (VIGP) Kaizen programming RVM-GP Sequential sparse Bayesian learning algorithm Particle swarm optimization based on affinity propagation (PSOAP) ILSDE SVC-DE TRAnsfer learning for DE (TRADE) NENDE (k-NN classifier for DE) 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.The University of TokyoTokyoJapan

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