GP-RVM: Genetic Programing-based Symbolic Regression Using Relevance Vector Machine

7 Jun 2018Hossein Izadi RadJi FengHitoshi Iba

This paper proposes a hybrid basis function construction method (GP-RVM) for Symbolic Regression problem, which combines an extended version of Genetic Programming called Kaizen Programming and Relevance Vector Machine to evolve an optimal set of basis functions. Different from traditional evolutionary algorithms where a single individual is a complete solution, our method proposes a solution based on linear combination of basis functions built from individuals during the evolving process... (read more)

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