Improving Generalisation of Genetic Programming for Symbolic Regression with Structural Risk Minimisation

Generalisation is one of the most important performance measures for any learning algorithm, no exception to Genetic Programming (GP). A number of works have been devoted to improve the generalisation ability of GP for symbolic regression. Methods based on a reliable estimation of generalisation error of models during evolutionary process are a sensible… CONTINUE READING