Symbolic regression for knowledge discovery
Gabriel Kronberger · ACM SIGEVOlution · 2011
This work describes an approach for data analysis based on symbolic regression and genetic programming, that produces an overall view of the dependencies of all variables of a system. The identi?ed dependencies are represented in form of a variable interaction network.