Symbolic Regression refers to the search for a mathematical expression that describes a nonlinear relationship between variables from some data set. The usual representation for a solution from the search space is the Expression Tree which is capable of representing every solution from the space of mathematical expressions. While the generalization power is desirable, a large portion of the search space is composed of very complicated expressions that are no better than a black box model. In this project we seek a restrictive representation that only allows simple expressions while keeping the space general enough to approximate the data relationship.
Graduate students: Cássia de Souza Carvalho