Variable Selection in Industrial Datasets Using Pareto Genetic Programming

Abstract

This chapter gives an overview, based on theexperience from the Dow Chemical Company, of theimportance of variable selection to build robust modelsfrom industrial datasets. A quick review of variableselection schemes based on linear techniques is given.A relatively simple fitness inheritance scheme isproposed to do nonlinear sensitivity analysis that isespecially effective when combined with Pareto GP. Themethod is applied to two industrial datasets with goodresults.