Finding Variables That Work

Abstract

This paper outlines a strategy for using two large-scale computer programs, the Automatic Interaction Detection and Multiple Classification Analysis algorithms. They supplement each other in the inductive task of formulating a model of the simultaneous effects of a set of independent variables on a criterion. MCA handles correlated predictors well, but assumes away interactions. Terms representing this type of joint effect are located by preliminary AID runs.