Discrete Discriminant Analysis: The Performance of Combining Models by a Hierarchical Coupling Approach

Abstract

We are concerned with combining models in discrete discriminant analysis in the multiclass (K > 2) case. Our approach consists of decomposing the multiclass problem in several biclass problems embedded in a binary tree. The affinity coefficient (Matusita (1955); Bacelar-Nicolau (1981,1985)) is proposed for the choice of the hierarchical couples, at each level of the tree, among all possible forms of merging. For the combination of models we consider a single coefficient: a measure of the relative performance of models - the integrated likelihood coefficient (Ferreira et al., 1999)) and we evaluate its performance.