Building a bayesian factor tree from examples

Abstract

A criterion based on mutual information among variables is proposed for building a bayesian tree from a finite number of examples. The factor graph, in Forney-style form, can be used as an associative memory that performs probabilistic inference in data fusion applications. The procedure is explained with the aid of a fully-described example.