Applying the deterministic annealing expectation maximization algorithm to Naive Bayes networks

A Bayesian Network is a means of representing relationships between a number of variables in some domain, . A directed acyclic graph (DAG) is used to represent the relationships between variables; nodes in the graph represent the variables themselves and arcs between them are used to indicate cause and effect, arcs being drawn from the causative variable to its immediate effect. Associated with each variable, , are two subsets of known as the parents and children of . These are, respectively, the set of all variables having a direct effect upon and the set of all variables which are directly affected by . Figure 1 shows a simple DAG representing the relationship between cause, disease and symptom for two different strains of the hepatitis virus. Here the parents of