Abstract:
This paper is devoted to the clustering belief updating algorithm using the junction
tree as a tree graph representation of Bayesian networks. The algorithm is
applicable for predictions based on a learned Bayesian network as well as
for supporting an exact network learning process, for example, the EM algorithm.
The constructing steps and the principles of work with the junction tree are
specified. The software implementation of the algorithm is also considered.