Bayesian network prediction: algorithm and software implementation

Authors

  • E.D. Maslennikov Dimonta
  • V.B. Sulimov Lomonosov Moscow State University

Keywords:

Bayesian network, belief network, belief update, expert system, join tree, junction tree, probabilistic interference, probabilistic propagation

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.

Author Biographies

E.D. Maslennikov

Dimonta, LLC
• Student

V.B. Sulimov

References

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Published

22-11-2010

How to Cite

Масленников Е., Сулимов В. Bayesian Network Prediction: Algorithm and Software Implementation // Numerical Methods and Programming (Vychislitel’nye Metody i Programmirovanie). 2010. 11. 94-107

Issue

Section

Section 2. Programming

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