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On Evaluation of a Population of Bayesian Networks
Hoai-Tuong Nguyen ( ) 1, Gérard Ramstein 1, Philippe Leray 1
For the BIL Project collaboration(s)
(2012-01-06)

Two new evaluation of quality approaches for a population of Bayesian networks (BN) are proposed in this paper. The first approach relies on the use of statistical principle with application of well-known evaluation methods. The other bases on quasi essential graph (QEG), an extension of essential graph (EG), that is a presentative graph for all BN of the population. In QEG, each edge is statistically weighted in two parts: (1) undirected part that represents the power of the relationship; (2) arrow part that represents the reliability of the orientation. Results of application to the both simulated and real-world problems show that these proposed approaches are the others helpful solutions for the problem of edge orientation and for the visualization of results of evaluation methods.
1:  Laboratoire d'Informatique de Nantes Atlantique (LINA)
CNRS : UMR6241 – Université de Nantes – École Nationale Supérieure des Mines - Nantes
Computer Science/Artificial Intelligence
quasi essential graph – Bayesian networks
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