INCREMENTAL COMPILATION OF BAYESIAN NETWORKS BASED ON MAXIMAL PRIME SUBGRAPHS

Incremental Compilation of Bayesian Networks Based on Maximal Prime Subgraphs

Incremental compilation of Bayesian networks

Most methods for exact probability propaga­ tion in Bayesian networks do not carry out the inference directly over the network, but over a secondary structure known as a junc­ tion tree or a join tree (JT). The process of obtaining a JT is usually termed compilation. As compilation is usually viewed as a whole process; each time the network is modified, a new compilation process has to be perfo...

Incremental Compilation of Object-Oriented Bayesian Networks

Object-oriented paradigms have been applied to Bayesian networks to provide a modular structure which allows greater flexibility and robustness. These object-oriented Bayesian networks may be used over larger and more complex domains. However, as the networks get larger, the computational cost of triangulation and junction tree construction grows. The process of creating new junction trees when...

Maximal Prime Subgraph Decomposition of Bayesian Networks

The authors present a method for decomposition of Bayesian networks into their maximal prime subgraphs. The correctness of the method is proven and results relating the maximal prime subgraph decomposition (MPD) to the maximal complete subgraphs of the moral graph of the original Bayesian network are presented. The maximal prime subgraphs of a Bayesian network can be organized as a tree which c...

Critical Remarks on the Maximal Prime Decomposition of Bayesian Networks

We present a critical analysis of the maximal prime decomposition of Bayesian networks (BNs). Our analysis suggests that it may be more useful to transform a BN into a hierarchical Markov network.