Probabilistic reasoning in intelligent systems: networks of plausible inference
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Learning belief networks from data: an information theory based approach
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
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The Journal of Machine Learning Research
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This paper introduces a new Bayesian network structure, named a Partial Bayesian Network (PBN), and describes an algorithm for constructing it. The PBN is designed to be used for classification tasks, and accordingly the algorithm constructs an approximate Markov blanket around a classification node. Initial experiments have compared the performance of the PBN algorithm with Na茂ve Bayes, Tree-Augmented Na茂ve Bayes and a general Bayesian network algorithm (K2). The results indicate that PBN performs better than other Bayesian network classification structures on some problem domains.