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Bayesian Network: Probabilistic Reasoning, Statistical Learning, and Applications
Yoichi Motomura
National Institute of Advanced Industrial Science and Technology, 2-41-6 Aomi, Koto-ku, Tokyo 135-0064, Japan
Received:September 18, 2003Accepted:December 1, 2003Published:March 20, 2004
Keywords:Bayesian network, probabilistic reasoning, statistical learning, intelligent system, probabilistic model
Abstract
Bayesian networks are probabilistic models that can be used for prediction and decision-making in the presence of uncertainty. For intelligent information processing, probabilistic reasoning based on Bayesian networks can be used to cope with uncertainty in real-world domains. In order to apply this, we need appropriate models and statistical learning methods to obtain models. We start by reviewing Bayesian network models, probabilistic reasoning, statistical learning, and related researches. Then, we introduce applications for intelligent information processing using Bayesian networks.
Cite this article as:Y. Motomura, “Bayesian Network: Probabilistic Reasoning, Statistical Learning, and Applications,” J. Adv. Comput. Intell. Intell. Inform., Vol.8 No.2, pp. 93-99, 2004.Data files:
