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Bayesian networks have found application in a number of fields, including risk analysis, consumer help desks, tissue pathology, pattern recognition, credit assessment, computer network diagnosis, and artificial intelligence. Bayesian Networks is a self-contained introduction to the theory and applications of Bayesian networks. It introduces Bayesian networks, the Dirichlet distribution, exponential families and their applications and discusses graphical models, a topic with applications in the engineering and computer sciences. All concepts are clearly defined, illustrated with examples. An essential reference for postgraduate students of statistics, computer engineering and mathematics, data mining, artificial intelligence, computing and biology.
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