Chapman & Hall/CRC computer science and data analysis series
Includes bibliographical references and index
I. PROBABILISTIC REASONING: Bayesian reasoning -- Introducing Bayesian networks -- Inference in Bayesian networks -- Decision networks -- Applications of Bayesian networks -- II. LEARNING CAUSAL MODELS: Learning probabilities -- Bayesian network classifiers -- Learning linear causal models -- Learning discrete causal structure -- III. KNOWLEDGE ENGINEERING: Knowledge engineering with Bayesian networks -- KEBN case studies
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"The second edition of this bestseller provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. This edition contains a new chapter on Bayesian network classifiers and a new section on object-oriented Bayesian networks, along with new applications and case studies. It includes a new section that addresses foundational problems with causal discovery and Markov blanket discovery and a new section that covers methods of evaluating causal discovery programs. The book also offers more coverage on the uses of causal interventions to understand and reason with causal Bayesian networks. Supplemental materials are available on the book's website"--Provided by publisher
Bayesian statistical decision theory-- Data processing