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Bayesian Networks and Decision Graphs
Paperback
Series: Information Science and Statistics
General ComputersGeneral MathematicsProbability & Statistics
ISBN13: 9781441923943
Publisher: Springer Nature
Published: Nov 23 2010
Pages: 447
Weight: 1.40
Height: 0.90 Width: 6.00 Depth: 9.00
Language: English
This is a brand new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical models including Bayesian networks and influence diagrams. The reader is guided through the two types of frameworks with examples and exercises, which also give instruction on how to build these models. Structured in two parts, the first section focuses on probabilistic graphical models, while the second part deals with decision graphs, and in addition to the frameworks described in the previous edition, also introduces Markov decision process. The new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network.
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