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Titlebook: Bayesian Networks and Decision Graphs; Finn V. Jensen Textbook 20011st edition Springer Science+Business Media New York 2001 Bayesian Netw

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期刊全稱Bayesian Networks and Decision Graphs
影響因子2023Finn V. Jensen
視頻videohttp://file.papertrans.cn/182/181863/181863.mp4
發(fā)行地址Gives a well-founded practical introduction to Bayesian networks.Includes presentation of the most efficient algorithm for solving influence diagrams
學科分類Information Science and Statistics
圖書封面Titlebook: Bayesian Networks and Decision Graphs;  Finn V. Jensen Textbook 20011st edition Springer Science+Business Media New York 2001 Bayesian Netw
影響因子Bayesian networks and decision graphs are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. Their strengths are two-sided. It is easy for humans to construct and to understand them, and when communicated to a computer, they can easily be compiled. Furthermore, handy algorithms are developed for analyses of the models and for providing responses to a wide range of requests such as belief updating, determining optimal strategies, conflict analyses of evidence, and most probable explanation. The book emphasizes both the human and the computer sides. Part I gives a thorough introduction to Bayesian networks as well as decision trees and infulence diagrams, and through examples and exercises, the reader is instructed in building graphical models from domain knowledge. This part is self-contained and it does not require other background than standard secondary school mathematics. Part II is devoted to the presentation of algorithms and complexity issues. This part is also self-contained, but it requires that the reader is familiar with working with texts in the mathematical language. The author also:.- provides a
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Belief Updating in Bayesian Networksworks. As shown in Chapter 1, access to . is sufficient for the calculations. However, because the joint probability table increases exponentially with the number of variables, we look for more efficient methods. Unfortunately, no method guarantees a tractable calculation task. However, the method p
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1613-9011 s part is also self-contained, but it requires that the reader is familiar with working with texts in the mathematical language. The author also:.- provides a 978-1-4757-3502-4Series ISSN 1613-9011 Series E-ISSN 2197-4128
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Textbook 20011st editionder uncertainty. Their strengths are two-sided. It is easy for humans to construct and to understand them, and when communicated to a computer, they can easily be compiled. Furthermore, handy algorithms are developed for analyses of the models and for providing responses to a wide range of requests
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