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Titlebook: Probabilistic Networks and Expert Systems; Exact Computational Robert G. Cowell,A. Philip Dawid,David J. Spiegelh Book 1999 Springer Scien

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書目名稱Probabilistic Networks and Expert Systems
副標(biāo)題Exact Computational
編輯Robert G. Cowell,A. Philip Dawid,David J. Spiegelh
視頻videohttp://file.papertrans.cn/757/756817/756817.mp4
概述Winner of the De..Groot Prize 2002, the only book prize in the field of statistics
叢書名稱Information Science and Statistics
圖書封面Titlebook: Probabilistic Networks and Expert Systems; Exact Computational  Robert G. Cowell,A. Philip Dawid,David J. Spiegelh Book 1999 Springer Scien
描述.WINNER OF THE 2001 DEGROOT PRIZE!...Probabilistic expert systems are graphical networks that support the modelling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors over a number of years, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms, emphasizing those cases in which exact answers are obtainable. It covers both the updating of probabilistic uncertainty in the light of new evidence, and statistical inference, about unknown probabilities or unknown model structure, in the light of new data. The careful attention to detail will make this work an important reference source for all those involved in the theory and applications of probabilistic expert systems....This book was awarded the first DeGroot Prize by the International Society for Bayesian Analysis for a book making an important, timely, thorough, and notably original contribution to the statistics literature..
出版日期Book 1999
關(guān)鍵詞Bayesian Network; Graphical model; Junction tree; Machine learning; Probability propagation; artificial i
版次1
doihttps://doi.org/10.1007/b97670
isbn_softcover978-0-387-71823-1
isbn_ebook978-0-387-22630-9Series ISSN 1613-9011 Series E-ISSN 2197-4128
issn_series 1613-9011
copyrightSpringer Science+Business Media New York 1999
The information of publication is updating

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Book 1999rge complex domains, while retaining ease of calculation. Building on original research by the authors over a number of years, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms, emphasizing those cases in which exact answers are obtain
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are introduced by example and you learn how they work together..In the. Complete Guide to Open Source Big Data Stack, .the author?begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack—sharing
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978-0-387-71823-1Springer Science+Business Media New York 1999
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Probabilistic Networks and Expert Systems978-0-387-22630-9Series ISSN 1613-9011 Series E-ISSN 2197-4128
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