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Chapman & Hall/CRC Computer Science & Data Analysis #2: Bayesian Artificial Intelligence, Second Edition

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Chapman & Hall/CRC Computer Science & Data Analysis #2: Bayesian Artificial Intelligence, Second Edition Cover

 

Synopses & Reviews

Book News Annotation:

Bayesian artificial intelligence results from using Bayesian inferential methods in developing a software architecture for an artificial intelligence, explain Korb and Nicholson (both computer science, Monash U., Melbourne). They present the elements of Bayesian network technology, automated causal discovery, learning probabilities from data, and examples and ideas about how to employ these technologies in developing probabilistic expert systems. Their topics include Bayesian reasoning, decision networks, learning linear causal models, and knowledge engineering with Bayesian networks. Among the case studies are poker, and Goulburn catchment ecological risk assessment. No date is cited for the first edition. Annotation ©2011 Book News, Inc., Portland, OR (booknews.com)

Synopsis:

Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.

New to the Second Edition

    • New chapter on Bayesian network classifiers
    • New section on object-oriented Bayesian networks
    • New section that addresses foundational problems with causal discovery and Markov blanket discovery
    • New section that covers methods of evaluating causal discovery programs
    • Discussions of many common modeling errors
    • New applications and case studies
    • More coverage on the uses of causal interventions to understand and reason with causal Bayesian networks

    Illustrated with real case studies, the second edition of this bestseller continues to cover the groundwork of Bayesian networks. It presents the elements of Bayesian network technology, automated causal discovery, and learning probabilities from data and shows how to employ these technologies to develop probabilistic expert systems.

    Web Resource

    The book 's website at www.csse.monash.edu.au/bai/book/book.html offers a variety of supplemental materials, including example Bayesian networks and data sets. Instructors can email the authors for sample solutions to many of the problems in the text.

    Synopsis:

    "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"--

    Product Details

    ISBN:
    9781439815915
    Author:
    Korb, Kevin B.
    Publisher:
    CRC Press
    Author:
    Nicholson, Ann E.
    Subject:
    Statistics
    Subject:
    Software Development & Engineering - Systems
    Subject:
    Mathematics - Statistics
    Edition Description:
    New
    Series:
    Chapman & Hall/CRC Computer Science & Data Analysis
    Series Volume:
    2
    Publication Date:
    20101231
    Binding:
    Hardcover
    Language:
    English
    Pages:
    392

    Related Subjects

    Business » General
    Business » Management
    Business » Writing
    Computers and Internet » Software Engineering » Systems Analysis and Design
    Science and Mathematics » Mathematics » Probability and Statistics » General
    Science and Mathematics » Mathematics » Probability and Statistics » Statistics

    Chapman & Hall/CRC Computer Science & Data Analysis #2: Bayesian Artificial Intelligence, Second Edition New Hardcover
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    $120.25 In Stock
    Product details 392 pages CRC Press - English 9781439815915 Reviews:
    "Synopsis" by , Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.

    New to the Second Edition

      • New chapter on Bayesian network classifiers
      • New section on object-oriented Bayesian networks
      • New section that addresses foundational problems with causal discovery and Markov blanket discovery
      • New section that covers methods of evaluating causal discovery programs
      • Discussions of many common modeling errors
      • New applications and case studies
      • More coverage on the uses of causal interventions to understand and reason with causal Bayesian networks

      Illustrated with real case studies, the second edition of this bestseller continues to cover the groundwork of Bayesian networks. It presents the elements of Bayesian network technology, automated causal discovery, and learning probabilities from data and shows how to employ these technologies to develop probabilistic expert systems.

      Web Resource

      The book 's website at www.csse.monash.edu.au/bai/book/book.html offers a variety of supplemental materials, including example Bayesian networks and data sets. Instructors can email the authors for sample solutions to many of the problems in the text.

      "Synopsis" by , "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"--
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