Amazon cover image
Image from Amazon.com

Bayesian artificial intelligence [Book] / Kevin B. Korb, Ann E. Nicholson.

By: Contributor(s): Material type: TextTextSeries: Computer science and data analysis series | Series in computer science and data analysisPublication details: Boca Raton, FL : CRC Press, c2011.Edition: 2nd edDescription: xxvii, 463 p. : ill. ; 25 cmISBN:
  • 1439815917 (hardback)
  • 9781439815915 (hardback)
Subject(s): DDC classification:
  • 519.5 42 22
Other classification:
  • 519.5 42
Contents:
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.
Summary: "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.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books Books Junaid Zaidi Library, COMSATS University Islamabad 519.5 42 KOR-B (Browse shelf(Opens below)) Available 47465
Total holds: 0

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.

"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.

There are no comments on this title.

to post a comment.