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Bayesian Networks and Decision Graphs : February 8, 2007

Author: Finn V Jensen; Michael Jordan; Jon Kleinberg; Thomas Dyhre Nielsen; Bernhard Schölkopf
Publisher: New York, NY : Springer New York, 2007.
Series: Information science and statistics.
Edition/Format:   eBook : Document : English : 2nd edView all editions and formats
Summary:
Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Finn V Jensen; Michael Jordan; Jon Kleinberg; Thomas Dyhre Nielsen; Bernhard Schölkopf
ISBN: 9780387682822 0387682821
OCLC Number: 465650550
Description: 1 online resource.
Contents: Prerequisites on Probability Theory --
Prerequisites on Probability Theory --
Probabilistic Graphical Models --
Causal and Bayesian Networks --
Building Models --
Belief Updating in Bayesian Networks --
Analysis Tools for Bayesian Networks --
Parameter estimation --
Learning the Structure of Bayesian Networks --
Bayesian Networks as Classifiers --
Decision Graphs --
Graphical Languages for Specification of Decision Problems --
Solution Methods for Decision Graphs --
Methods for Analyzing Decision Problems.
Series Title: Information science and statistics.
Responsibility: by Finn V. Jensen, Thomas D. Nielsen ; edited by Michael Jordan, Jon Kleinberg, Bernhard Schölkopf.

Abstract:

This is a 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. It  Read more...

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From the reviews:MATHEMATICAL REVIEWS"This is indeed an invaluable text for students in information technology, engineering, and statistics. It is also very helpful for researchers in these fields Read more...

 
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