Bayesian Networks and Decision Graphs

Bayesian Networks and Decision Graphs by Thomas Dyhre Nielsen, FINN VERNER JENSEN.

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 algor...

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Bibliographic Details
Main Authors: Nielsen, Thomas Dyhre (Author), VERNER JENSEN, FINN (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2007.
Edition:2nd ed. 2007.
Series:Information Science and Statistics,
Springer eBook Collection.
Subjects:
Plant science.
Botany.
Probabilities.
Mathematical statistics.
Artificial intelligence.
Statistics .
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of 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.

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