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Bayesian networks : an introduction /

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Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in clas...

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Bibliographic Details
Main Author: Koski, Timo
Other Authors: Noble, John M.
Format: eBook
Language:English
Published: Chichester, West Sussex, UK : John Wiley, ©2009.
Subjects:
Bayesian statistical decision theory.
Neural networks (Computer science)
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Graphical models and probabilistic reasoning
  • Conditional independence, graphs, and d-separation
  • Evidence, sufficiency and Monte Carlo methods
  • Decomposable graphs and chain graphs
  • Learning the conditional probability potentials
  • Learning the graph structure
  • Parameters and sensitivity
  • Graphical models and exponential families
  • Causality and intervention calculus
  • The junction tree and probability updating
  • Factor graphs and the sum product algorithm.