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Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis / by Uffe B. Kjærulff, Anders L. Madsen.

SpringerLink Books Computer Science (2011-2024) Available online

View online
Format:
Book
Author/Creator:
Kjaerulff, Uffe B., author.
Madsen, Anders L., author.
Contributor:
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
Information science and statistics 1613-9011 ; 22.
Information Science and Statistics, 1613-9011 ; 22
Language:
English
Subjects (All):
Statistics.
Mathematical statistics.
Data mining.
Artificial intelligence.
Operations research.
Management science.
Probabilities.
Statistics and Computing/Statistics Programs.
Probability and Statistics in Computer Science.
Data Mining and Knowledge Discovery.
Artificial Intelligence.
Operations Research, Management Science.
Probability Theory and Stochastic Processes.
Local Subjects:
Statistics and Computing/Statistics Programs.
Probability and Statistics in Computer Science.
Data Mining and Knowledge Discovery.
Artificial Intelligence.
Operations Research, Management Science.
Probability Theory and Stochastic Processes.
Physical Description:
1 online resource (XVIII, 382 pages).
Edition:
Second edition 2013.
Contained In:
Springer eBooks
Place of Publication:
New York, NY : Springer New York : Imprint: Springer, 2013.
System Details:
text file PDF
Summary:
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new sections, in addition to fully-updated examples, tables, figures, and a revised appendix. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented on model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined based on numerous courses the authors have held for practitioners worldwide. Uffe B. Kjærulff holds a PhD on probabilistic networks and is an Associate Professor of Computer Science at Aalborg University. Anders L. Madsen of HUGIN EXPERT A/S holds a PhD on probabilistic networks and is an Adjunct Professor of Computer Science at Aalborg University.
Contents:
Introduction
Networks
Probabilities
Probabilistic Networks
Solving Probabilistic Networks
Eliciting the Model
Modeling Techniques
Data-Driven Modeling
Conflict Analysis
Sensitivity Analysis
Value of Information Analysis
Quick Reference to Model Construction
List of Examples
List of Figures
List of Tables
List of Symbols
References
Index.
Other Format:
Printed edition:
ISBN:
978-1-4614-5104-4
9781461451044
Access Restriction:
Restricted for use by site license.

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