Overview
- Comprehensive introduction to probabilistic networks
- Written specifically for practitioners of applied artificial intelligence
- Complete guide to understand, construct, and analyze probabilistic networks
Part of the book series: Information Science and Statistics (ISS)
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Table of contents (11 chapters)
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Front Matter
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Model Construction
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Model Analysis
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Back Matter
Keywords
About this book
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty.
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. 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/her level of understanding.
The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide.
Reviews
From the reviews:
"The book under review is by two well known contributors to this general area. … the book, consisting of five chapters, provides a very clear, insightful introduction to this theory. … This is a good book for learning or teaching an important, practically useful topic. There are many good examples and example-based discussions." (Jayanta K. Ghosh, International Statistical Review, Vol. 76 (3), 2008)
Kjaerulff, Bayesian networks and influence Diagrams: …
“This book is written for practitioners wishing to understand, construct, and analyze decision support systems based on Bayesian networks and influence diagrams. …Simple worked examples are provided throughout….and exercises are included after each chapter. …this book is a useful addition to the texts on Bayesian networks. …covers many key aspects in the construction and analysis of decision support systems based on Bayesian networks and influence diagrams, achieving the authors’ stated goal; …I would certainly put this book on my reading list for decision analysis classes and recommend it for research students using these techniques…”(Journal of the American Statistical Association, September 2009, Vol. 104, No. 487)
Authors and Affiliations
Bibliographic Information
Book Title: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
Authors: Uffe B. Kjærulff, Anders L. Madsen
Series Title: Information Science and Statistics
DOI: https://doi.org/10.1007/978-0-387-74101-7
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag New York 2008
Softcover ISBN: 978-1-4419-2546-6Published: 19 November 2010
eBook ISBN: 978-0-387-74101-7Published: 20 December 2007
Series ISSN: 1613-9011
Series E-ISSN: 2197-4128
Edition Number: 1
Number of Pages: XVIII, 318
Topics: 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