Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis von Uffe B. Kjærulff | ISBN 9781461451044

Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis

von Uffe B. Kjærulff und Anders L. Madsen
Mitwirkende
Autor / AutorinUffe B. Kjærulff
Autor / AutorinAnders L. Madsen
Buchcover Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis | Uffe B. Kjærulff | EAN 9781461451044 | ISBN 1-4614-5104-3 | ISBN 978-1-4614-5104-4
Leseprobe

From the book reviews:

“The monograph concentrates on intelligent systems for decision support based on probabilistic models, including Bayesian networks and influence diagrams. … This monograph provides a review of recent state affairs of probabilistic networks that can be useful for professionals, practitioners, and researchers from diverse fields of statistics and related disciplines. I think it can be used as a textbook in its own right for an upper level undergraduate course, especially for a reading course.” (Technometrics, Vol. 55 (2), May, 2013)

Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis

von Uffe B. Kjærulff und Anders L. Madsen
Mitwirkende
Autor / AutorinUffe B. Kjærulff
Autor / AutorinAnders L. Madsen

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 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.