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

by Kjærulff, Uffe B [author.]; Madsen, Anders L [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Information Science and Statistics: 22Publisher: New York, NY : Springer New York : 2013.Edition: Second Edition.Description: XVII, 382 p. 186 illus. online resource.ISBN: 9781461451044.Subject(s): Statistics | Computer science | Data mining | Artificial intelligence | Distribution (Probability theory) | Mathematical statistics | Statistics | Statistics and Computing/Statistics Programs | Probability and Statistics in Computer Science | Data Mining and Knowledge Discovery | Artificial Intelligence (incl. Robotics) | Operations Research, Management Science | Probability Theory and Stochastic ProcessesDDC classification: 519.5 Online resources: Click here to access online
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.
In: Springer eBooksSummary: 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.
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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.

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.

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