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

AvUffe B. Kjærulff,Anders L. Madsen

Häftad, Engelska, 2014

Del 22 i serien Information Science and Statistics

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Häftad

819 kr

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867 kr

Beskrivning

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.

Produktinformation

Utgivningsdatum:2014-12-13
Mått:155 x 235 x 22 mm
Vikt:604 g
Format:Häftad
Språk:Engelska
Serie:Information Science and Statistics
Antal sidor:382
Upplaga:2
Förlag:Springer-Verlag New York Inc.
ISBN:9781493900299

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Matematisk statistik inom Naturvetenskap och teknik
Databaser inom Data och IT

Mer om författaren

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.

Recensioner i media

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)

Innehållsförteckning

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.