Sensitivity Analysis of Probabilistic Graphical Models : Theoretical Results and Their Applications on Bayesian Network Modeling and Inference

Language: English

Published by VDM Verlag Dr. Müller, 2009

3639136950 / 9783639136951

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nach der Bestellung gedruckt Neuware - Printed after ordering - Probabilistic graphical models such as Bayesian networks are widely used for large-scale data analysis in various fields such as customer data analysis and medical diagnosis, as they model probabilistic knowledge naturally and allow the use of efficient inference algorithms to draw conclusions from the model. Sensitivity analysis of probabilistic graphical models is the analysis of the relationships between the inputs (local beliefs), such as network parameters, and the outputs (global beliefs), such as values of probabilistic queries, and addresses the central research problem of how beliefs will be changed when we incorporate new information to the current model. This book provides many theoretical results, such as the assessment of global belief changes due to local belief changes, the identification of local belief changes that induce certain global belief changes, and the quantifying of belief changes in general. These results can be applied on the modeling and inference of Bayesian networks, and provide a critical tool for the researchers, developers, and users of Bayesian networks during the process of probabilistic data modeling and reasoning. …

Seller Inventory # 9783639136951

Title
Sensitivity Analysis of Probabilistic Graphical Models : Theoretical Results and Their Applications on Bayesian Network Modeling and Inference
Author
Hei Chan
Publisher
VDM Verlag Dr. Müller
Publication year
2009
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3639136950
ISBN 13
9783639136951
Item weight
234 grams
Dimensions
220x150x10 mm

AHA-BUCH GmbH

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