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

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

автор Hei C. издательство Книга по Требованию Локальные и корпоративные сети
Cтраниц 164        мягкая обложка       
Аннотация: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. 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. 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. 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.
Автор: Hei C.
Издательство: Книга по Требованию
Год:2009
Цена:
2783 руб
Нет в наличии
Поиск: Sensitivity Analysis of Probabilistic Graphical Models. Theoretical Results and Their Applications on Bayesian Network Modeling and Inference
НОВЫЙ ГОД СИМВОЛ 2013 ГОДАУКРАШЕНИЯ
КАРНАВАЛ НА НОВЫЙ ГОД РАСПРОДАЖА
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Управление конфигурацией в стандартах CMM и ISO...

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