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Advances in Bayesian Networks, Jos? A. G?mez; Serafin Moral; Antonio Salmer?n Cer


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Автор: Jos? A. G?mez; Serafin Moral; Antonio Salmer?n Cer
Название:  Advances in Bayesian Networks
ISBN: 9783642058851
Издательство: Springer
Классификация:



ISBN-10: 364205885X
Обложка/Формат: Paperback
Страницы: 328
Вес: 0.48 кг.
Дата издания: 15.12.2010
Серия: Studies in Fuzziness and Soft Computing
Язык: English
Размер: 234 x 156 x 18
Основная тема: Mathematics
Ссылка на Издательство: Link
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Поставляется из: Германии

Innovations in Bayesian Networks

Автор: Dawn E. Holmes
Название: Innovations in Bayesian Networks
ISBN: 3540850651 ISBN-13(EAN): 9783540850656
Издательство: Springer
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Цена: 191560.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume the editors have brought together contributions from some of the most prestigious researchers in this field.

Innovations in Bayesian Networks

Автор: Dawn E. Holmes
Название: Innovations in Bayesian Networks
ISBN: 3642098754 ISBN-13(EAN): 9783642098758
Издательство: Springer
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Цена: 174130.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume the editors have brought together contributions from some of the most prestigious researchers in this field.

Advances in Neural Networks -- ISNN 2010

Автор: James Kwok; Liqing Zhang; Bao-Liang Lu
Название: Advances in Neural Networks -- ISNN 2010
ISBN: 3642133177 ISBN-13(EAN): 9783642133176
Издательство: Springer
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Цена: 111790.00 T
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Описание: Constitutes the proceedings of the 7th International Symposium on Neural Networks, ISNN 2010, held in Shanghai, China, June 6-9, 2010. This title presents the papers that focus on topics such as SVM and Kernel Methods, Vision and Image, Data Mining and Text Analysis, BCI and Brain Imaging and its applications.

Bayesian Analysis with Stata

Автор: Thompson John
Название: Bayesian Analysis with Stata
ISBN: 1597181412 ISBN-13(EAN): 9781597181419
Издательство: Taylor&Francis
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Цена: 57150.00 T
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Описание:

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Stata's data management and graphing capability to be used with OpenBUGS/WinBUGS speed and reliability.

The book emphasizes practical data analysis from the Bayesian perspective, and hence covers the selection of realistic priors, computational efficiency and speed, the assessment of convergence, the evaluation of models, and the presentation of the results. Every topic is illustrated in detail using real-life examples, mostly drawn from medical research.

The book takes great care in introducing concepts and coding tools incrementally so that there are no steep patches or discontinuities in the learning curve. The book's content helps the user see exactly what computations are done for simple standard models and shows the user how those computations are implemented. Understanding these concepts is important for users because Bayesian analysis lends itself to custom or very complex models, and users must be able to code these themselves.


Modeling and Reasoning with Bayesian Networks

Автор: Darwiche
Название: Modeling and Reasoning with Bayesian Networks
ISBN: 1107678420 ISBN-13(EAN): 9781107678422
Издательство: Cambridge Academ
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Цена: 65470.00 T
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Описание: This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis.

Advances in Neural Networks  -- ISNN 2010

Автор: James Kwok; Bao-Liang Lu; Liqing Zhang; Bao-Liang
Название: Advances in Neural Networks -- ISNN 2010
ISBN: 3642132774 ISBN-13(EAN): 9783642132773
Издательство: Springer
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Цена: 121110.00 T
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Описание: Constitutes the proceedings of the 7th International Symposium on Neural Networks, ISNN 2010, held in Shanghai, China, June 6-9, 2010. This title presents the papers that focus on topics such as Neurophysiological Foundation, Theory and Models, Learning and Inference, and Neurodynamics.

Bayesian networks in r

Автор: Nagarajan, Radhakrishnan Scutari, Marco Lebre, Sophie
Название: Bayesian networks in r
ISBN: 1461464455 ISBN-13(EAN): 9781461464457
Издательство: Springer
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Цена: 40050.00 T
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Описание: This book introduces readers essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R. Each chapter includes exercises with solutions.

Bayesian networks and influence diagrams: a guide to construction and analysis

Автор: Kjarulff, Uffe B. Madsen, Anders L.
Название: Bayesian networks and influence diagrams: a guide to construction and analysis
ISBN: 1461451035 ISBN-13(EAN): 9781461451037
Издательство: Springer
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Цена: 111790.00 T
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Описание: In a Second Edition offering six new sections, new examples, tables, figures and more, this book shows how to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Includes more than 140 examples.

Advances in Neural Networks - ISNN 2017

Автор: Fengyu Cong; Andrew Leung; Qinglai Wei
Название: Advances in Neural Networks - ISNN 2017
ISBN: 3319590715 ISBN-13(EAN): 9783319590714
Издательство: Springer
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Цена: 74530.00 T
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Описание: This book constitutes the refereed proceedings of the 14th International Symposium on Neural Networks, ISNN 2017, held in Sapporo, Hakodate, and Muroran, Hokkaido, Japan, in June 2017. The 135 revised full papers presented in this two-volume set were carefully reviewed and selected from 259 submissions.

Advances in Neural Networks - ISNN 2017

Автор: Fengyu Cong; Andrew Leung; Qinglai Wei
Название: Advances in Neural Networks - ISNN 2017
ISBN: 3319590804 ISBN-13(EAN): 9783319590806
Издательство: Springer
Рейтинг:
Цена: 74530.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 14th International Symposium on Neural Networks, ISNN 2017, held in Sapporo, Hakodate, and Muroran, Hokkaido, Japan, in June 2017. The 135 revised full papers presented in this two-volume set were carefully reviewed and selected from 259 submissions.

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

Автор: Uffe B. Kj?rulff; Anders L. Madsen
Название: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
ISBN: 1493900293 ISBN-13(EAN): 9781493900299
Издательство: Springer
Рейтинг:
Цена: 121110.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In a Second Edition offering six new sections, new examples, tables, figures and more, this book shows how to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Includes more than 140 examples.

Bayesian Networks in Educational Assessment

Автор: Russell G. Almond; Robert J. Mislevy; Linda S. Ste
Название: Bayesian Networks in Educational Assessment
ISBN: 149392124X ISBN-13(EAN): 9781493921249
Издательство: Springer
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Цена: 83850.00 T
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Описание: Bayesian Networks in Educational Assessment


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