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Innovations in Bayesian Networks: Theory and Applications: 156
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Innovations in Bayesian Networks: Theory and Applications: 156 - Livro de bolso

2010, ISBN: 9783642098758

redacteur: Holmes, Dawn E. Springer, Paperback, Auflage: Softcover reprint of hardcover 1st ed. 2008, 332 Seiten, Publiziert: 2010-11-30T00:00:01Z, Produktgruppe: Book, Hersteller-Nr.: bl… mais…

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Innovations in Bayesian Networks Theory and Applications - Holmes, Dawn E. (Herausgeber)
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Holmes, Dawn E. (Herausgeber):

Innovations in Bayesian Networks Theory and Applications - Livro de bolso

2010, ISBN: 3642098754

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Softcover reprint of hardcover 1st ed. 2008 Kartoniert / Broschiert Künstliche Intelligenz, bayesiannetworks; Bayesiannetwork; LearningBayesiannetworks; Topologie; ArtificialIntelligenc… mais…

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Innovations in Bayesian Networks: Theory and Applications (Studies in Computational Intelligence (156)) - Livro de bolso

2010

ISBN: 3642098754

[EAN: 9783642098758], Tweedehands, als nieuw, [SC: 35.04], [PU: Springer], Like New, Books

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Innovations in Bayesian Networks: Theory and Applications (Studies in Computational Intelligence (156)) - Livro de bolso

2010, ISBN: 3642098754

[EAN: 9783642098758], D'occasion, comme neuf, [SC: 23.11], [PU: Springer], Like New, Books

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Holmes, Dawn E.:
Innovations in Bayesian Networks : Theory and Applications - Livro de bolso

ISBN: 9783642098758

paperback, [PU: Springer, Berlin/Heidelberg/New York, NY]

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Innovations in Bayesian Networks: Theory and Applications: 156
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9783642098758


Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. Each of the twelve chapters is self-contained.Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Graduate students since it shows the direction of current research.

Dados detalhados do livro - Innovations in Bayesian Networks: Theory and Applications: 156


EAN (ISBN-13): 9783642098758
ISBN (ISBN-10): 3642098754
Livro de capa dura
Livro de bolso
Ano de publicação: 2010
Editor/Editora: Springer
332 Páginas
Peso: 0,503 kg
Língua: eng/Englisch

Livro na base de dados desde 2010-10-29T09:02:47+01:00 (Lisbon)
Página de detalhes modificada pela última vez em 2024-03-16T09:47:01+00:00 (Lisbon)
Número ISBN/EAN: 9783642098758

Número ISBN - Ortografia alternativa:
3-642-09875-4, 978-3-642-09875-8
Ortografia alternativa e termos de pesquisa relacionados:
Autor do livro: holmes, holme
Título do livro: innovations bayesian networks, innovation networks, bayes networks

Dados da editora

Autor: Dawn E. Holmes
Título: Studies in Computational Intelligence; Innovations in Bayesian Networks - Theory and Applications
Editora: Springer; Springer Berlin
322 Páginas
Ano de publicação: 2010-11-30
Berlin; Heidelberg; DE
Impresso / Feito em
Língua: Inglês
160,49 € (DE)
164,99 € (AT)
177,00 CHF (CH)
POD
X, 322 p. 92 illus.

BC; Hardcover, Softcover / Technik/Allgemeines, Lexika; Mathematik für Ingenieure; Verstehen; Bayesian Networks; Bayesian network; Learning Bayesian networks; Topologie; artificial intelligence; computational intelligence; intelligence; learning; modeling; statistics; system modeling; Mathematical and Computational Engineering Applications; Artificial Intelligence; Künstliche Intelligenz; BB

to Bayesian Networks.- A Polemic for Bayesian Statistics.- A Tutorial on Learning with Bayesian Networks.- The Causal Interpretation of Bayesian Networks.- An Introduction to Bayesian Networks and Their Contemporary Applications.- Objective Bayesian Nets for Systems Modelling and Prognosis in Breast Cancer.- Modeling the Temporal Trend of the Daily Severity of an Outbreak Using Bayesian Networks.- An Information-Geometric Approach to Learning Bayesian Network Topologies from Data.- Causal Graphical Models with Latent Variables: Learning and Inference.- Use of Explanation Trees to Describe the State Space of a Probabilistic-Based Abduction Problem.- Toward a Generalized Bayesian Network.- A Survey of First-Order Probabilistic Models.
Presents the innovative paradigms related to the theory and practical applications of Bayesian Networks

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