Articles liés à Bayesian Networks and Decision Graphs
Synopsis
This is a new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical models including Bayesian networks and influence diagrams. It presents a thorough introduction to state-of-the-art solution and analysis algorithms.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Présentation de l'éditeur
This is a new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical models including Bayesian networks and influence diagrams. It presents a thorough introduction to state-of-the-art solution and analysis algorithms.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurSpringer
- Date d'édition2010
- ISBN 10 1441923942
- ISBN 13 9781441923943
- ReliureBroché
- Langueanglais
- Nombre de pages464
- Coordonnées du fabricantnon disponible
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Bayesian Networks and Decision Graphs
Edité par
Springer New York, 2010
ISBN 10 : 1441923942
ISBN 13 : 9781441923943
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Gives a well-founded practical introduction to Bayesian networksIncludes presentation of the most efficient algorithm for solving influence diagramsThis is a brand new edition of an essential work on Bayesian networks and decision graph. N° de réf. du vendeur 4172910
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Bayesian Networks and Decision Graphs (Information Science and Statistics)
Vendeur : Chiron Media, Wallingford, Royaume-Uni
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Paperback. Etat : New. N° de réf. du vendeur 6666-IUK-9781441923943
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Bayesian Networks and Decision Graphs (Information Science and Statistics)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Etat : New. In. N° de réf. du vendeur ria9781441923943_new
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Bayesian Networks and Decision Graphs
Edité par
Springer New York Nov 2010, 2010
ISBN 10 : 1441923942
ISBN 13 : 9781441923943
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence, detecting conflicts in the evidence entered into the network, determining optimal strategies, analyzing for relevance, and performing sensitivity analysis.The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams. The reader is introduced to the two types of frameworks through examples and exercises, which also instruct the reader on how to build these models. The book is a new edition of Bayesian Networks and Decision Graphs by Finn V. Jensen. The new edition is structured into two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems. The authors also provide a well-founded practical introduction to Bayesian networks, object-oriented Bayesian networks, decision trees, influence diagrams (and variants hereof), and Markov decision processes.give practical advice on the construction of Bayesian networks, decision trees, and influence diagrams from domain knowledge.give several examples and exercises exploiting computer systems for dealing with Bayesian networks and decision graphs.present a thorough introduction to state-of-the-art solution and analysis algorithms.The book is intended as a textbook, but it can also be used for self-study and as a reference book. 464 pp. Englisch. N° de réf. du vendeur 9781441923943
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Bayesian Networks and Decision Graphs
Edité par
Springer New York, Springer New York Nov 2010, 2010
ISBN 10 : 1441923942
ISBN 13 : 9781441923943
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware -Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence, detecting conflicts in the evidence entered into the network, determining optimal strategies, analyzing for relevance, and performing sensitivity analysis.The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams. The reader is introduced to the two types of frameworks through examples and exercises, which also instruct the reader on how to build these models.The book is a new edition of Bayesian Networks and Decision Graphs by Finn V. Jensen. The new edition is structured into two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems. The authors alsoprovide a well-founded practical introduction to Bayesian networks, object-oriented Bayesian networks, decision trees, influence diagrams (and variants hereof), and Markov decision processes.give practical advice on the construction of Bayesian networks, decision trees, and influence diagrams from domain knowledge.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 464 pp. Englisch. N° de réf. du vendeur 9781441923943
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Bayesian Networks and Decision Graphs
Edité par
Springer New York, Springer New York, 2010
ISBN 10 : 1441923942
ISBN 13 : 9781441923943
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence, detecting conflicts in the evidence entered into the network, determining optimal strategies, analyzing for relevance, and performing sensitivity analysis.The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams. The reader is introduced to the two types of frameworks through examples and exercises, which also instruct the reader on how to build these models. The book is a new edition of Bayesian Networks and Decision Graphs by Finn V. Jensen. The new edition is structured into two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems. The authors also provide a well-founded practical introduction to Bayesian networks, object-oriented Bayesian networks, decision trees, influence diagrams (and variants hereof), and Markov decision processes.give practical advice on the construction of Bayesian networks, decision trees, and influence diagrams from domain knowledge.give several examples and exercises exploiting computer systems for dealing with Bayesian networks and decision graphs.present a thorough introduction to state-of-the-art solution and analysis algorithms.The book is intended as a textbook, but it can also be used for self-study and as a reference book. N° de réf. du vendeur 9781441923943
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Bayesian Networks and Decision Graphs
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Etat : New. N° de réf. du vendeur 11864898-n
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Bayesian Networks and Decision Graphs
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Etat : New. N° de réf. du vendeur 11864898-n
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Bayesian Networks and Decision Graphs
Edité par
Springer-Verlag New York Inc., 2010
ISBN 10 : 1441923942
ISBN 13 : 9781441923943
Neuf
Paperback / softback
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Bayesian Networks and Decision Graphs
Vendeur : Books Puddle, New York, NY, Etats-Unis
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