Bayesian Networks: An Introduction

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9780470743041: Bayesian Networks: An Introduction

Book by Noble John Koski Timo

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Quatrième de couverture :

Bayesian Networks: An Introduction provides a self–containedintroduction to the theory and applications of Bayesian networks, atopic of interest and importance for statisticians, computerscientists and those involved in modelling complex data sets. Thematerial has been extensively tested in classroom teaching andassumes a basic knowledge of probability, statistics andmathematics. All notions are carefully explained and featureexercises throughout.

Features include:

  • An introduction to Dirichlet Distribution, Exponential Familiesand their applications.
  • A detailed description of learning algorithms and ConditionalGaussian Distributions using Junction Tree methods.
  • A discussion of Pearl′s intervention calculus, with anintroduction to the notion of see and do conditioning.
  • All concepts are clearly defined and illustrated with examplesand exercises. Solutions are provided online.

This book will prove a valuable resource for postgraduatestudents of statistics, computer engineering, mathematics, datamining, artificial intelligence, and biology.
Researchers and users of comparable modelling or statisticaltechniques such as neural networks will also find this book ofinterest.

Revue de presse :

"It assumes only a basic knowledge of probability, statistics andmathematics and is well suited for classroom teaching . . . Eachchapter of the book is concluded with short notes on the literatureand a set of helpful exercises." (Mathematical Reviews, 2011)

"Extensively tested in classroom teaching .The authorsclearly define all concepts and provide numerous examples andexercises." (Book News, December 2009)

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Koski, Timo;Noble, John
Edité par Somerset, New Jersey, U.S.A.: John Wiley & Sons Inc (2009)
ISBN 10 : 0470743042 ISBN 13 : 9780470743041
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Timo Koski, John Noble
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ISBN 10 : 0470743042 ISBN 13 : 9780470743041
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Description du livre John Wiley and Sons Ltd, United States, 2009. Hardback. État : New. 1. Auflage. 250 x 170 mm. Language: English . Brand New Book. Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications. A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. A discussion of Pearl s intervention calculus, with an introduction to the notion of see and do conditioning. All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest. N° de réf. du libraire AAH9780470743041

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Timo Koski, John Noble
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Description du livre John Wiley and Sons Ltd, United States, 2009. Hardback. État : New. 1. Auflage. 250 x 170 mm. Language: English . Brand New Book. Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications. A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. A discussion of Pearl s intervention calculus, with an introduction to the notion of see and do conditioning. All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest. N° de réf. du libraire AAH9780470743041

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Koski, Timo; Noble, John
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Description du livre John Wiley and Sons Ltd, 2009. État : New. Bayesian networks have found application in a number of fields, including risk analysis, consumer help desks, tissue pathology, pattern recognition, credit assessment, computer network diagnosis, and artificial intelligence. Bayesian Networks is a self-contained introduction to the theory and applications of Bayesian networks. Series: Wiley Series in Probability and Statistics. Num Pages: 366 pages, Illustrations. BIC Classification: PBT. Category: (U) Tertiary Education (US: College); (UU) Undergraduate. Dimension: 253 x 176 x 26. Weight in Grams: 788. . 2009. 1st Edition. Hardcover. . . . . . N° de réf. du libraire V9780470743041

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Description du livre 2009. Hardcover. État : New. 1st. 169mm x 251mm x 25mm. Hardcover. Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, comput.Shipping may be from multiple locations in the US or from the UK, depending on stock availability. 366 pages. 0.816. N° de réf. du libraire 9780470743041

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Description du livre John Wiley and Sons Ltd. État : New. Bayesian networks have found application in a number of fields, including risk analysis, consumer help desks, tissue pathology, pattern recognition, credit assessment, computer network diagnosis, and artificial intelligence. Bayesian Networks is a self-contained introduction to the theory and applications of Bayesian networks. Series: Wiley Series in Probability and Statistics. Num Pages: 366 pages, Illustrations. BIC Classification: PBT. Category: (U) Tertiary Education (US: College); (UU) Undergraduate. Dimension: 253 x 176 x 26. Weight in Grams: 788. . 2009. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. N° de réf. du libraire V9780470743041

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