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Bayesian Networks: An Introduction
Timo Koski
€ 100.17
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Description for Bayesian Networks: An Introduction
Hardcover. 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.
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.
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 ... Read more
- 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.
Show LessProduct Details
Publisher
John Wiley & Sons Inc United Kingdom
Number of pages
366
Format
Hardback
Publication date
2009
Series
Wiley Series in Probability and Statistics
Condition
New
Weight
788g
Number of Pages
368
Place of Publication
New York, United States
ISBN
9780470743041
SKU
V9780470743041
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50
About Timo Koski
Timo Koski, Professor of Mathematical Statistics, Department of Mathematics, Royal Institute of Technology, Stockholm, Sweden. John M. Noble, Department of Mathematics, University of Linköping, Sweden.
Reviews for Bayesian Networks: An Introduction
"It assumes only a basic knowledge of probability, statistics and mathematics and is well suited for classroom teaching . . . Each chapter of the book is concluded with short notes on the literature and a set of helpful exercises." (Mathematical Reviews, 2011) "Extensively tested in classroom teaching … .The authors clearly define all concepts ... Read more