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:
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Etat : 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 vendeur V9780470743041
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