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Bayesian Networks

An Introduction

Timo Koski, John Noble

EPUB
80,99
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John Wiley & Sons img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik

Description

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.

Reviews

(Mathematical Reviews, 2011)
"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."
(Book News, December 2009)
"Extensively tested in classroom teaching ... .The authors clearly define all concepts and provide numerous examples and exercises."
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Keywords

Computer Science, Bayessches Verfahren, Informatik, Rechnergestützte u. graphische Statistik, Applied Probability & Statistics, Bayes-Verfahren, Populäre Themen i. d. Informatik, Statistik, Computational & Graphical Statistics, Computer Science - General Interest, Angewandte Wahrscheinlichkeitsrechnung u. Statistik, Bayessche Netzwerke, Statistics, Bayesian Analysis