Bayesian Networks: An Introduction - Rilegato

Koski, Timo; Noble, John

 
9780470743041: Bayesian Networks: An Introduction
Rilegato
ISBN 10: 0470743042 ISBN 13: 9780470743041
Casa editrice: John Wiley & Sons Inc, 2009

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

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.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
John Wiley & Sons Inc
Data di pubblicazione
2009
Lingua
Inglese
ISBN 10 
0470743042
ISBN 13 
9780470743041
Rilegatura
Copertina rigida
Numero di pagine
347
Contatto del produttore
non disponibile
Persona responsabile
non disponibile