Graphical Models

Methods for Data Analysis and Mining

Christian Borgelt, Rudolf Kruse

358 pages, parution le 15/02/2002

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Résumé

The concept of modelling using graph theory has its origin in several scientific areas, notably statistics, physics, genetics, and engineering. The use of graphical models in applied statistics has increased considerably over recent years and the theory has been greatly developed and extended. This book provides a self-contained introduction to the learning of graphical models from data, and is the first to include detailed coverage of possibilistic networks - a relatively new reasoning tool that allows the user to infer results from problems with imprecise data. One major advantage of graphical modelling is that specialised techniques that have been developed in one field can be transferred into others easily. The methods described here are applied in a number of industries, including a recent quality testing programme at a major car manufacturer.

Provides a self-contained introduction to learning relational, probabilistic and possibilistic networks from data
Each concept is carefully explained and illustrated by examples
Contains all necessary background, including modeling under uncertainty, decomposition of distributions, and graphical representation of decompositions
Features applications of learning graphical models from data, and problems for further research
Includes a comprehensive bibliography

An essential reference for graduate students of graphical modelling, applied statistics, computer science and engineering, as well as researchers and practitioners who use graphical models in their work.

Contents

Preface

Introduction
Imprecision and Uncertainty
Decomposition
Graphical Representation
Computing Projections
Naive Classifiers
Learning Global Structure
Learning Local Structure
Inductive Causation
Applications

A. Proofs of Theorems
B. Software Tools

Bibliography
Index

Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Christian Borgelt, Rudolf Kruse
Parution	15/02/2002
Nb. de pages	358
Format	15,5 x 23,8
Couverture	Broché
Poids	709g
Intérieur	Noir et Blanc
EAN13	9780470843376
ISBN13	978-0-470-84337-6