Printer Friendly

Research and Markets: Graphical Models: Representations for Learning, Reasoning and Data Mining, Second Edition Provides a Self-Contained Introduction.

DUBLIN -- Research and Markets (http://www.researchandmarkets.com/research/269a91/graphical_models) has announced the addition of John Wiley and Sons Ltd's new report "Graphical Models: Representations for Learning, Reasoning and Data Mining, Second Edition" to their offering.

Graphical models are of increasing importance in applied statistics, and in particular in data mining. Providing a self-contained introduction and overview to learning relational, probabilistic, and possibilistic networks from data, this second edition of Graphical Models is thoroughly updated to include the latest research in this burgeoning field, including a new chapter on visualization. The text provides graduate students, and researchers with all the necessary background material, including modelling under uncertainty, decomposition of distributions, graphical representation of distributions, and applications relating to graphical models and problems for further research.

This book provides a self-contained introduction into learning relational, probabilistic, and possibilistic networks from data. All basic concepts are carefully explained and illustrated by examples throughout. Contains all necessary background material, including modelling under uncertainty, decomposition of distributions, and graphical representation of distributions as well as applications relating to graphical models and problems for further research. This second edition will feature more extensive coverage of clique tree propagation, visualization techniques and exercises for the reader, the book will also be supported by a website containing additional material.

Key Topics Covered:

* Preface

* 1 Introduction

* 2 Imprecision and Uncertainty

* 3 Decomposition

* 4 Graphical Representation

* 5 Computing Projections

* 6 Naive Classifiers

* 7 Learning Global Structure

* 8 Learning Local Structure

* 9 Inductive Causation

* 10 Visualization

* 11 Applications

* A Proofs of Theorems

* B Software Tools

* Bibliography

* Index

Author:

Christian Borgelt, is the Principal researcher at the European Centre for Soft Computing at Otto-von-Guericke University of Magdeburg Rudolf Kruse, Professor for Computer Science at Otto-von-Guericke University of Magdeburg Matthias Steinbrecher, Dept. of Knowledge Processing and Language Engineering, School of Computer Science, Universitatsplatz 2, Magdeburg, Germany

For more information visit http://www.researchandmarkets.com/research/269a91/graphical_models
COPYRIGHT 2009 Business Wire
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2009 Gale, Cengage Learning. All rights reserved.

 
Article Details
Printer friendly Cite/link Email Feedback
Publication:Business Wire
Article Type:Report
Date:Oct 14, 2009
Words:318
Previous Article:Photo District News and Kodak Launch Animal Photo Contest to Benefit Animal Welfare Groups.
Next Article:A.M. Best to Sponsor PCI's 2009 Annual Meeting in Orlando.
Topics:


Related Articles
Data mining and customer relationship marketing in the banking industry.
Applying and evaluating models to predict customer attrition using data mining techniques.
An introduction to Latent Variable Growth Curve Modeling: Concepts, Issues, and Applications, 2d ed. .
Discovering hidden knowledge from biomedical literature.
The handbook of statistical analysis & data mining applications.
Extracting co-expression relations between genes using Grammatical parsing.
Graphical models; representations for learning, reasoning and data mining, 2d ed.

Terms of use | Privacy policy | Copyright © 2018 Farlex, Inc. | Feedback | For webmasters