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Graphical Models

Graphical Models Representations for Learning, Reasoning and Data Mining

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Wiley Series in Computational Statistics

Graphical Models

Representations for Learning, Reasoning and Data Mining

Christian Borgelt | Matthias Steinbrecher | Rudolf R. Kruse

Mathematics / Probability & Statistics / General

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.

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, Department of Knowledge Processing and Language Engineering, School of Computer Science, Universitätsplatz 2,?Magdeburg, Germany.


Publication Date: 22 September 2009
Publisher: Wiley
Imprint: Wiley
ISBN-13: 9780470722107
Format: Hardback
Page Count: 404
Weight (oz): 25.12

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