Graphical Models: Representations for Learning, Reasoning and Data Mining, 2nd Edition

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Graphical Models: Representations for Learning, Reasoning and Data Mining, 2nd Edition

Christian Borgelt,Matthias Steinbrecher,Rudolf R. Kruse

Available on Wiley Online Library

Description

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.

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

Series

Wiley Series in Computational Statistics

To Purchase this product, please visit

https://dev.store.wiley.com/en-us/Graphical+Models%3A+Representations+for+Learning%2C+Reasoning+and+Data+Mining%2C+2nd+Edition-p-9780470722107