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Graphical Models: Representations for Learning, Reasoning and Data Mining, Second Edition
John Wiley and Sons Ltd, Aug 2009, Pages: 404
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.
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