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Graphical Models: Representations for Learning, Reasoning and Data Mining
Christian Borgelt
€ 127.13
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Description for Graphical Models: Representations for Learning, Reasoning and Data Mining
Hardcover. Provides a self-contained introduction to learning relational, probabilistic and possibilistic networks from data All basic concepts carefully explained and illustrated by examples throughout Contains background material including graphical representation, including Markov and Bayesian Networks. Includes a comprehensive bibliography. Series: Wiley Series in Computational Statistics. Num Pages: 404 pages, Illustrations. BIC Classification: PBT; TJ; UNF. Category: (P) Professional & Vocational. Dimension: 240 x 160 x 27. Weight in Grams: 718.
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.
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.
Product Details
Publisher
John Wiley & Sons Inc United Kingdom
Number of pages
404
Format
Hardback
Publication date
2009
Series
Wiley Series in Computational Statistics
Condition
New
Weight
718 g
Number of Pages
404
Place of Publication
New York, United States
ISBN
9780470722107
SKU
V9780470722107
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-1
About Christian Borgelt
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.
Reviews for Graphical Models: Representations for Learning, Reasoning and Data Mining
“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.” (Zentralblatt Math, 1 August 2013) "All of the necessary background is provided, with material on modeling under uncertainty and imprecision modeling, decomposition of ... Read more