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.

Graphical Models: Representations for Learning, Reasoning and Data Mining

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£97.95

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Hardback by Christian Borgelt , Matthias Steinbrecher

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Graphical models are of increasing importance in applied statistics, and in particular in data mining. Providing a self-contained introduction and... Read more

    Publisher: John Wiley & Sons Inc
    Publication Date: 07/08/2009
    ISBN13: 9780470722107, 978-0470722107
    ISBN10: 047072210X

    Number of Pages: 404

    Non Fiction , Mathematics & Science , Education

    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.

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