ISBN: 9780470722107 - graphical models: representations for learning, reasoning and data mining (wiley series in computational statistics) (3 Ergebnisse)

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  • Sprache: Englisch

    Verlag: John Wiley & Sons, 2009

    047072210X / 9780470722107

    • Hardcover

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    Gebunden. Zustand: New. The use of graphical models in applied statistics has increased considerably in recent years. At the same time the field of data mining has developed as a response to the large amounts of available data. This book addresses the overlap between these two imp.

  • Sprache: Englisch

    Verlag: John Wiley & Sons Inc, 2009

    047072210X / 9780470722107

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    Anbieter: Kennys Bookstore, Olney, MD, USAKennys Bookstore

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    Zustand: New. 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. . 2009. 2nd Revised edition. Hardcover. . . . . Books ship from the US and Ireland.…

  • Sprache: Englisch

    Verlag: Wiley Sep 2009, 2009

    047072210X / 9780470722107

    • Hardcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Buch. Zustand: Neu. Neuware - 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.…