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Item Details
| Title:
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GRAPHICAL MODELS
REPRESENTATIONS FOR LEARNING, REASONING AND DATA MINING |
| By: |
Christian Borgelt, Rudolf R. Kruse, Matthias Steinbrecher |
| Format: |
Hardback |
| List price:
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£97.95 |
| Our price: |
£88.16 |
| Discount: |
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| You save:
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£9.79 |
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| ISBN 10: |
047072210X |
| ISBN 13: |
9780470722107 |
| Availability: |
Usually dispatched within 1-3 weeks.
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| Stock: |
Currently 0 available |
| Publisher: |
JOHN WILEY AND SONS LTD |
| Pub. date: |
7 August, 2009 |
| Edition: |
2nd Revised edition |
| Series: |
Wiley Series in Computational Statistics |
| Pages: |
404 |
| Description: |
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. |
| Synopsis: |
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. |
| Illustrations: |
Illustrations |
| Publication: |
US |
| Imprint: |
Wiley-Blackwell |
| Returns: |
Returnable |
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