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Item Details
| Title:
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STATISTICAL LEARNING THEORY
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| By: |
Vladimir N. Vapnik |
| Format: |
Hardback |
| List price:
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£194.95 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
0471030031 |
| ISBN 13: |
9780471030034 |
| Publisher: |
JOHN WILEY AND SONS LTD |
| Pub. date: |
12 October, 1998 |
| Series: |
Adaptive and Learning Systems for Signal Processing, Communications and |
| Pages: |
768 |
| Description: |
This book is devoted to the statistical theory of learning and generalization, that is, the problem of choosing the desired function on the basis of empirical data. The author will present the whole picture of learning and generalization theory. Learning theory has applications in many fields, such as psychology, education and computer science. |
| Synopsis: |
A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a variety of computer science and robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more. |
| Illustrations: |
Illustrations |
| Publication: |
US |
| Imprint: |
John Wiley & Sons Inc |
| Returns: |
Returnable |
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