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Item Details
Title: A PROBABILISTIC THEORY OF PATTERN RECOGNITION
By: Luc Devroye, Laszlo Gyorfi, Gabor Lugosi
Format: Hardback

List price: £99.99


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ISBN 10: 0387946187
ISBN 13: 9780387946184
Publisher: SPRINGER-VERLAG NEW YORK INC.
Pub. date: 1 June, 1996
Edition: 1st ed. 1996. Corr. 2nd printing 1997
Series: Stochastic Modelling and Applied Probability v. 31
Pages: 638
Description: Offers an account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. This title is suitable for both research workers and graduate students.
Synopsis: A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.
Illustrations: biography
Publication: US
Imprint: Springer-Verlag New York Inc.
Returns: Returnable
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A PROBABILISTIC THEORY OF PATTERN RECOGNITION (PB)
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CHAOS IN CHEMISTRY AND BIOCHEMISTRY (HB)
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LECTURE NOTES ON BUCKET ALGORITHMS (PB)
LECTURES ON THE NEAREST NEIGHBOR METHOD (HB)
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MACHINE LEARNING FOR FINANCIAL ENGINEERING (HB)
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