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Luc Devroye - A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) - 9780387946184 - V9780387946184
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A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)

€ 154.00
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Description for A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) Hardcover. 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. Series: Stochastic Modelling and Applied Probability. Num Pages: 638 pages, biography. BIC Classification: PBT; PBW; UYQP. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 34. Weight in Grams: 1094.
Pattern recognition presents one of the most significant challenges for scientists and engineers, and many different approaches have been proposed. The aim of this book is to provide a self-contained account of probabilistic analysis of these approaches. The book includes a discussion of distance measures, nonparametric methods based on kernels or nearest neighbors, Vapnik-Chervonenkis theory, epsilon entropy, parametric classification, error estimation, free classifiers, and neural networks. Wherever possible, distribution-free properties and inequalities are derived. A substantial portion of the results or the analysis is new. Over 430 problems and exercises complement the material.

Product Details

Publisher
Springer
Format
Hardback
Publication date
1997
Condition
New
Number of Pages
638
Place of Publication
New York, NY, United States
ISBN
9780387946184
SKU
V9780387946184
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

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