A Probabilistic Theory of Pattern Recognition

By: Luc Devroye, Laszlo Gyorfi, Gabor Lugosi

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Paperback | 22 November 2013

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Paperback
660 Pages

Dimensions(cm)
23.5 x 15.49 x 3.38

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$149.01

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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.

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