A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)

Devroye, Luc; Györfi, Laszlo; Lugosi, Gabor

ISBN 10: 0387946187 / ISBN 13: 9780387946184

Published by Springer, 1996

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Bibliographic Details

Title: A Probabilistic Theory of Pattern ...

Publisher: Springer

Publication Date: 1996

Binding: hardcover

Condition: New

About this title

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.

From the Back Cover:

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, tree 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.