A Probabilistic Theory of Pattern Recognition

A Probabilistic Theory of Pattern Recognition

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Pattern recognition presents one of the most significant challenges for scientists and engineers and many different approaches have been proposed and developed. The aim of this book is to provide a self-contained and coherent account of probabilistic techniques which have been applied to the subject. Among the topics covered are: distance measures; kernel rules; nearest neighbor rules; Vapnik-Chervonenkis theory; parametric classification; and feature extraction. Each chapter concludes with problems and exercises.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

Title:A Probabilistic Theory of Pattern Recognition
Author:Luc Devroye, László Györfi, Gabor Lugosi
Publisher:Springer Science & Business Media - 1996-04-04


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