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A Probabilistic Theory of Pattern Recognition PDF

654 Pages·1996·10.782 MB·English
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by Luc Devroye, László Györfi, Gábor Lugosi (auth.)| 1996| 654 pages| 10.782| English

About A Probabilistic Theory of Pattern Recognition

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.

Detailed Information

Author:Luc Devroye, László Györfi, Gábor Lugosi (auth.)
Publication Year:1996
ISBN:9780387946184
Pages:654
Language:English
File Size:10.782
Format:PDF
Price:FREE
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