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＜電子ブック＞
A Probabilistic Theory of Pattern Recognition / by Luc Devroye, Laszlo Györfi, Gabor Lugosi
(Stochastic Modelling and Applied Probability. ISSN:2197439X ; 31)

版	1st ed. 1996.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	1996
本文言語	英語
大きさ	XV, 638 p : online resource
著者標目	*Devroye, Luc author Györfi, Laszlo author Lugosi, Gabor author SpringerLink (Online service)
件　名	LCSH:Probabilities LCSH:Pattern recognition systems FREE:Probability Theory FREE:Automated Pattern Recognition
一般注記	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 HTTP:URL=https://doi.org/10.1007/978-1-4612-0711-5

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