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A Probabilistic Theory of Pattern Recognition
Luc DevroyeLaszlo GyörfiGabor Lugosi
出版Springer Science & Business Media, 2013-11-27
主題Mathematics / Probability & Statistics / GeneralComputers / Artificial Intelligence / Computer Vision & Pattern RecognitionMathematics / Probability & Statistics / Stochastic ProcessesComputers / Optical Data Processing
ISBN14612071189781461207115
URLhttp://books.google.com.hk/books?id=Y5bxBwAAQBAJ&hl=&source=gbs_api
EBookSAMPLE
註釋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.