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AuthorDevroye, Luc. author
TitleA Probabilistic Theory of Pattern Recognition [electronic resource] / by Luc Devroye, Lรกszlรณ Gyรถrfi, Gรกbor Lugosi
ImprintNew York, NY : Springer New York : Imprint: Springer, 1996
Connect tohttp://dx.doi.org/10.1007/978-1-4612-0711-5
Descript XV, 638 p. online resource

SUMMARY

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


Mathematics Pattern recognition Probabilities Mathematics Probability Theory and Stochastic Processes Pattern Recognition



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