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[null,"1.","Record Nr.",null,"UNINA9910789071903321"]
[null,null,"Autore",null,"Devroye Luc"]
[null,null,"Titolo",null,"A Probabilistic Theory of Pattern Recognition [[electronic resource] /] / by Luc Devroye, Laszlo Györfi, Gabor Lugosi"]
[null,null,"Pubbl/distr/stampa",null,"New York, NY : , : Springer New York : , : Imprint : Springer, , 1996"]
[null,null,"ISBN",null,"1-4612-0711-8"]
[null,null,"Edizione",null,"[1st ed. 1996.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XV, 638 p.)"]
[null,null,"Collana",null,"Stochastic Modelling and Applied Probability, , 0172-4568 ; ; 31"]
[null,null,"Disciplina",null,"519.2"]
[null,null,"Soggetti",null,"Probabilities"]
[{"$nulls":4},"Pattern recognition"]
[{"$nulls":4},"Probability Theory and Stochastic Processes"]
[{"$nulls":4},"Pattern Recognition"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and indexes."]
[null,null,null,"Sommario/riassunto","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."]