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