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Die Natur der statistischen Lerntheorie - 9781441931603 - Vladimir Vapnik
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Die Natur der statistischen Lerntheorie - 9781441931603 - Livro de bolso

ISBN: 9781441931603

ISBN-13: 9781441931603, 978-1441931603. It considers learning as a general problem of function estimation based on empirical data. Written in a readable and concise style, the book is int… mais…

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The Nature of Statistical Learning Theory - Vladimir Vapnik
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Vladimir Vapnik:

The Nature of Statistical Learning Theory - Livro de bolso

2010, ISBN: 1441931600

[EAN: 9781441931603], Neubuch, [PU: Springer New York], CONDITIONALPROBABILITY STATISTICALSTATISTICALTHEORY COGNITION CONTROL PATTERNRECOGNITION STATISTICS NATURWISSENSCHAFTEN ALLGEMEIN C… mais…

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The Nature of Statistical Learning Theory (Information Science and Statistics) - Vapnik, Vladimir N.
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Vapnik, Vladimir N.:
The Nature of Statistical Learning Theory (Information Science and Statistics) - Livro de bolso

1999

ISBN: 9781441931603

Springer New York, Taschenbuch, Auflage: Softcover reprint of hardcover 2nd ed. 2000, 336 Seiten, Publiziert: 1999-11-19T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: 48 black & white i… mais…

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The Nature of Statistical Learning Theory - novo libro

ISBN: 9781441931603

Find The Nature of Statistical Learning Theory by Vladimir Vapnik in Paperback and other formats in Mathematics > Probability & Statistics - General. Media > Books new, Springer

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The Nature of Statistical Learning Theory (Information Science and Statistics) - Vapnik, Vladimir
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Vapnik, Vladimir:
The Nature of Statistical Learning Theory (Information Science and Statistics) - Livro de bolso

2010, ISBN: 1441931600

[EAN: 9781441931603], Gebraucht, wie neu, [PU: Springer], Like New, Books

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The Nature of Statistical Learning Theory (Information Science and Statistics)
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Número ISBN:

1441931600


The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.

Dados detalhados do livro - The Nature of Statistical Learning Theory (Information Science and Statistics)


EAN (ISBN-13): 9781441931603
ISBN (ISBN-10): 1441931600
Livro de capa dura
Livro de bolso
Ano de publicação: 2010
Editor/Editora: Springer New York
336 Páginas
Peso: 0,509 kg
Língua: eng/Englisch

Livro na base de dados desde 2010-07-16T14:06:08+01:00 (Lisbon)
Página de detalhes modificada pela última vez em 2023-06-11T11:32:56+01:00 (Lisbon)
Número ISBN/EAN: 1441931600

Número ISBN - Ortografia alternativa:
1-4419-3160-0, 978-1-4419-3160-3
Ortografia alternativa e termos de pesquisa relacionados:
Autor do livro: vapnik
Título do livro: the nature statistical learning theory, information theory and statistics, theories nature

Dados da editora

Autor: Vladimir Vapnik
Título: Information Science and Statistics; The Nature of Statistical Learning Theory
Editora: Springer; Springer US
314 Páginas
Ano de publicação: 2010-12-01
New York; NY; US
Impresso / Feito em
Língua: Inglês
241,99 € (DE)

BC; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Conditional probability; Statistical Learning; Statistical Theory; cognition; control; learning; pattern recognition; statistics; Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Artificial Intelligence; Künstliche Intelligenz; BC; BB; EA

Introduction: Four Periods in the Research of the Learning Problem.- 1 Setting of the Learning Problem.- 2 Consistency of Learning Processes.- 3 Bounds on the Rate of Convergence of Learning Processes.- 4 Controlling the Generalization Ability of Learning Processes.- 5 Methods of Pattern Recognition.- 6 Methods of Function Estimation.- 7 Direct Methods in Statistical Learning Theory.- 8 The Vicinal Risk Minimization Principle and the SVMs.- 9 Conclusion: What Is Important in Learning Theory?.- References.- Remarks on References.- References.
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