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

4,13 valoración promedio
( 15 valoraciones por GoodReads )
 
9780387987804: The Nature of Statistical Learning Theory (Information Science and Statistics)
Review:

From the reviews of the second edition:

ZENTRALBLATT MATH

"...written in a concise style. It must be recommended to scientists of statistics, mathematics, physics, and computer science."

SHORT BOOK REVIEWS

"This interesting book helps a reader to understand the interconnections between various streams in the empirical modeling realm and may be recommended to any reader who feels lost in modern terminology, such as artificial intelligence, neural networks, machine learning etcetera."

"The book by Vapnik focuses on how to estimate a function of parameters from empirical data … . The book is concisely written and is intended to be useful to statisticians, computer scientists, mathematicians, and physicists. … This book is very well written at a very high level of abstract thinking and comprehension. The references are up-to-date." (Ramalingam Shanmugam, Journal of Statistical Computation and Simulation, Vol. 75 (2), February, 2005)

"The aim of the book is to introduce a wide range of readers to the fundamental ideas of statistical learning theory. … Each chapter is supplemented by ‘Reasoning and Comments’ which describe the relations between classical research in mathematical statistics and research in learning theory. … The book is well suited to promote the ideas of statistical learning theory and can be warmly recommended to all who are interested in computer learning problems." (S. Vogel, Metrika, June, 2002)

From the Publisher:

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.

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1.

Vapnik, Vladimir
Editorial: Springer
ISBN 10: 0387987800 ISBN 13: 9780387987804
Nuevos Tapa dura Cantidad: 15
Edición internacional
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Bookish
(Erlanger, KY, Estados Unidos de America)
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Descripción Springer. Hardcover. Estado de conservación: New. 0387987800 International Edition Paperback OR Softcover Edition with Same Contents. Fast Delivery. Book Cover and ISBN may be different from the US Edition. Customer satisfaction guaranteed. Nº de ref. de la librería INDMKT-9788132202592

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2.

Vapnik, Vladimir
Editorial: Springer-Verlag New York Inc., United States (2000)
ISBN 10: 0387987800 ISBN 13: 9780387987804
Nuevos Tapa dura Cantidad: 1
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The Book Depository
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Descripción Springer-Verlag New York Inc., United States, 2000. Hardback. Estado de conservación: New. 2nd ed. 2000. 236 x 162 mm. Language: English . Brand New Book. 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. Nº de ref. de la librería AAZ9780387987804

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3.

Vapnik, Vladimir
Editorial: Springer-Verlag New York Inc. 1999-11-19, New York, NY (1999)
ISBN 10: 0387987800 ISBN 13: 9780387987804
Nuevos Tapa dura Cantidad: > 20
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Blackwell's
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Descripción Springer-Verlag New York Inc. 1999-11-19, New York, NY, 1999. hardback. Estado de conservación: New. Nº de ref. de la librería 9780387987804

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4.

Vapnik, Vladimir
Editorial: Springer-Verlag New York Inc., United States (2000)
ISBN 10: 0387987800 ISBN 13: 9780387987804
Nuevos Tapa dura Cantidad: 1
Librería
The Book Depository US
(London, Reino Unido)
Valoración
[?]

Descripción Springer-Verlag New York Inc., United States, 2000. Hardback. Estado de conservación: New. 2nd ed. 2000. 236 x 162 mm. Language: English . Brand New Book. 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. Nº de ref. de la librería AAZ9780387987804

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5.

Vapnik, Vladimir
Editorial: Springer-Verlag New York Inc. (1999)
ISBN 10: 0387987800 ISBN 13: 9780387987804
Nuevos Cantidad: 1
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Books2Anywhere
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Descripción Springer-Verlag New York Inc., 1999. HRD. Estado de conservación: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. de la librería GB-9780387987804

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Vapnik, Vladimir
Editorial: Springer-Verlag New York Inc.
ISBN 10: 0387987800 ISBN 13: 9780387987804
Nuevos Tapa dura Cantidad: 1
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THE SAINT BOOKSTORE
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Descripción Springer-Verlag New York Inc. Hardback. Estado de conservación: new. BRAND NEW, The Nature of Statistical Learning Theory (2nd ed. 2000), Vladimir Vapnik, 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. Nº de ref. de la librería B9780387987804

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7.

Vapnik, Vladimir
Editorial: Springer (1999)
ISBN 10: 0387987800 ISBN 13: 9780387987804
Nuevos Tapa dura Cantidad: 1
Librería
Valoración
[?]

Descripción Springer, 1999. Estado de conservación: New. Discusses the fundamental ideas which lie behind the statistical theory of learning and generalization. This book considers learning as a general problem of function estimation based on empirical data. It concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. Series: Information Science and Statistics. Num Pages: 314 pages, biography. BIC Classification: PBT; UYAM; UYQM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 243 x 163 x 27. Weight in Grams: 658. . 1999. 2nd. Hardcover. . . . . . Nº de ref. de la librería V9780387987804

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Vapnik, Vladimir
Editorial: Springer (1999)
ISBN 10: 0387987800 ISBN 13: 9780387987804
Nuevos Tapa dura Cantidad: 1
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Green Books
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Descripción Springer, 1999. Hardcover. Estado de conservación: New. Brand New Book. Shipping: Once your order has been confirmed and payment received, your order will then be processed. The book will be located by our staff, packaged and despatched to you as quickly as possible. From time to time, items get mislaid en route. If your item fails to arrive, please contact us first. We will endeavour to trace the item for you and where necessary, replace or refund the item. Please do not leave negative feedback without contacting us first. All orders will be dispatched within two working days. If you have any quesions please contact us. Nº de ref. de la librería V9780387987804

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Vapnik, Vladimir
ISBN 10: 0387987800 ISBN 13: 9780387987804
Nuevos Tapa dura Cantidad: 1
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Ria Christie Collections
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Descripción Hardback. Estado de conservación: New. Not Signed; 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. book. Nº de ref. de la librería ria9780387987804_rkm

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Vapnik, Vladimir
Editorial: Springer
ISBN 10: 0387987800 ISBN 13: 9780387987804
Nuevos Tapa dura Cantidad: 1
Librería
Kennys Bookstore
(Olney, MD, Estados Unidos de America)
Valoración
[?]

Descripción Springer. Estado de conservación: New. Discusses the fundamental ideas which lie behind the statistical theory of learning and generalization. This book considers learning as a general problem of function estimation based on empirical data. It concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. Series: Information Science and Statistics. Num Pages: 314 pages, biography. BIC Classification: PBT; UYAM; UYQM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 243 x 163 x 27. Weight in Grams: 658. . 1999. 2nd. Hardcover. . . . . Books ship from the US and Ireland. Nº de ref. de la librería V9780387987804

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