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PRINT ON DEMAND pp. 340. Codice articolo 18296139
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.
Recensione:
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)
Titolo: The Nature of Statistical Learning Theory
Casa editrice: Springer
Data di pubblicazione: 1999
Legatura: Rilegato
Condizione: New
Edizione: seconda edizione
Da: BooksRun, Philadelphia, PA, U.S.A.
Hardcover. Condizione: Fair. 2nd. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way. Codice articolo 0387987800-7-1
Quantità: 1 disponibili
Da: Phatpocket Limited, Waltham Abbey, HERTS, Regno Unito
Condizione: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. Codice articolo Z1-AA-007-00638
Quantità: 1 disponibili
Da: medimops, Berlin, Germania
Condizione: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages. Codice articolo M00387987800-V
Quantità: 1 disponibili
Da: BennettBooksLtd, Los Angeles, CA, U.S.A.
hardcover. Condizione: New. In shrink wrap. Looks like an interesting title! Codice articolo Q-0387987800
Quantità: 1 disponibili
Da: moluna, Greven, Germania
Condizione: New. The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. Written in readable and concise style and devoted to key learning problems, the book is intended for statisticians, mathematicia. Codice articolo 5913501
Quantità: 2 disponibili
Da: preigu, Osnabrück, Germania
Buch. Condizione: Neu. The Nature of Statistical Learning Theory | V. N. Vapnik | Buch | Information Science and Statistics | xx | Englisch | 1999 | Springer-Verlag GmbH | EAN 9780387987804 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Codice articolo 102588474
Quantità: 1 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 672799-n
Quantità: 1 disponibili
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo DB-9780387987804
Quantità: 2 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In English. Codice articolo ria9780387987804_new
Quantità: Più di 20 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 672799-n
Quantità: 1 disponibili