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In den WarenkorbPaperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
Verlag: Springer-Verlag New York Inc., 2000
ISBN 10: 0387945598 ISBN 13: 9780387945590
Sprache: Englisch
Anbieter: Ammareal, Morangis, Frankreich
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In den WarenkorbHardcover. Zustand: Bon. Ancien livre de bibliothèque avec équipements. Edition 2000. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Edition 2000. Ammareal gives back up to 15% of this item's net price to charity organizations.
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In den WarenkorbZustand: Acceptable. The book is 100% readable but visibly worn, and damaged. This may include stains, tears, rips, folded pages, binding damage, dents, scuffs, scratches and sticker residue. The book also may contain heavy highlighting and notes. Please ask for photos as our books are donations and may not contain above mentioned defects. There is a signature or handwriting on the inside front cover.
Anbieter: BooksRun, Philadelphia, PA, USA
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In den WarenkorbHardcover. Zustand: 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.
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In den WarenkorbZustand: 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.
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
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In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. In.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. In English.
Verlag: Springer New York, Springer US, 2010
ISBN 10: 1441931600 ISBN 13: 9781441931603
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. These include: \* the setting of learning problems based on the model of minimizing the risk functional from empirical data \* a comprehensive analysis of the empirical risk minimization principle including necessary and sufficient conditions for its consistency \* non-asymptotic bounds for the risk achieved using the empirical risk minimization principle \* principles for controlling the generalization ability of learning machines using small sample sizes based on these bounds \* the Support Vector methods that control the generalization ability when estimating function using small sample size. The second edition of the book contains three new chapters devoted to further development of the learning theory and SVM techniques. These include: \* the theory of direct method of learning based on solving multidimensional integral equations for density, conditional probability, and conditional density estimation \* a new inductive principle of learning. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists. Vladimir N. Vapnik is Technology Leader AT&T Labs-Research and Professor of London University. He is one of the founders of.
Anbieter: Kennys Bookstore, Olney, MD, USA
EUR 404,14
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In den WarenkorbZustand: 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.