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Beschreibung
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, mathematicians, physicists, and computer scientists.
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, mathematicians, physicists, and computer scientists.
Zusammenfassung
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, mathematicians, physicists, and computer scientists.
Inhaltsverzeichnis
Informal Reasoning and Comments * Consistency of Learning Processes * Bounds on the Rate of Convergence of Learing Processes * Controlling the Generalization Ability of Learning Processes * Methods of Pattern Recognition * Methods of Function Estimation * Direct Methods in Statistical Learning Theory * The Vicinal Risk Minimization Principle and the SVMs
Details
Erscheinungsjahr: 2010
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Importe, Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Reihe: Information Science and Statistics
Inhalt: xx
314 S.
48 s/w Illustr.
ISBN-13: 9781441931603
ISBN-10: 1441931600
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Vapnik, Vladimir
Auflage: Second Edition 2000
Hersteller: Humana
Springer
Springer US, New York, N.Y.
Information Science and Statistics
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 235 x 155 x 19 mm
Von/Mit: Vladimir Vapnik
Erscheinungsdatum: 01.12.2010
Gewicht: 0,511 kg
Artikel-ID: 107152370