E-Book, Englisch, 314 Seiten, eBook
Vapnik The Nature of Statistical Learning Theory
2. Auflage 2000
ISBN: 978-1-4757-3264-1
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 314 Seiten, eBook
Reihe: Information Science and Statistics
ISBN: 978-1-4757-3264-1
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
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.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
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
