The Nature of Statistical Learning Theory - Hardcover

Vapnik, Vladimir N.

Hardcover

ISBN 10: 0387945598 ISBN 13: 9780387945590

Publisher: Springer, 1999

Synopsis

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning from the general point of view 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 general setting of learning problems and the general model of minimizing the risk functional from empirical data - a comprehensive analysis of the empirical risk minimization principle and shows how this allows for the construction of necessary and sufficient conditions for 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 - introducing a new type of universal learning machine that controls the generalization ability.

About this title

Review:

"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." V.V. Fedorov, Oak Ridge National Laboratory, USA

About this edition

• Publisher: Springer
• Publication date: 1999
• ISBN 10: 0387945598
• ISBN 13: 9780387945590
• Binding: Hardcover
• Edition number: 1
• Number of pages: 188