THE NATURE OF STATISTICAL LEARNING THEORY - Couverture rigide

Vapnik, Vladimir-N

Couverture rigide

ISBN 10 : 0387945598 ISBN 13 : 9780387945590

Editeur : Springer-Verlag New York Inc., 2000

Synopsis

The aim of this text 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 connection 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; an 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; princples for controlling the generalization ability of learning machines using small sample sizes; and introducing a new type of universal learning machine that controls the generalization ability.

Détails de l'édition

• Éditeur: Springer-Verlag New York Inc.
• Date d'édition: 2000
• Langue: anglais
• ISBN 10: 0387945598
• ISBN 13: 9780387945590
• Reliure: Relié
• Numéro d'édition: 2
• Nombre de pages: 208
• Coordonnées du fabricant: non disponible
• Personne responsable: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Allemagne