The nature of statistical learning theory
著者
書誌事項
The nature of statistical learning theory
（Statistics for engineering and information science）
Springer, c2000
2nd ed
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注記
Includes bibliographical references (p. [301]-309) and index
内容説明・目次
内容説明
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.
目次
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
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