The Nature of Statistical Learning Theory (inbunden)
Format
Inbunden (Hardback)
Språk
Engelska
Antal sidor
314
Utgivningsdatum
1999-11-01
Upplaga
2nd ed. 2000
Förlag
Springer-Verlag New York Inc.
Illustratör/Fotograf
50 Abb
Illustrationer
XX, 314 p.
Dimensioner
242 x 162 x 25 mm
Vikt
600 g
Antal komponenter
1
Komponenter
52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam
ISBN
9780387987804

The Nature of Statistical Learning Theory

Inbunden, Engelska, 1999-11-01
1355 kr
Skickas inom 2-5 vardagar.
Fri frakt inom Sverige för privatpersoner.
Finns även som
Visa alla 3 format & utgåvor
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.
Visa hela texten

Passar bra ihop

  1. The Nature of Statistical Learning Theory
  2. +
  3. Estimation of Dependences Based on Empirical Data

De som köpt den här boken har ofta också köpt Estimation of Dependences Based on Empirical Data av Vladimir Vapnik (häftad).

Köp båda 2 för 3506 kr

Kundrecensioner

Har du läst boken? Sätt ditt betyg »

Fler böcker av Vladimir Vapnik

Recensioner i media

From the reviews of the second edition: ZENTRALBLATT MATH "...written in a concise style. It must be recommended to scientists of statistics, mathematics, physics, and computer science." SHORT BOOK REVIEWS "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, such as artificial intelligence, neural networks, machine learning etcetera." "The book by Vapnik focuses on how to estimate a function of parameters from empirical data ... . The book is concisely written and is intended to be useful to statisticians, computer scientists, mathematicians, and physicists. ... This book is very well written at a very high level of abstract thinking and comprehension. The references are up-to-date." (Ramalingam Shanmugam, Journal of Statistical Computation and Simulation, Vol. 75 (2), February, 2005) "The aim of the book is to introduce a wide range of readers to the fundamental ideas of statistical learning theory. ... Each chapter is supplemented by `Reasoning and Comments' which describe the relations between classical research in mathematical statistics and research in learning theory. ... The book is well suited to promote the ideas of statistical learning theory and can be warmly recommended to all who are interested in computer learning problems." (S. Vogel, Metrika, June, 2002)

Bloggat om The Nature of Statistical Learning Theory

Innehållsförteckning

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