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An elementary introduction to statistical learning theory

Author: Sanjeev Kulkarni; Gilbert Harman; Wiley InterScience (Online service)
Publisher: Hoboken, N.J. : Wiley, ©2011.
Series: Wiley series in probability and statistics.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
"A joint endeavor from leading researchers in the fields of philosophy and electrical engineering An Introduction to Statistical Learning Theory provides a broad and accessible introduction to rapidly evolving field of statistical pattern recognition and statistical learning theory. Exploring topics that are not often covered in introductory level books on statistical learning theory, including PAC learning, VC  Read more...
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Genre/Form: Llibres electrònics
Additional Physical Format: Print version:
Kulkarni, Sanjeev.
Elementary introduction to statistical learning theory.
Hoboken, N.J. : Wiley, ©2011
(OCoLC)726329153
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Sanjeev Kulkarni; Gilbert Harman; Wiley InterScience (Online service)
ISBN: 9781118023471 1118023471 9781118023433 1118023439 1283098687 9781283098687
OCLC Number: 729724626
Description: 1 online resource (1 volume) : illustrations.
Contents: Introduction: Classification, Learning, Features, and Applications --
Probability --
Probability Densities --
The Pattern Recognition Problem --
The Optimal Bayes Decision Rule --
Learning from Examples --
The Nearest Neighbor Rule --
Kernel Rules --
Neural Networks: Perceptrons --
Multilayer Networks --
PAC Learning --
VC Dimension --
Infinite VC Dimension --
The Function Estimation Problem --
Learning Function Estimation --
Simplicity --
Support Vector Machines --
Boosting.
Series Title: Wiley series in probability and statistics.
Responsibility: Sanjeev Kulkarni, Gilbert Harman.

Abstract:

Serves as a fundamental introduction to statistical learning theory and its role in understanding human learning and inductive reasoning. Topics of coverage include: probability, pattern recognition,  Read more...

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"The main focus of the book is on the ideas behind basic principles of learning theory and I can strongly recommend the book to anyone who wants to comprehend these ideas." ( Mathematical Reviews , 1 Read more...

 
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