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Boosting : foundations and algorithms

Author: Robert E Schapire; Yoav Freund
Publisher: Cambridge, MA : MIT Press, ©2012.
Series: Adaptive computation and machine learning.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
A remarkably rich theory has evolved around boosting, with connections to a range of topics including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Schapire, Robert E.
Boosting.
Cambridge, MA : MIT Press, c2012
(DLC) 2011038972
(OCoLC)758388404
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Robert E Schapire; Yoav Freund
ISBN: 9780262301183 0262301180
OCLC Number: 794669892
Description: 1 online resource (xv, 526 p.) : ill.
Contents: Foundations of machine learning --
Using AdaBoost to minimize training error --
Direct bounds on the generalization error --
The margins explanation for boosting's effectiveness --
Game theory, online learning, and boosting --
Loss minimization and generalizations of boosting --
Boosting, convex optimization, and information geometry --
Using confidence-rated weak predictions --
Multiclass classification problems --
Learning to rank --
Attaining the best possible accuracy --
Optimally efficient boosting --
Boosting in continuous time.
Series Title: Adaptive computation and machine learning.
Responsibility: Robert E. Schapire and Yoav Freund.

Abstract:

A remarkably rich theory has evolved around boosting, with connections to a range of topics including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. --

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This excellent book is a mind-stretcher that should be read and reread, even by nonspecialists. Computing Reviews Boosting is, quite simply, one of the best-written books I've read on machine Read more...

 
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