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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Boosting: Foundations and Algorithms

Boosting: Foundations and Algorithms

Schapire, Robert E.
Freund, Yoav

Paperback

Series: Adaptive Computation and Machine Learning

General ComputersProgramming

ISBN10: 0262526034
ISBN13: 9780262526036
Publisher: MIT Press
Published: Jan 10 2014
Pages: 544
Weight: 1.86
Height: 0.95 Width: 7.20 Depth: 8.93
Language: English
An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones.

Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate rules of thumb. 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.

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