Boosting
Foundations and Algorithms
$87.63
- Paperback
544 pages
- Release Date
10 January 2014
Summary
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 informatio…
Book Details
| ISBN-13: | 9780262526036 |
|---|---|
| ISBN-10: | 0262526034 |
| Author: | Robert E. Schapire, Yoav Freund |
| Publisher: | MIT Press Ltd |
| Imprint: | MIT Press |
| Format: | Paperback |
| Number of Pages: | 544 |
| Release Date: | 10 January 2014 |
| Weight: | 762g |
| Dimensions: | 229mm x 178mm x 24mm |
| Series: | Adaptive Computation and Machine Learning series |
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What They're Saying
Critics Review
“This excellent book is a mind-stretcher that should be read and reread, evenbynonspecialists.” – Computing Reviews
This excellent book is a mind-stretcher that should be read and reread, even by nonspecialists.
—Computing ReviewsBoosting is, quite simply, one of the best-written books I’ve read on machine learning…
—The Bactra ReviewFor those who wish to work in the area, it is a clear and insightful view of the subject that deserves a place in the canon of machine learning and on the shelves of those who study it.
—Giles Hooker, Journal of the American Statistical AssociationAbout The Author
Robert E. Schapire
Robert E. Schapire is Principal Researcher at Microsoft Research in New York City. For their work on boosting, Freund and Schapire received both the G del Prize in 2003 and the Kanellakis Theory and Practice Award in 2004.Yoav Freund is Professor of Computer Science at the University of California, San Diego. For their work on boosting, Freund and Schapire received both the G del Prize in 2003 and the Kanellakis Theory and Practice Award in 2004.
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