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Boosting - Foundations and Algorithms (Paperback) Loot Price: R1,655
Discovery Miles 16 550
Boosting - Foundations and Algorithms (Paperback): Yoav Freund

Boosting - Foundations and Algorithms (Paperback)

Yoav Freund

Series: Adaptive Computation and Machine Learning Series

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Loot Price R1,655 Discovery Miles 16 550 | Repayment Terms: R155 pm x 12*

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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. 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. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.

General

Imprint: MIT Press
Country of origin: United States
Series: Adaptive Computation and Machine Learning Series
Release date: February 2014
First published: 2012
Authors: Yoav Freund (Professor)
Dimensions: 181 x 230 x 24mm (L x W x T)
Format: Paperback
Pages: 544
ISBN-13: 978-0-262-52603-6
Categories: Books > Computing & IT > General theory of computing > Mathematical theory of computation
Books > Computing & IT > General theory of computing > Data structures
Books > Computing & IT > Computer programming > Algorithms & procedures
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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LSN: 0-262-52603-4
Barcode: 9780262526036

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