[PDF.37ja] Boosting: Foundations and Algorithms (Adaptive Computation and Machine Learning series)

Boosting: Foundations and Algorithms (Adaptive Computation and Machine Learning series)

[PDF.hc16] Boosting: Foundations and Algorithms (Adaptive Computation and Machine Learning series)

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 | #396270 in Books |  imusti |  2014-01-10 | Original language:English | PDF # 1 |  9.00 x.94 x7.00l,1.86 | File type: PDF | 544 pages

 | Mit Press

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||1 of 1 people found the following review helpful.| everything about boosting|By Sergey Babkin|It's a quite comprehensive book, describing lots of different ways to look at the AdaBoost family of algorithms. For all I can tell, the authors have collected all the state-of-the-art knowledge about boosting at the time the book was written, from the publications developed both by them and by the other people. So if you want to learn| ||Robert Schapire and Yoav Freund made a huge impact in machine and statistical learning with their invention of boosting, which has survived the test of time. There have been lively discussions about alternative explanations of why it works so well, and the ju

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 ...

You can specify the type of files you want, for your gadget.Boosting: Foundations and Algorithms (Adaptive Computation and Machine Learning series)   |  Robert E. Schapire, Yoav Freund. Just read it with an open mind because none of us really know.

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