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Boosting : foundations and algorithms

作者: Robert E Schapire; Yoav Freund
出版商: Cambridge, MA : MIT Press, ©2012.
叢書: Adaptive computation and machine learning.
版本/格式:   電子書 : 文獻 : 英語所有版本和格式的總覽
資料庫:WorldCat
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類型/形式: Electronic books
其他的實體格式: Print version:
Schapire, Robert E.
Boosting.
Cambridge, MA : MIT Press, c2012
(DLC) 2011038972
(OCoLC)758388404
資料類型: 文獻, 網際網路資源
文件類型: 網路資源, 電腦資料
所有的作者/貢獻者: Robert E Schapire; Yoav Freund
ISBN: 9780262301183 0262301180
OCLC系統控制編碼: 794669892
描述: 1 online resource (xv, 526 p.) : ill.
内容: 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.
叢書名: Adaptive computation and machine learning.
責任: Robert E. Schapire and Yoav Freund.

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"This excellent book is a mind-stretcher that should be read and reread, even bynonspecialists." -- Computing Reviews "Boosting is, quite simply, one of the best-written books I've read on machine 再讀一些...

 
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