人工知能学会第二種研究会資料
Online ISSN : 2436-5556
Smooth Boosting for Margin-Based Ranking
Jun-ichiMoribeKohei HatanoEiji TakimotoMasayuki Takeda
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研究報告書・技術報告書 フリー

2008 年 2008 巻 DMSM-A801 号 p. 02-

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We propose a new boosting algorithm for bipartite ranking problems. Our boosting algorithm, called SoftRankBoost, is a modification of RankBoost which maintains only smooth distributions over data. SoftRankBoost provably achieves approximately the maximum soft margin over all pairs of positive and negative examples, which implies high AUC score for future data.

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© 2008 著作者
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