Learning to rank with extremely randomized trees
暂无分享,去创建一个
[1] Yi Chang,et al. Yahoo! Learning to Rank Challenge Overview , 2010, Yahoo! Learning to Rank Challenge.
[2] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[3] Jaana Kekäläinen,et al. Cumulated gain-based evaluation of IR techniques , 2002, TOIS.
[4] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[5] Jianfeng Gao,et al. Ranking, Boosting, and Model Adaptation , 2008 .
[6] Leo Breiman,et al. Classification and Regression Trees , 1984 .
[7] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[8] C. Burges,et al. Learning to Rank Using Classification and Gradient Boosting , 2008 .
[9] Pierre Geurts,et al. Extremely randomized trees , 2006, Machine Learning.
[10] Larry P. Heck,et al. Trada: tree based ranking function adaptation , 2008, CIKM '08.
[11] Yi Su,et al. Model Adaptation via Model Interpolation and Boosting for Web Search Ranking , 2009, EMNLP.
[12] Qiang Wu,et al. McRank: Learning to Rank Using Multiple Classification and Gradient Boosting , 2007, NIPS.
[13] Olivier Chapelle,et al. Expected reciprocal rank for graded relevance , 2009, CIKM.
[14] Wei-Yin Loh,et al. Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..
[15] Zhaohui Zheng,et al. Stochastic gradient boosted distributed decision trees , 2009, CIKM.
[16] Leo Breiman,et al. Random Forests , 2001, Machine Learning.