Bagging gradient-boosted trees for high precision, low variance ranking models

@inproceedings{Ganjisaffar2011BaggingGT,
  title={Bagging gradient-boosted trees for high precision, low variance ranking models},
  author={Yasser Ganjisaffar and Rich Caruana and Cristina V. Lopes},
  booktitle={SIGIR},
  year={2011}
}
Recent studies have shown that boosting provides excellent predictive performance across a wide variety of tasks. In Learning-to-rank, boosted models such as RankBoost and LambdaMART have been shown to be among the best performing learning methods based on evaluations on public data sets. In this paper, we show how the combination of bagging as a variance reduction technique and boosting as a bias reduction technique can result in very high precision and low variance ranking models. We perform… CONTINUE READING

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