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主动学习梯度提升

主动学习梯度提升（Active Learning Gradient Boosting）将梯度提升树强大的预测准确性与主动学习循环相结合，该循环选择最具信息量的未标记示例供人工标注。通过仅查询模型最不确定的实例，该方法可以用远少于被动监督学习的标记示例实现高准确率。

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主动学习梯度提升
主动学习梯度提升（Gradient Boosting）随机森林XGBoost

来源

  1. Settles, B. (2010). Active Learning Literature Survey. Computer Sciences Technical Report 1648, University of Wisconsin–Madison. link ↗
  2. Friedman, J. H. (2001). Greedy Function Approximation: A Gradient Boosting Machine. Annals of Statistics, 29(5), 1189–1232. DOI: 10.1214/aos/1013203451 ↗

如何引用本页

ScholarGate. (2026, June 3). Active Learning with Gradient Boosting (Query-by-Committee / Uncertainty Sampling with Gradient Boosted Trees). ScholarGate. https://scholargate.app/zh/machine-learning/active-learning-gradient-boosting

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ScholarGate — Active Learning Gradient Boosting (Active Learning with Gradient Boosting (Query-by-Committee / Uncertainty Sampling with Gradient Boosted Trees)). 于 2026-06-15 检索自 https://scholargate.app/zh/machine-learning/active-learning-gradient-boosting · 数据集： https://doi.org/10.5281/zenodo.20539026