Machine learningMachine learning
主动学习提升（Active Learning Boosting）
主动学习提升将主动学习的查询驱动标签获取与AdaBoost等提升算法的加权集成逻辑相结合。该模型迭代地选择信息量最大的未标记样本进行标注——由提升集成内部的分歧或不确定性指导——并在每次获得新标签后重新训练，从而以远少于被动学习所需的标记样本数量实现高准确率。
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来源
- Abe, N. & Mamitsuka, H. (1998). Query Learning Strategies Using Boosting and Bagging. Proceedings of the 15th International Conference on Machine Learning (ICML 1998), pp. 1–9. Morgan Kaufmann. link ↗
- Settles, B. (2009). Active Learning Literature Survey. Computer Sciences Technical Report 1648, University of Wisconsin–Madison. link ↗
如何引用本页
ScholarGate. (2026, June 3). Active Learning with Boosting Ensembles. ScholarGate. https://scholargate.app/zh/machine-learning/active-learning-boosting
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