Machine learningMachine learning
半监督XGBoost
半监督XGBoost将XGBoost梯度提升框架扩展到只有部分训练样本带有标签的场景。通过迭代地为未标记数据生成伪标签，并在扩展数据集上重新训练，该方法从未标记观测中提取信号，在标记数据稀缺时提高泛化能力。
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来源
- Chen, T. & Guestrin, C. (2016). XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 785–794. DOI: 10.1145/2939672.2939785 ↗
- Chapelle, O., Scholkopf, B. & Zien, A. (Eds.) (2006). Semi-Supervised Learning. MIT Press. ISBN: 978-0-262-03358-9
如何引用本页
ScholarGate. (2026, June 3). Semi-supervised Extreme Gradient Boosting. ScholarGate. https://scholargate.app/zh/machine-learning/semi-supervised-xgboost
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