Machine learningMachine learning
在线随机森林
在线随机森林（ORF）将经典的随机森林扩展到流式设置，在不存储或重放完整训练集的情况下，随着新观测值的到来而逐步更新每个树。自适应随机森林（ARF）等算法增加了漂移检测，以便在数据分布随时间变化时，集成模型能够进行自适应调整。
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Method map
The neighbourhood of related methods — select a node to explore.
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来源
- Saffari, A., Leistner, C., Santner, J., Godec, M., & Bischof, H. (2009). On-line random forests. In Proceedings of the 3rd IEEE International Workshop on On-Line Learning for Computer Vision (OLCV 2009), pp. 1–8. IEEE. link ↗
- Gomes, H. M., Bifet, A., Read, J., Barddal, J. P., Enembreck, F., Pfharinger, B., Holmes, G., & Abdessalem, T. (2017). Adaptive random forests for evolving data stream classification. Machine Learning, 106(9), 1469–1495. DOI: 10.1007/s10994-017-5642-8 ↗
如何引用本页
ScholarGate. (2026, June 3). Online Random Forest (Incremental Ensemble of Decision Trees). ScholarGate. https://scholargate.app/zh/machine-learning/online-random-forest
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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