Machine learningMachine learning
在线孤立森林 (Online Isolation Forest)
在线孤立森林将孤立森林异常检测算法扩展到了流式或连续到达的数据。当新观测值到达时，森林会进行增量更新，而不是从头开始重建孤立树，从而使异常分数保持最新，而无需重新处理全部历史数据。这使其在实时监控、欺诈检测和传感器数据监控等数据量无限增长的场景中具有实用性。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Liu, F. T., Ting, K. M., & Zhou, Z.-H. (2008). Isolation Forest. In Proceedings of the 8th IEEE International Conference on Data Mining (ICDM), pp. 413–422. DOI: 10.1109/ICDM.2008.17 ↗
- Tan, S. C., Ting, K. M., & Liu, T. F. (2011). Fast Anomaly Detection for Streaming Data. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI), pp. 1511–1516. link ↗
如何引用本页
ScholarGate. (2026, June 3). Online Isolation Forest (Streaming Anomaly Detection with Isolation Trees). ScholarGate. https://scholargate.app/zh/machine-learning/online-isolation-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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