Machine learningMachine learning
鲁棒决策树
鲁棒决策树是一种决策树变体，它采用修改后的分裂标准或训练程序进行训练，旨在降低对异常值、标签噪声和对抗性扰动的敏感性。鲁棒变体不使用受极端值强烈影响的标准不纯度度量，而是使用统计上鲁棒的类似物或正则化来生成在噪声或损坏数据条件下具有泛化能力的分裂。
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来源
- Chen, H., & Nan, F. (2019). Robust Decision Trees Against Adversarial Examples. Proceedings of the 36th International Conference on Machine Learning (ICML), PMLR 97, 1006–1015. link ↗
- Hubert, M., & Debruyne, M. (2010). Minimum covariance determinant. Wiley Interdisciplinary Reviews: Computational Statistics, 2(1), 36–43. (background on robust estimation applied to tree splitting criteria) DOI: 10.1002/wics.61 ↗
如何引用本页
ScholarGate. (2026, June 3). Robust Decision Tree (Outlier-Resistant Tree Induction). ScholarGate. https://scholargate.app/zh/machine-learning/robust-decision-tree
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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