Machine learningMachine learning
自监督单类支持向量机 (Self-supervised One-class SVM)
自监督单类支持向量机 (Self-supervised One-class SVM) 将基于预设任务的表征学习与单类支持向量机 (One-class SVM, OC-SVM) 相结合，无需异常样本的标签即可检测异常和新颖性。该模型首先仅从正常数据中学习富有表现力的特征嵌入，然后在学习到的特征空间中拟合一个 OC-SVM 边界，以标记出分布外样本。
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来源
- Golan, I. & El-Yaniv, R. (2018). Deep One-Class Classification. Proceedings of the 35th International Conference on Machine Learning (ICML), PMLR 80, 1747–1756. link ↗
- Ruff, L., Vandermeulen, R., Goernitz, N., Deecke, L., Siddiqui, S. A., Binder, A., Muller, E. & Kloft, M. (2018). Deep One-Class Classification. Proceedings of the 35th International Conference on Machine Learning (ICML), PMLR 80, 4393–4402. link ↗
如何引用本页
ScholarGate. (2026, June 3). Self-supervised One-class Support Vector Machine. ScholarGate. https://scholargate.app/zh/machine-learning/self-supervised-one-class-svm
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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