Machine learningMachine learning
半监督在线学习
半监督在线学习结合了在线学习的增量更新方式和利用无标签样本的能力，使模型能够从数据流中持续改进，而数据流中只有一小部分到达的实例带有真实标签。当标注成本高昂或延迟，但数据实时到达时，它尤其有价值。
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来源
- Goldberg, A., Li, M., & Zhu, X. (2008). Online manifold regularization: A new learning setting and empirical study. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2008), Lecture Notes in Computer Science, 5211, 393–407. Springer. link ↗
- Zhu, X., & Goldberg, A. B. (2009). Introduction to Semi-Supervised Learning. Morgan & Claypool Publishers. ISBN: 978-1-59829-548-3
如何引用本页
ScholarGate. (2026, June 3). Semi-supervised Online Learning (Incremental Learning with Partially Labeled Streams). ScholarGate. https://scholargate.app/zh/machine-learning/semi-supervised-online-learning
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