Machine learningMachine learning
半监督K-均值
半监督K-均值通过整合部分监督信息（可以是少量带标签的种子点，也可以是成对的“必须链接”和“不能链接”约束）来扩展标准K-均值聚类，以指导聚类形成。它弥合了无监督聚类和全监督分类之间的鸿沟，在标签稀缺但完全获取成本高昂的情况下，能够形成更有意义的聚类。
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来源
- Wagstaff, K., Cardie, C., Rogers, S., & Schroedl, S. (2001). Constrained K-means Clustering with Background Knowledge. In Proceedings of the 18th International Conference on Machine Learning (ICML 2001), pp. 577–584. link ↗
- Basu, S., Banerjee, A., & Mooney, R. J. (2002). Semi-supervised Clustering by Seeding. In Proceedings of the 19th International Conference on Machine Learning (ICML 2002), pp. 27–34. link ↗
如何引用本页
ScholarGate. (2026, June 3). Semi-supervised K-means Clustering. ScholarGate. https://scholargate.app/zh/machine-learning/semi-supervised-k-means
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