Machine learningMachine learning
度量学习
度量学习是一种机器学习框架，它从数据中训练一个距离或相似性函数，使得语义上相似的示例在学习到的空间中彼此靠近，而语义上不相似的示例则被推开。与欧几里得距离等固定距离不同，学习到的度量可以适应任务的结构，从而显著提高下游分类器、聚类器和检索系统的准确性。
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来源
- Xing, E. P., Jordan, M. I., Russell, S., & Ng, A. Y. (2003). Distance metric learning with application to clustering with side-information. In Advances in Neural Information Processing Systems (NIPS), 16, 505–512. link ↗
- Weinberger, K. Q., & Saul, L. K. (2009). Distance metric learning for large margin nearest neighbor classification. Journal of Machine Learning Research, 10, 207–244. link ↗
如何引用本页
ScholarGate. (2026, June 3). Metric Learning (Distance Metric Learning). ScholarGate. https://scholargate.app/zh/machine-learning/metric-learning
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