方法证据记录
Ensemble Metric Learning
Ensemble Metric Learning trains multiple distance metric learners — each on a different data view, feature subspace, or with a different objective — and combines the resulting metrics to produce a single, more robust similarity function. Combining diverse metrics reduces the variance of any individual metric and improves performance in tasks such as nearest-neighbor classification, retrieval, and few-shot learning.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Ensemble Metric Learning (Combined Distance Metric Ensembles)
分类方法记录 · ml-model / machine-learning
- Wang, J., Kalousis, A., & Woznica, A. (2012). Parametric local metric learning for nearest neighbor classification. Advances in Neural Information Processing Systems, 25. · URL
- Similarity learning. Wikipedia. · URL
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