方法证据记录
Explainable K-Nearest Neighbors
Explainable K-Nearest Neighbors (XKNN) augments the classic KNN classifier or regressor with structured post-hoc or built-in explanation mechanisms, exposing which retrieved neighbors, which features, and which distance contributions drive each individual prediction — making the model's reasoning transparent and auditable for human decision-makers.
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。
Explainable K-Nearest Neighbors (XKNN)
分类方法记录 · ml-model / machine-learning
- Cover, T. & Hart, P. (1967). Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 13(1), 21–27. · DOI 10.1109/TIT.1967.1053964
- Papernot, N. & McDaniel, P. (2018). Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning. arXiv preprint arXiv:1803.04765. · URL
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