Machine learningMachine learning

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.

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Sources

  1. Cover, T. & Hart, P. (1967). Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 13(1), 21–27. DOI: 10.1109/TIT.1967.1053964
  2. Papernot, N. & McDaniel, P. (2018). Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning. arXiv preprint arXiv:1803.04765. link

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Referenced by

ScholarGateExplainable K-Nearest Neighbors (Explainable K-Nearest Neighbors (XKNN)). Retrieved 2026-06-04 from https://scholargate.app/en/machine-learning/explainable-k-nearest-neighbors