English(EN) On k-nearest-neighbor regression in metric spaces

新研究探讨度量空间中k-NN回归的一致性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

一篇新研究论文探讨了度量空间中k近邻（k-NN）回归的理论基础。该研究侧重于均方一致性，详细说明了邻居选择如何影响概率重新分布，并提供了近似误差和条件响应方差的条件。它还研究了Nagata维数的作用，证明虽然它确保了k-NN分类的通用一致性，但不能保证具有无界响应的回归的均方一致性。 AI

影响为k-NN回归的行为提供了理论见解，可能为未来的算法开发提供信息。

排序理由关于理论机器学习概念的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · L\'aszl\'o Gy\"orfi, Vladimir G. Pestov, Harro Walk, Roi Weiss · 2026-11-02 05:00

On k-nearest-neighbor regression in metric spaces

arXiv:2610.41896v1 Announce Type: new Abstract: We study mean squared consistency of k-nearest-neighbor regression for metric space valued features. For a fixed feature distribution mu with atomless distance distributions, we describe how neighbor selection redistributes probabil…