Asymptotic Slowing Down of the Nearest-Neighbor Classifier
Abstract
If patterns are drawn from an n-dimensional feature space according to a probability distribution that obeys a weak smoothness criterion, we show that the probability that a random input pattern is misclassified by a nearest-neighbor classifier using M random reference patterns asymptoti(cid:173) cally satisfies
Cite
Text
Snapp et al. "Asymptotic Slowing Down of the Nearest-Neighbor Classifier." Neural Information Processing Systems, 1990.Markdown
[Snapp et al. "Asymptotic Slowing Down of the Nearest-Neighbor Classifier." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/snapp1990neurips-asymptotic/)BibTeX
@inproceedings{snapp1990neurips-asymptotic,
title = {{Asymptotic Slowing Down of the Nearest-Neighbor Classifier}},
author = {Snapp, Robert R. and Psaltis, Demetri and Venkatesh, Santosh S.},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {932-938},
url = {https://mlanthology.org/neurips/1990/snapp1990neurips-asymptotic/}
}