Improving the Predictive Performances of $k$ Nearest Neighbors Learning by Efficient Variable Selection
Machine Learning
2022-11-07 v1 Machine Learning
Abstract
This paper computationally demonstrates a sharp improvement in predictive performance for nearest neighbors thanks to an efficient forward selection of the predictor variables. We show both simulated and real-world data that this novel repeatedly approaches outperformance regression models under stepwise selection
Cite
@article{arxiv.2211.02600,
title = {Improving the Predictive Performances of $k$ Nearest Neighbors Learning by Efficient Variable Selection},
author = {Eddie Pei and Ernest Fokoue},
journal= {arXiv preprint arXiv:2211.02600},
year = {2022}
}
Comments
11 pages, 7 figures