Model Selection via the VC-Dimension
Statistics Theory
2018-08-17 v1 Statistics Theory
Abstract
We derive an objective function that can be optimized to give an estimator of the Vapnik- Chervonenkis dimension for model selection in regression problems. We verify our estimator is consistent. Then, we verify it performs well compared to seven other model selection techniques. We do this for a variety of types of data sets.
Cite
@article{arxiv.1808.05296,
title = {Model Selection via the VC-Dimension},
author = {Merlin Mpoudeu and Bertrand Clarke},
journal= {arXiv preprint arXiv:1808.05296},
year = {2018}
}
Comments
62 pages and 16 figures, 14 tables