A note on the prediction error of principal component regression
Statistics Theory
2019-04-17 v2 Statistics Theory
Abstract
We analyse the prediction error of principal component regression (PCR) and prove non-asymptotic upper bounds for the corresponding squared risk. Under mild assumptions, we show that PCR performs as well as the oracle method obtained by replacing empirical principal components by their population counterparts. Our approach relies on upper bounds for the excess risk of principal component analysis.
Cite
@article{arxiv.1811.02998,
title = {A note on the prediction error of principal component regression},
author = {Martin Wahl},
journal= {arXiv preprint arXiv:1811.02998},
year = {2019}
}
Comments
24 pages