Statistics Papers

Document Type

Journal Article

Date of this Version

6-2013

Publication Source

Journal of Machine Learning Research

Volume

14

Start Page

1505

Last Page

1511

Abstract

We compare the risk of ridge regression to a simple variant of ordinary least squares, in which one simply projects the data onto a finite dimensional subspace (as specified by a principal component analysis) and then performs an ordinary (un- regularized) least squares regression in this subspace. This note shows that the risk of this ordinary least squares method (PCA-OLS) is within a constant factor (namely 4) of the risk of ridge regression (RR).

Keywords

risk inflation, ridge regression, pca

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Date Posted: 27 November 2017

This document has been peer reviewed.