Nonparametric variable importance assessment using machine learning techniques.

ABSTRACT: In a regression setting, it is often of interest to quantify the importance of various features in predicting the response. Commonly, the variable importance measure used is determined by the regression technique employed. For this reason, practitioners often only resort to one of a few regression techniques for which a variable importance measure is naturally defined. Unfortunately, these regression techniques are often suboptimal for predicting the response. Additionally, because the variable importance measures native to different regression techniques generally have a different interpretation, comparisons across techniques can be difficult. In this work, we study a variable importance measure that can be used with any regression technique, and whose interpretation is agnostic to the te

SUBMITTER: Williamson BD 

PROVIDER: S-EPMC7946807 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature