Challenges in Variable Importance Ranking Under Correlation

no code implementations • 5 Feb 2024 • Annie Liang, Thomas Jemielita, Andy Liaw, Vladimir Svetnik, Lingkang Huang, Richard Baumgartner, Jason M. Klusowski

Recently, several adjustments to marginal permutation utilizing feature knockoffs were proposed to address this issue, such as the variable importance measure known as conditional predictive impact (CPI).

Feature Correlation Interpretable Machine Learning

CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search

1 code implementation • 11 Oct 2021 • Hengrui Cai, Wenbin Lu, Rachel Marceau West, Devan V. Mehrotra, Lingkang Huang

In this paper, we present an optimal subgroup selection rule (SSR) that maximizes the number of selected patients, and in the meantime, achieves the pre-specified clinically meaningful mean outcome, such as the average treatment effect.