All Models are Wrong, but <i>Many</i> are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously. 论文

摘要

prediction model, U-statistics, conditional variable importance, conditional causal effects, and linear model coefficients. We then give probabilistic bounds for MCR, using a novel, generalizable technique. We apply MCR to a public data set of Broward County criminal records to study the reliance of recidivism prediction models on sex and race. In this application, MCR can be used to help inform VI for unknown, proprietary models.