2008 NIPS NeurIPS 2008

On Bootstrapping the ROC Curve

Abstract

This paper is devoted to thoroughly investigating how to bootstrap the ROC curve, a widely used visual tool for evaluating the accuracy of test/scoring statistics in the bipartite setup. The issue of confidence bands for the ROC curve is considered and a resampling procedure based on a smooth version of the empirical distribution called the smoothed bootstrap" is introduced. Theoretical arguments and simulation results are presented to show that the "smoothed bootstrap" is preferable to a "naive" bootstrap in order to construct accurate confidence bands."

🌉 Interdisciplinary Bridge — Machine Learning and Mathematics & Optimization
🧭 Keyword Pioneer — resampling procedure
🐝 Cross-Pollinator — Artificial Intelligence, Data Science & Analytics, Machine Learning, Mathematics & Optimization, Reinforcement Learning
📈 Trend Setter — Evaluation
🐣 Hot Topic Early Bird — confidence interval