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Poster
On Bootstrapping the ROC Curve
Patrice Bertail · Stephan Clémençon · Nicolas Vayatis
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.
Author Information
Patrice Bertail (University Paris X)
Stephan Clémençon (Telecom ParisTech)
Nicolas Vayatis (Ecole Normale Supérieure de Cachan)
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