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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.
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Submitted on : Tuesday, April 23, 2019 - 3:30:19 PM
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  • HAL Id : hal-02107183, version 1


Patrice Bertail, Stéphan Clémençon, Nicolas Vayatis. On Bootstrapping the ROC Curve. On Bootstrapping the ROC Curve, 2009, Advances in Neural Information Processing Systems 21. ⟨hal-02107183⟩



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