Confidence intervals and bands for the binormal ROC curve revisited

Confidence Intervals for the Area Under the ROC Curve

In many applications, good ranking is a highly desirable performance for a classifier. The criterion commonly used to measure the ranking quality of a classification algorithm is the area under the ROC curve (AUC). To report it properly, it is crucial to determine an interval of confidence for its value. This paper provides confidence intervals for the AUC based on a statistical and combinatori...

Confidence Bands for ROC Curves

We address the problem of comparing the performance of classifiers. In this paper we study techniques for generating and evaluating confidence bands on ROC curves. Historically this has been done using one-dimensional confidence intervals by freezing one variable—the false-positive rate, or threshold on the classification scoring function. We adapt two prior methods and introduce a new radial s...

REU PROJECT Confidence bands for ROC Curves

Permutation Tests and Confidence Intervals for the Area under the Roc-curve

We investigate rank-based studentized permutation methods for the nonparametric Behrens-Fisher problem, i.e. inference methods for the area under the ROC-curve (AUC). We hereby prove that the studentized permutation distribution of the Brunner-Munzel rank statistic is asymptotically standard normal, even under the alternative. This does not only imply consistency of the corresponding permutatio...

ROC curves and confidence intervals : getting them

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