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Found 5 papers, 0 papers with code
On U-processes and clustering performance
Many clustering techniques aim at optimizing empirical criteria that are of the form of a U-statistic of degree two.
AUC optimization and the two-sample problem
A nearly optimal scoring function in the AUC sense is first learnt from one of the two half-samples.
Empirical performance maximization for linear rank statistics
The ROC curve is known to be the golden standard for measuring performance of a test/scoring statistic regarding its capacity of discrimination between two populations in a wide variety of applications, ranging from anomaly detection in signal processing to information retrieval, through medical diagnosis.
On Bootstrapping the ROC Curve
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.
Overlaying classifiers: a practical approach for optimal ranking
ROC curves are one of the most widely used displays to evaluate performance of scoring functions.
