Abstract Throughout science and technology, receiver operating characteristic (ROC) curves associated area under the curve ( $$\mathrm{AUC}$$ AUC ) measures constitute powerful tools for assessing predictive abilities of features, markers tests in binary classification problems. Despite its immense popularity...

The justification for making a measurement can be sought in asking what decisions are based on measurement, such as assessing the compliance of quality characteristic an entity relation to specification limit, SL. relative performance testing devices and classification algorithms used is often evaluated using venerable ever popular receiver operating (ROC). However, ROC tool has potentially all...

Which eyewitness identification procedure better enables eyewitnesses to discriminate between innocent and guilty suspects? In other words, which procedure better enables eyewitnesses to sort innocent and guilty suspects into their correct categories? The answer to that objective, theory-free question is what policymakers need to know, and it is precisely the information that ROC analysis provi...

Receiver operating characteristic (ROC) curves are very popular for evaluating a diagnostic test or score performances in various decision making applications: medicine, marketing, credit scoring etc. The ROC curve provides a concise graphical representation of the trade off between sensitivity and specificity. We will focus here on supervised classification into two groups. Error rate estimati...