The receiver operating characteristic (ROC) curve is used for classification between two populations. Usually two independent random samples from the populations with absolutely continuous cumulative distribution functions (CDF) F and G are considered. Then the ROC curve is defined as ROC(t) = 1−G(F−1(1− t)) for 0 < t < 1 if the inverse F−1 exists. Classical ROC curve estimator is based on empi...

In many practical classiication problems it is important to distinguish false positive from false negative results when evaluating the performance of the classiier. This is of particular importance for medical diagnostic tests. In this context, receiver operating characteristic (ROC) curves have become a standard tool. Here we apply this concept to characterize the performance of a simple neura...

Eyewitness identification is a pivotal issue in applied research because, in practice, a correct identification can help to remove a dangerous criminal from society, but a false identification can lead to the erroneous conviction of an innocent suspect. Consequently, psychologists have tried to ascertain the best procedures for collecting identification evidence, evaluating them using measures ...

The receiver operating characteristic (ROC) curve is used to describe the performance of a diagnostic test which classifies observations into two groups. We introduce new methods for selecting bandwidths when computing kernel estimates of ROC curves. Our techniques allow for interaction between the distributions of each group of observations and give substantial improvement in MISE over other p...

Precision-recall (PR) and receiver operating characteristic (ROC) curves are valuable measures of classifier performance. Here, we present the R-package PRROC, which allows for computing and visualizing both PR and ROC curves. In contrast to available R-packages, PRROC allows for computing PR and ROC curves and areas under these curves for soft-labeled data using a continuous interpolation betw...

Background: Bender Gestalt Test is one of the most famous neuropsychological tests, simple and easy to perform, and is used to evaluate brain injuries. This study aimed at determining the rate of sensitivity, characteristic and cut-off point of this test in patients with traumatic brain injury (TBI). Methods and Materials: Overall, 120 TBI patients with mean age of 31.25± 13.60 years old in...

The area under an ROC curve (AUC) has been advocated as an evaluation criterion for bipartite ranking problems. In this paper, we study large deviation properties of the AUC; in particular, we derive a distribution-free large deviation bound for the AUC which serves to bound the expected accuracy of a ranking function in terms of its empirical AUC on an independent test sequence.1 A comparison ...