This paper introduces cost curves, a graphical technique for visualizing the performance
(error rate or expected cost) of 2-class classifiers over the full range of possible class …

Many performance metrics have been introduced in the literature for the evaluation of
classification performance, each of them with different origins and areas of application …

Abstract Receiver Operating Characteristic (ROC) curves are a standard way to display the
performance of a set of binary classifiers for all feasible ratios of the costs associated with …

The area under the ROC curve (AUC) is a very widely used measure of performance for
classification and diagnostic rules. It has the appealing property of being objective, requiring …

Receiver Operating Characteristic (ROC) curves are popular ways of summarising the
performance of two class classification rules. In fact, however, they are extremely …

The area under the ROC curve, or the equivalent Gini index, is a widely used measure of
performance of supervised classification rules. It has the attractive property that it side-steps …

Brier Curves: a New Cost-Based Visualisation of Classifier Performance Page 1 Brier Curves: a
New Cost-Based Visualisation of Classifier Performance J. Hernández-Orallo1 and P. Flach2 …

In this note we use examples from the literature to illustrate some poor practices in
assessing the performance of supervised classification rules, and we suggest guidelines for …

ROC analysis investigates and employs the relationship between sensitivity and specificity
of a binary classifier. Sensitivity or true positiverate measures the proportion of positives …

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 …