There is a summary measure of the diagnostic ability of a binary classifier system that is also called "Gini coefficient", which is defined as twice the area between the receiver operating characteristic (ROC) curve and its diagonal. It is related to the AUC (Area Under the ROC Curve) measure of performance given by formula_40 and to Mann–Whitney U. Although both Gini coefficients are defined as areas between certain curves and share certain properties, there is no direct simple relation between the Gini coefficient of statistical dispersion and the Gini coefficient of a classifier.