Also known as: Area Under the Curve (AUC) Β· AUC
Area Under The Curve (AUC) is an evaluation metric for binary classification that measures the area under a performance curve, most commonly the receiver operating characteristic curve. It summarizes how well a model ranks positive examples above negative examples, with higher values generally indicating stronger discrimination. In many contexts, AUC refers specifically to ROC AUC.
In binary classification , an evaluation metric that is the value of the area under the curve that plots the true positives rate (on the y-axis) against the false positives rate (on the x-axis). Ranges from 0.5 (worst) to 1 (best). Also known as the area under the ROC curve, i.e., receiver operating characteristic curve. For more information, see the Receiver operating characteristic article on Wikipedia.