What is AUC in ROC curve?

What is AUC in ROC curve?

The Area Under the Curve (AUC) is the measure of the ability of a classifier to distinguish between classes and is used as a summary of the ROC curve. The higher the AUC, the better the performance of the model at distinguishing between the positive and negative classes.

What does ROC AUC tell you?

What is the AUC – ROC Curve? AUC – ROC curve is a performance measurement for the classification problems at various threshold settings. ROC is a probability curve and AUC represents the degree or measure of separability. It tells how much the model is capable of distinguishing between classes.

What means AUC?

area under the curve
In the field of pharmacokinetics, the area under the curve (AUC) is the definite integral of a curve that describes the variation of a drug concentration in blood plasma as a function of time (this can be done using liquid chromatography–mass spectrometry).

What is AUC in medical terms?

area under the curve. A representation of total drug exposure. The area-under-the-curve is a function of (1) the length of time the drug is present, and (2) the concentration of the drug in blood plasma.

What is a good AUC?

The higher is better however any value above 80% is considered good and over 90% means the model is behaving great. AUC is an abbreviation for Area Under the Curve.

What does AUC stand for and what is it?

Area Under the Curve (AUC) is a mathematical method of measuring drug concentrations. The “curve” referred to in AUC is the curve on a concentration-versus-time graph. The concentration of a drug in the patient’s blood is plotted against the time when the sample was taken.

What is the area under the ROC curve?

Area under curve ( AUC ) The area under (a ROC) curve is a summary measure of the accuracy of a quantitative diagnostic test. A point estimate of the AUC of the empirical ROC curve is the Mann-Whitney U estimator (DeLong et. al., 1988). The confidence interval for AUC indicates the uncertainty of the estimate and uses the Wald Z large sample normal…

What is AUC score?

An AUC score is a measure of the likelihood that the model that produced the predictions will rank a randomly chosen positive example above a randomly chosen negative example. Specifically, that the probability will be higher for a real event (class=1) than a real non-event (class=0).