What does AUC measure?

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 is an acceptable AUC score?

In general, an AUC of 0.5 suggests no discrimination (i.e., ability to diagnose patients with and without the disease or condition based on the test), 0.7 to 0.8 is considered acceptable, 0.8 to 0.9 is considered excellent, and more than 0.9 is considered outstanding.

What is area under the curve in medicine?

The area under the curve is a measurement of the overall quality of the diagnostic test. Tests with the same AUC show the same overall diagnostic performance, but not the same sensitivity and specificity.

Is area under curve accurate?

The AUC is an overall summary of diagnostic accuracy. AUC equals 0.5 when the ROC curve corresponds to random chance and 1.0 for perfect accuracy. On rare occasions, the estimated AUC is <0.5, indicating that the test does worse than chance.

How do you read an AUC curve?

AUC represents the probability that a random positive (green) example is positioned to the right of a random negative (red) example. AUC ranges in value from 0 to 1. A model whose predictions are 100% wrong has an AUC of 0.0; one whose predictions are 100% correct has an AUC of 1.0.

What is Cmax and AUC?

Abstract. In bioequivalence studies, the maximum concentration (Cmax) is shown to reflect not only the rate but also the extent of absorption. Cmax is highly correlated with the area under the curve (AUC) contrasting blood concentration with time.

How is AUC calculated?

The AUC can be computed by adjusting the values in the matrix so that cells where the positive case outranks the negative case receive a 1 , cells where the negative case has higher rank receive a 0 , and cells with ties get 0.5 (since applying the sign function to the difference in scores gives values of 1, -1, and 0 …

What does PR AUC mean?

Average Precision
PR AUC | Average Precision It is a curve that combines precision (PPV) and Recall (TPR) in a single visualization. For every threshold, you calculate PPV and TPR and plot it. The higher on y-axis your curve is the better your model performance.

What does a higher area under the curve mean?

Higher the AUC, the better the model is at predicting 0 classes as 0 and 1 classes as 1. By analogy, the Higher the AUC, the better the model is at distinguishing between patients with the disease and no disease. The ROC curve is plotted with TPR against the FPR where TPR is on the y-axis and FPR is on the x-axis.

What is the area under the normal curve?

Probability and the Normal Curve The normal distribution is a continuous probability distribution. This has several implications for probability. The total area under the normal curve is equal to 1. The probability that a normal random variable X equals any particular value is 0.

Is area under curve a percentage?

The area under the curve is the percentage of randomly drawn pairs for which this is true (that is, the test correctly classifies the two patients in the random pair).