The area under the ROC curve

The whole curve rather than its best point. TSS is a maximum over cuts, so a small change in a prediction often moves it not at all and then moves it a long way; the area responds to every reordering, which is what makes it the steadier reading when many rescorings are compared, as in occlusion(). Tied predictions take the average rank.

Usage

roc_auc(y, p)

Arguments

y

Observed presence-absence, 0/1 or logical.

p

Predicted scores for the same units, in the same order. Higher means presence.

Value

One number, or NA where the cell defines none.

Examples

roc_auc(c(0, 0, 1, 1), c(0.1, 0.2, 0.8, 0.9))