Area Under the ROC CurveSource:
Measure to compare true observed labels with predicted probabilities in binary classification tasks.
True (observed) labels. Must have the exactly same two levels and the same length as
Predicted probability for positive class. Must have exactly same length as
Name of the positive class.
Value that should be returned if the measure is not defined for the input (as described in the note). Default is
Additional arguments. Currently ignored.
Computes the area under the Receiver Operator Characteristic (ROC) curve. The AUC can be interpreted as the probability that a randomly chosen positive observation has a higher predicted probability than a randomly chosen negative observation.
This measure is undefined if the true values are either all positive or all negative.
Youden WJ (1950). “Index for rating diagnostic tests.” Cancer, 3(1), 32--35. doi:10.1002/1097-0142(1950)3:1<32::aid-cncr2820030106>3.0.co;2-3 .