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.

Note

The score function calls mlr3measures::auc() from package mlr3measures.

If the measure is undefined for the input, NaN is returned. This can be customized by setting the field na_value.

Dictionary

This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():

mlr_measures$get("auc")
msr("auc")

Meta Information

  • Type: "binary"

  • Range: \([0, 1]\)

  • Minimize: FALSE

  • Required prediction: prob

See also