Get the Area under the ROC curve to assess classifier performance using pairwise concordance
auc_pairs(estimated.score, true.labels, verbose = TRUE)Float, Vector: Probabilities or model scores (e.g. c(.32, .75, .63), etc)
True labels of outcomes (e.g. c(0, 1, 1))
Logical: If TRUE, print messages to output
The first level of true.labels must be the positive class, and high numbers in
estimated.score should correspond to the positive class.