Get the Area under the ROC curve to assess classifier performance using pairwise concordance
Usage
auc_pairs(estimated.score, true.labels, verbosity = 1L)
Arguments
- estimated.score
Float, Vector: Probabilities or model scores
(e.g. c(.32, .75, .63), etc)
- true.labels
True labels of outcomes (e.g. c(0, 1, 1))
- verbosity
Integer: Verbosity level.
Details
The first level of true.labels must be the positive class, and high numbers in
estimated.score should correspond to the positive class.
Examples
if (FALSE) { # \dontrun{
true.labels <- factor(c("a", "a", "a", "b", "b", "b", "b"))
estimated.score <- c(0.7, 0.55, 0.45, 0.25, 0.6, 0.7, 0.2)
auc_pairs(estimated.score, true.labels, verbosity = 1L)
} # }