computes various discrimination error values, namely: sensitivity, specificity, accuracy, positive predictive value (ppv), negative predictive value (npv) and AUC
evaluate_discrimination(actual, predicted, cutoff = NULL)vector of observed class labels (0/1)
vector of uncalibrated predictions
cut-off to be used for the computation of npv, ppv, sensitivity and specificity, Default: value that maximizes sensitivity and specificity (Youden-Index)
list object with the following components:
sensitivity
specificity
accuracy
positive predictive value
negative predictive value
cut-off that was used to compute the error values
AUC value