evaluate_discrimination: evaluate_discrimination

In CalibratR: Mapping ML Scores to Calibrated Predictions

Description

computes various discrimination error values, namely: sensitivity, specificity, accuracy, positive predictive value (ppv), negative predictive value (npv) and AUC

Usage

evaluate_discrimination(actual, predicted, cutoff = NULL)

Arguments

actual	vector of observed class labels (0/1)
predicted	vector of uncalibrated predictions
cutoff	cut-off to be used for the computation of npv, ppv, sensitivity and specificity, Default: value that maximizes sensitivity and specificity (Youden-Index)

Value

list object with the following components:

sens	sensitivity
spec	specificity
acc	accuracy
ppv	positive predictive value
npv	negative predictive value
cutoff	cut-off that was used to compute the error values
auc	AUC value

See Also

roc

CalibratR documentation built on Aug. 19, 2019, 5:04 p.m.