| roc {AUC} | R Documentation |
Compute the receiver operating characteristic (ROC) curve.
Description
This function computes the receiver operating characteristic (ROC) curve required for the auc function and the plot function.
Usage
roc(predictions, labels)
Arguments
predictions |
A numeric vector of classification probabilities (confidences, scores) of the positive event. |
labels |
A factor of observed class labels (responses) with the only allowed values {0,1}. |
Value
A list containing the following elements:
cutoffs |
A numeric vector of threshold values |
fpr |
A numeric vector of false positive rates corresponding to the threshold values |
tpr |
A numeric vector of true positive rates corresponding to the threshold values |
Author(s)
Authors: Michel Ballings and Dirk Van den Poel, Maintainer: Michel.Ballings@UGent.be
References
Ballings, M., Van den Poel, D., Threshold Independent Performance Measures for Probabilistic Classifcation Algorithms, Forthcoming.
See Also
sensitivity, specificity, accuracy, roc, auc, plot
Examples
data(churn)
roc(churn$predictions,churn$labels)