| specificity {AUC} | R Documentation |
Compute the specificity curve.
Description
This function computes the specificity curve required for the auc function and the plot function.
Usage
specificity(predictions, labels, perc.rank = TRUE)
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}. |
perc.rank |
A logical. If TRUE (default) the percentile rank of the predictions is used. |
Value
A list containing the following elements:
cutoffs |
A numeric vector of threshold values |
measure |
A numeric vector of specificity values 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)
specificity(churn$predictions,churn$labels)