accuracy {AUC}R Documentation

Compute the accuracy curve.

Description

This function computes the accuracy curve required for the auc function and the plot function.

Usage

  accuracy(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 accuracy 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)

accuracy(churn$predictions,churn$labels)

[Package AUC version 0.3.0 Index]