A mock data set containing 10 sets of predictions and corresponding labels as would be obtained from 10-fold cross-validation.

data(ROCR.xval)

## Format

A two element list. The first element, ROCR.xval$predictions, is itself a 10 element list. Each of these 10 elements is a vector of numerical predictions for each cross-validation run. Likewise, the second list entry, ROCR.xval$labels is a 10 element list in which each element is a vector of true class labels corresponding to the predictions.

## Examples

# plot ROC curves for several cross-validation runs (dotted
# in grey), overlaid by the vertical average curve and boxplots
# showing the vertical spread around the average.
library(ROCR)
data(ROCR.xval)
pred <- prediction(ROCR.xval$predictions, ROCR.xval$labels)
pred#> A prediction instance
#>   with 10 cross validation runs (equal lengths)perf <- performance(pred,"tpr","fpr")
perf#> A performance instance
#>   'False positive rate' vs. 'True positive rate' (alpha: 'Cutoff')
#>   for 10 cross validation runs plot(perf,col="grey82",lty=3)plot(perf,lwd=3,avg="vertical",spread.estimate="boxplot",add=TRUE)