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)