Data set: Artificial cross-validation data for use with ROCR
A mock data set containing 10 sets of predictions and corresponding labels as would be obtained from 10-fold cross-validation.
data(ROCR.xval)
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.
# 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 perf <- performance(pred,"tpr","fpr") perf plot(perf,col="grey82",lty=3) plot(perf,lwd=3,avg="vertical",spread.estimate="boxplot",add=TRUE)
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