Dear R-philes,
I am plotting ROC curves for several cross-validation runs of a
classifier (using the function below). In addition to the average
AUC, I am interested in obtaining a confidence interval for the
average AUC. Is there a straightforward way to do this via the ROCR
package?
plot_roc_curve <- function(roc.dat, plt.title) {
#print(str(vowel.ROC))
pred <- prediction(roc.dat$predictions, roc.dat$labels)
perf <- performance(pred, "tpr", "fpr")
perf.auc <- performance(pred, "auc")
perf.auc.areas <- slot(perf.auc, "y.values")
curve.area <- mean(unlist(perf.auc.areas))
#quartz(width=4, height=6)
plot(perf, col="grey82", lty=3)
plot(perf,lwd=3,avg="horizontal",spread.estimate="boxplot",
add=T)
title(main=plt.title)
mtext(sprintf("%s%1.4f", "Area under Curve = ", curve.area),
side=3, line=0, cex=0.8)
}
P.S. After years of studying statistical analysis as a student, I
still consider myself a novice.
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