On Jan 22, 2010, at 3:53 AM, Na'im R. Tyson wrote:
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?
You should probably contact the authors. When I tried using that
package a few weeks ago, several of the annotation features were
broken. I contacted the author who said there had been problems after
converting to S4 method. He also said there would be a fix but not
immediately. There has been a release since that time and I tried it,
but it did not appear to fix the problems I encountered. All I was
able to get were very simple ROC curves without any confidence
intervals or marking of levels. I ended up turning to the Epi package
for what I needed ( but I did not need confidence intervals so cannot
comment on that aspect.)
--
David.
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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David Winsemius, MD
Heritage Laboratories
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.