Thanks for the reply. I am not sure I am following: 1. for the sample code. I tried p...@auc but get auc object not found 2. I am SPECIFICALLY interested in the averaged auc value of the multiple runs. How to get that out? I typed perf and it comes out as a list. 3. as for the plot using whisker plot to see the distribution of the multiple runs, the outliers outside the whisker is very annoying. How to get rid of the "outline" which is outside the whisker? I tried to use boxplot option and put in the following plot code as an option outline=FALSE and it did not work.
Please help me with the specifics of the above 3 questions. Use code instead of description would be helpful. Thanks a lot in advance. >Waverley, >use @ (instead of $) to extract the slots from the performance object (it's S4 >class system). >HTH, > Tobias On Sat, Jul 25, 2009 at 8:20 AM, Waverley<waverley.paloa...@gmail.com> wrote: > I use ROCR to plot multiple runs' performance. Using the sample code > as example: > > # plot ROC curves for several cross-validation runs (dotted # in > grey), overlaid by the vertical average curve and boxplots # showing > the vertical spread around the average. > data(ROCR.xval) > pred <- prediction(ROCR.xval$predictions, ROCR.xval$labels) perf <- > performance(pred,"tpr","fpr") > plot(perf,col="grey82",lty=3) > plot(perf,lwd=3,avg="vertical",spread.estimate="boxplot",add=TRUE) > > I can follow the code and plot without any problem. However, I don't > know how to extract the averaged ROC area under curve value. > > Can someone help? > > Thanks. > > -- > Waverley @ Palo Alto > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Waverley @ Palo Alto ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
