Hi Max and Andrew,

Thanks so much for your reply. Indeed I found your link last night using
steps shown below.

My first question is if the following two steps are right and AUC is 51% as
shown below.

My seond question is that currently I am using cost parameter=1 (the default
in R-SVM; http://www.stanford.edu/group/wonglab/RSVMpage/R-SVM.html). To
improve the AUC from ROC curve, can I can optimize the SVM cost function
(instead of keeping it fixed a 1) to get the mimimum LOO error in training
cross.validation and then draw the ROC from decision.values as Step2 below
using a cost parameter that gave mimimum cross.validation error in the
training data. Is that right?

Many thanks.
----------

*Step 1: For obtaining ROC curve of test data I turned on "prob=T" option:*

> svmres.prob <- svm(traindx[,resrsvm$SelInd], as.factor(traindy),
decision.values = TRUE)
> svmpred.prob <- predict(svmres.prob, testdx[,resrsvm$SelInd],
decision.values = TRUE)
> print(confusionMatrix(svmpred.prob,testdy))
Confusion Matrix and Statistics

           Reference
Prediction  Resistant Sensitive
  Resistant         5        13
  Sensitive        37        88

             Accuracy : 0.6503


*Step 2: Actual ROC plot command using output from above and plot attached
as well as pdf (I am assuming the following says the AUC is 51.4):*
> library(ROCR)
> svm.roc <- prediction(attributes(svmpred.prob)$decision.values, testdy)
> svm.auc <- performance(svm.roc, 'tpr', 'fpr')
> aucsvm <- performance(svm.roc, 'auc')
> pdf(file="roc_curve_rsvm_decval.pdf")
> plot(svm.auc)
> print(str(aucsvm))
> print(str(aucsvm))
Formal class 'performance' [package "ROCR"] with 6 slots
  ..@ x.name      : chr "None"
  ..@ y.name      : chr "Area under the ROC curve"
  ..@ alpha.name  : chr "none"
  ..@ x.values    : list()
  ..@ y.values    :List of 1
  .. ..$ : num 0.514
  ..@ alpha.values: list()

---------------------------



On Tue, Feb 22, 2011 at 4:23 PM, Andrew Ziem <AZiem@us.ci.org> wrote:

> In addition's to Max's suggestion about caret, look at ROCR which
> visualizes ROC charts for any binary classifier.  I have an example of
> e1071::SVN and ROCR here
>
>
> https://heuristically.wordpress.com/2009/12/23/compare-performance-machine-learning-classifiers-r/
>
>
>
> -----Original Message-----
> From: r-help-bounces@r-project.org [mailto:r-help-bounces@r-project.org]
> On Behalf Of Angel Russo
> Sent: Monday, February 21, 2011 3:34 PM
> To: r-help@r-project.org
> Subject: [R] ROC from R-SVM?
>
> *Hi,
>
> *Does anyone know how can I show an *ROC curve for R-SVM*? I understand in
> R-SVM we are not optimizing over SVM cost parameter. Any example ROC for
> R-SVM code or guidance can be really useful.
>
> Thanks, Angel.
>
>
>

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