I still think you ought to do cross-validation or something like it for #1 (ROCR may do it internally for you). You really don't want to evaluate how well your model "predicts" its own training data. I would train on 9/10ths of your data, test on the remaining 1/10th and repeat until each point has been tested once, and use that to generate each point of your ROC curve.