What is the advantages of the ROC curves?
For example I am classifying some images which is a binary classification problem. I extracted about 500 features and applied a features selection algorithm to select a set of features then I applied SVM for classification. In this case how can I get a ROC curve? Should I change the threshold values of my feature selection algorithm and get sensitivty and specificity of the output to draw a ROC curve?
In my case what is the purpose of creating a ROC curve?