plotroc draws the recevier operating characteristic(ROC) curve for an svm-model
auc = svmrocplot(training_label, training_instance) auc = svmrocplot(training_label, training_instance , model) auc = svmrocplot(training_label, training_instance , libsvm_options) auc = svmrocplot(training_label, training_instance , libsvm_options, uselinear)
Use cross-validation on training data to get decision values and plot ROC curve.
Use the given model to predict testing data and obtain decision values for ROC
[label,instance]=libsvmread("demos/heart_scale"); svmrocplot(label, instance,'-v 5'); [label,instance]=libsvmread("demos/heart_scale"); model = svmtrain(label,instance); svmrocplot(label,instance,model); [label,instance]=libsvmread("demos/heart_scale"); svmrocplot(label, instance,'-v 5',%t); //linear [label,instance]=libsvmread("demos/heart_scale"); model = train(label,instance); svmrocplot(label,instance,model);