Fig. 2

ROC curves for logistic regression, random forest, and multilayer perceptron models using a) backward selection model and b) all-feature model using cross-validation. We repeat the 5-fold cross validation 10 times, each time using stratified 5-fold split with different random initializations. We use different colors for ROC curves from different cross validations. Note that for both for both the all-variable and backward selection models, the model performance is insensitive to stratified 5-fold splits with different random initializations. Thus, the ROC curves are almost identical to each other