Fig. 3From: Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) projectThe ROC curves of the different machine learning classification models. The models are: Decision Tree (DT), Support Vector Machine (SVM), Artificial Neural Networks (ANN), Naïve Bayesian Classifier (BC), Bayesian Network (BN) and K-Nearest Neighbor (KNN). The results show that without using the SMOTE sampling method (a), BC and BN achieves the highest AUC (0.81) while with using the SMOTE sampling method (b), the KNN model achieves the highest AUC (0.94)Back to article page