Table 6 Performance of decision tree, kNN, logistic regression, SVM and XGBoost in predicting mortality outcome among T2DM in-patients
Classifier | Â | Train | Test |
|---|---|---|---|
Decision Tree | Â | Â | |
Accuracy | Â | 1.00 | 1.00 |
Precision | Alive | 1.00 | 1.00 |
Dead | 1.00 | 0.94 | |
Recall | Alive | 1.00 | 0.99 |
Dead | 1.00 | 1.00 | |
F1 score | Alive | 1.00 | 1.00 |
Dead | 1 | 0.97 | |
kNN | Â | Â | Â |
Accuracy | Â | 0.90 | 0.90 |
Precision | Alive | 0.99 | 1.00 |
Dead | 0.20 | 0.06 | |
Recall | Alive | 0.90 | 0.90 |
Dead | 0.80 | 1.00 | |
F1 score | Alive | 0.94 | 0.95 |
Dead | 0.32 | 0.11 | |
Logistic Regression | Â | Â | |
Accuracy | Â | 0.90 | 0.90 |
Precision | Alive | 1.00 | 1.00 |
Dead | 0.15 | 0.00 | |
Recall | Alive | 0.89 | 0.90 |
Dead | 1.00 | 0.00 | |
F1 score | Alive | 0.94 | 0.95 |
Dead | 0.26 | 0.00 | |
SVM | Â | Â | Â |
Accuracy | Â | 0.88 | 0.90 |
Precision | Alive | 1.00 | 1.00 |
Dead | 0.00 | 0.00 | |
Recall | Alive | 0.88 | 0.90 |
Dead | 0.00 | 0.00 | |
F1 score | Alive | 0.94 | 0.95 |
Dead | 0.00 | 0.00 | |
XGBoost | Â | Â | Â |
Accuracy | Â | 0.90 | 0.88 |
Precision | Alive | 0.90 | 0.88 |
Dead | 0.00 | 0.00 | |
Recall | Alive | 1.00 | 1.00 |
Dead | 0.00 | 0.00 | |
F1 score | Alive | 0.95 | 0.94 |
Dead | 0.00 | 0.00 | |