Table 2.
Classification 2 (C-2) performance (Patients with NGT vs. Patients with T2D).
| ML algorithms | Accuracy | AUC | Mean Accuracy (SD, CV=10) |
Mean AUC (SD, CV=10) |
|---|---|---|---|---|
| Logistic Regression | 1 | 1 | 0.94 (0.04) | 0.94 (0.06) |
| Naive Bayes | 0.87 | 0.84 | 0.85 (0.04) | 0.92 (0.04) |
| Decision Tree | 0.86 | 0.83 | 0.84 (0.08) | 0.75 (0.16) |
| Random Forest | 0.89 | 0.98 | 0.96 (0.03) | 0.99 (0.02) |
| XGBoost | 0.92 | 0.96 | 0.91 (0.04) | 0.98 (0.02) |
| Multilayer Perceptron (MLP) | 1 | 1 | 0.91 (0.07) | 0.93 (0.07) |
We compared the performance of six ML algorithms using the Precision and area under the receiver operating characteristic (ROC) curve (AUC) values. We use the stratified cross-validation (CV) technique to obtain our results’ standard deviation (SD) (K Fold = 10).