Table 3.
Random Forest | XGBoost | Logistic Regression | |
---|---|---|---|
Accuracy | 86.7% | 86.7% | 86.7% |
Sensitivity | 80% | 80% | 80% |
Specificity | 90% | 90% | 90% |
AUROC | 0.90 | 0.88 | 0.84 |
Positive Predictive Value | 90% | 90% | 80% |
Negative Predictive Value | 90% | 90% | 90% |
Performance metrics for the 3 machine learning models implemented. XGBoost = extreme gradient boosting. AUROC = area under recover operating characteristic.