Table 2 Performance parameters of models with the highest AUROC
From: Machine learning-based approach for predicting low birth weight
Row | Algorithms | Accuracy | Precision | Recall | F_1 Score |
|---|---|---|---|---|---|
1 | Random Forest Classification | 0.78 | 0.85 | 0.70 | 0.77 |
2 | XGBoost Classification | 0.79 | 0.87 | 0.69 | 0.77 |
3 | Deep Learning- Feed Forward | 0.78 | 0.84 | 0.70 | 0.76 |