Table 2.
Scores for each learning algorithm metric.
| Accuracy (%) | Precision (%) | Recall (%) | F1-score (%) | |
|---|---|---|---|---|
| LR | 77.52 | 80.55 | 77.12 | 78.80 |
| DT | 83.28 | 82.17 | 88.29 | 85.12 |
| SVM | 72.62 | 73.60 | 77.12 | 75.32 |
| RF | 84.14 | 83.75 | 87.76 | 85.71 |
| GBDT | 89.04 | 87.87 | 92.55 | 90.15 |
| XGBoost | 88.46 | 88.54 | 90.42 | 89.47 |
| AdaBoost | 88.47 | 87.75 | 91.48 | 89.58 |
Bold values represent the best performing values among all the modeled properties.