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Performance of the XGBoost model.
| Training dataset (N = 469) | Test dataset (N = 118) | |
|---|---|---|
| BA | 84.89% | 85.21% |
| F-score | 73.36% | 76.06% |
| MCC | 63.68% | 66.56% |
| Precision | 63.10% | 69.23% |
| Recall | 87.60% | 84.38% |
| AUC | 91.53% | 90.88% |
| RMSE | 0.4052 | 0.3796 |
| R2 | 0.1424 | 0.2711 |
XGBoost, eXtreme Gradient Boosting; BA, balanced accuracy; MCC, Matthew’s correlation coefficient; AUC, area under the curve; RMSE, root mean square error; R2, coefficient of determination.
