Research Article
Decision Tree Ensembles to Predict Coronavirus Disease 2019 Infection: A Comparative Study
Table 1
Decision tree ensembles and the related packages.
| Classifier | Package |
| Single decision tree | Weka | Random forest | Weka | Bagging | Weka | XGBoost | XGBoost (Python) | AdaBoost | Weka | Balanced random forest (RUS) | Imblearn (Python) | SmoteBagging | Ebmc (R) | RUSBagging | Imblearn (Python) | SmoteBoost | Ebmc (R) | RUSBoost | Imblearn (Python) | SMOTE oversampling (single decision tree) | SMOTE (Weka), Weka | SMOTE oversampling random forest | SMOTE (Weka), Weka | SMOTE oversampling Bagging | SMOTE (Weka), Weka | SMOTE oversampling AdaBoost | SMOTE (Weka), Weka | SMOTE oversampling XGBoost | Imblearn (Python), XGBoost (Python) | Random undersampling (single decision tree) | SpreadsubSample (Weka), Weka | RUS random forest | SpreadsubSample (Weka), Weka | RUSBagging | SpreadsubSample (Weka), Weka | RUS XGBoost | Imblearn (Python), XGBoost (Python) | RUS AdaBoost | SpreadsubSample (Weka), Weka |
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