Table 1 The hyper-parameters’ values of the employed fusion techniques.
Hyper-parameters | Models | Values |
|---|---|---|
Number of iterations | All models | 100 |
Number of estimators | XGBoost, Random Forest, and Extra Trees | 100 |
Max depth of the tree | XGBoost, Random Forest, and Extra Trees | 3 (XGBoost) – 6 (for others) |
Learning rate | XGBoost | 0.01 |
Penalty | Logistic Regression | l2 |
Optimization algorithm | Logistic Regression | saga |
Number of features to consider per split | Random Forest, and Extra Trees | sqrt |
