| Parameter | Value | Description |
| Objective | binary: logistic | The objective function for binary classification. |
| colsample_bytree | 0.3 | Fraction of features used per tree, combating overfitting. |
| Learning Rate | 0.01 | Shrinks feature weights to improve model robustness. |
| Max Depth | 12 | Limits tree depth to prevent over-complex models. |
| reg_alpha | 0.001 | L1 regularization on weights, encouraging sparsity. |
| n_estimators | 550 | Total count of boosting trees to be constructed. |
| Random State | 42 | Ensures reproducibility with a fixed seed. |