In other words, I did not use the trained XGBoost model to make predictions on the test set and then use SHAP for interpretation. The reasons are as follows:
Jorge Bernal-Alviz
Indeed! However, you must ensure the robustness and reliability of your validation method with respect to overfitting, potential biases, calibration, and data leakage. The most important consideration is using an appropriate SHAP algorithm. I recommend opting for conditional, parametric, and causal variants instead of interventional ones, as they tend to alter real estimations at both local and global scales. Good luck!
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