Completed comments

explainability/compute_shap_vals.py

+# Computing SHAP Values
+# Author: Joaquín Torres Bravo
+"""
+    Script to compute SHAP values for chosen models.
+"""
+
 # Libraries
 # --------------------------------------------------------------------------------------------------------
 import pandas as pd
 import numpy as np
-import shap
-import pickle
+import shap # Explainability
+import pickle # Loading/saving models
+# Models
 from xgboost import XGBClassifier
 from sklearn.ensemble import RandomForestClassifier, BaggingClassifier, AdaBoostClassifier
 from sklearn.neural_network import MLPClassifier
@@ -72,7 +79,7 @@ if __name__ == "__main__":
             if is_tree:
                  explainer = shap.TreeExplainer(fitted_model)
             # else:
-            #     explainer = shap.KernelExplainer(fitted_model.predict_proba, X_test[:500])
+            #     explainer = shap.KernelExplainer...
             # Compute shap values
             shap_vals = explainer.shap_values(X_test, check_additivity=True) # Change to true for final results
             # ---------------------------------------------------------------------------------------------------------