remove importance in XGBoost Fit since we have Explainer Dashboard

Author: diegomarvid

README.md

@@ -46,7 +46,6 @@ Here's an example of how to use the library to run an XGBoost pipeline:
 ```json
 {
     "custom_steps_path": "examples/ocf/",
-    "save_path": "runs/xgboost_train.pkl",
     "pipeline": {
         "name": "XGBoostTrainingPipeline",
         "description": "Training pipeline for XGBoost models.",

pipeline_lib/implementation/tabular/xgboost/fit_model.py

@@ -90,10 +90,6 @@ def execute(self, data: DataContainer) -> DataContainer:
         # Save the model to the data container
         data[DataContainer.MODEL] = model
 
-        importance = model.get_booster().get_score(importance_type="gain")
-        importance = dict(sorted(importance.items(), key=lambda item: item[1], reverse=True))
-        data[DataContainer.IMPORTANCE] = importance
-
         # save model to disk
         save_path = self.save_path