SIENTIAPDE-1171

Enhance data merging in MLFlowRepository by specifying merge parameters

- Updated the merge operation in the fit method to include 'how' and 'validate' parameters for improved data integrity and flexibility during model training.

laborious/utils/repository/model_repository.py

@@ -135,7 +135,12 @@ class MLFlowRepository():
         target_name = data_model.target_variable
         y = data[target_name]
         treated_data = pd.merge(
-            treated_data, y, left_index=True, right_index=True)
+            treated_data, y,
+            left_index=True,
+            right_index=True,
+            how='left',           # or 'inner', depending on your needs
+            validate='one_to_one'  # ensures each index appears only once in both
+        )
         prediction_model = prediction_model.fit(treated_data)
         experiment = self.get_experiment_by_run_id(latest_production_id)
         mlflow.set_experiment(experiment)