KNN_predictions = KNN_model.predict(testData) # Saving predictions csv_saver(predictions=KNN_predictions, type="KNN") # Decision model predictions DT_model = Models.build_model_DT() DT_predictions = DT_model.predict(testData) # Saving predictions csv_saver(predictions=DT_predictions, type="DT") # Default and tuned Random Forest model predictions RF_model = Models.build_model_RF() RF_tuned = Models.build_optimized_RF() RF_predictions = RF_model.predict(testData) RF_tuned_predictions = RF_tuned.predict(testData) # Saving predictions csv_saver(predictions=RF_predictions, type="RF") csv_saver(predictions=RF_tuned_predictions, type="RF_tuned") # Decision model predictions SVC_model = Models.build_model_SVC() SVC_predictions = SVC_model.predict(testData) # Saving predictions csv_saver(predictions=SVC_predictions, type="SVC") # XGBoost model predictions XGB_model = Models.build_model_XGB() XGB_predictions = XGB_model.predict(testData) # Saving predictions csv_saver(predictions=XGB_predictions, type="XGBoost")