C:\Users\Broxter\Desktop\ALL VSCODE PROJECTS\MASTER FINAL RUN\mytinpanenv\Lib\site-packages\keras\src\saving\saving_lib.py:418: UserWarning: Skipping variable loading for optimizer 'adam', because it has 2 variables whereas the saved optimizer has 14 variables.
  trackable.load_own_variables(weights_store.get(inner_path))
24/24 ━━━━━━━━━━━━━━━━━━━━ 0s 2ms/step 
2024-10-09 08:08:37,607 - INFO - MSE: 510.23170215441286
2024-10-09 08:08:37,608 - INFO - MAE: 19.33947199928601
2024-10-09 08:08:37,608 - INFO - RMSE: 22.58830897066916
2024-10-09 08:08:37,608 - INFO - R²: 0.8231401014995439
2024-10-09 08:08:37,608 - INFO - Cross-validation completed.
2024-10-09 08:08:37,609 - INFO - Evaluating best LSTM model on the entire dataset...
142/142 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step  
2024-10-09 08:08:38,558 - INFO - MSE: 744.7094897949921
2024-10-09 08:08:38,558 - INFO - MAE: 13.450142203649797
2024-10-09 08:08:38,564 - INFO - RMSE: 27.289365873815978
2024-10-09 08:08:38,564 - INFO - R²: 0.9505853639715761
2024-10-09 08:08:38,564 - INFO - Evaluating best MLP model on the entire dataset...
142/142 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step 
2024-10-09 08:08:38,832 - INFO - MSE: 36396.92321552502
2024-10-09 08:08:38,839 - INFO - MAE: 111.03099907217221
2024-10-09 08:08:38,839 - INFO - RMSE: 190.77977674671135
2024-10-09 08:08:38,839 - INFO - R²: -1.4150903646263093
142/142 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step 
142/142 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step 
2024-10-09 08:08:40,224 - INFO - Training meta-learner 1...
2024-10-09 08:08:45,180 - INFO - Training meta-learner 2...
2024-10-09 08:08:49,158 - INFO - Models and scalers saved successfully.
2024-10-09 08:08:49,158 - INFO - Evaluating meta-learners on the entire dataset...
142/142 ━━━━━━━━━━━━━━━━━━━━ 0s 663us/step
2024-10-09 08:08:49,373 - INFO - MSE: 126.12109042731613
2024-10-09 08:08:49,373 - INFO - MAE: 6.485768012308609
2024-10-09 08:08:49,373 - INFO - RMSE: 11.230364661368576
2024-10-09 08:08:49,373 - INFO - R²: 0.9916313302510897
142/142 ━━━━━━━━━━━━━━━━━━━━ 0s 863us/step
2024-10-09 08:08:49,633 - INFO - MSE: 105.84872695143505
2024-10-09 08:08:49,633 - INFO - MAE: 5.871768047997949
2024-10-09 08:08:49,634 - INFO - RMSE: 10.288281049399606
2024-10-09 08:08:49,634 - INFO - R²: 0.9929764876263131
2024-10-09 08:08:49,725 - INFO - Final models and scalers saved successfully.
2024-10-09 08:08:56,561 - ERROR - Error calculating SHAP values for best_lstm_model: The truth 
value of an array with more than one element is ambiguous. Use a.any() or a.all()
2024-10-09 08:08:56,599 - ERROR - Traceback (most recent call last):
  File "c:\Users\Broxter\Desktop\ALL VSCODE PROJECTS\MASTER FINAL RUN\training code by openai o1 SHAP.py", line 368, in calculate_shap_values
    shap.summary_plot(shap_values_agg, X_sample_agg, feature_names=feature_names_used, show=False)
  File "C:\Users\Broxter\Desktop\ALL VSCODE PROJECTS\MASTER FINAL RUN\mytinpanenv\Lib\site-packages\shap\plots\_beeswarm.py", line 680, in summary_legacy
    if quant[ind] != last_bin:
       ^^^^^^^^^^^^^^^^^^^^^^
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

2024-10-09 08:08:56,676 - ERROR - Error calculating SHAP values for best_mlp_model: operands could not be broadcast together with shapes (200,20,23) (200,460)
2024-10-09 08:08:56,677 - ERROR - Traceback (most recent call last):
  File "c:\Users\Broxter\Desktop\ALL VSCODE PROJECTS\MASTER FINAL RUN\training code by openai o1 SHAP.py", line 342, in calculate_shap_values
    shap_values = explainer.shap_values(X_sample)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\Broxter\Desktop\ALL VSCODE PROJECTS\MASTER FINAL RUN\mytinpanenv\Lib\site-packages\shap\explainers\_gradient.py", line 158, in shap_values
    return self.explainer.shap_values(X, nsamples, ranked_outputs, output_rank_order, rseed, return_variances)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\Broxter\Desktop\ALL VSCODE PROJECTS\MASTER FINAL RUN\mytinpanenv\Lib\site-packages\shap\explainers\_gradient.py", line 345, in shap_values
    samples = grad[a] * samples_delta[a]
              ~~~~~~~~^~~~~~~~~~~~~~~~~~
ValueError: operands could not be broadcast together with shapes (200,20,23) (200,460)

PS C:\Users\Broxter\Desktop\ALL VSCODE PROJECTS\MASTER FINAL RUN> 
 *  History restored 
PS C:\Users\Broxter\Desktop\ALL VSCODE PROJECTS\MASTER FINAL RUN> \