WHY THIS ERROR ?
PS C:\Users\siddh> & C:/Users/siddh/AppData/Local/Programs/Python/Python311/python.exe c:/Users/swarn/python_codes/python_try/hugging/predictive_32.py
C:\Users\siddh\AppData\Local\Programs\Python\Python311\Lib\site-packages\yfinance\base.py:48: FutureWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
  _empty_series = pd.Series()
Program started...
Do you want to 'Train' the models or 'Use' existing models? Enter 'Train' or 'Use': use
Enter the stock symbols separated by commas (e.g., AAPL, GOOGL, MSFT): NSE:SUZLON
Enter the prediction horizon in days (e.g., 5): 15
Enter the number of years of data to use for training (e.g., 5 or 10): 5
Training the Models on 2 stocks data
Estimated Time in minutes =  2
Time of start =  2024-09-23 00:12:04.286726
Loading saved models...
RandomForestRegressor model loaded from c:/users/swarn/python_codes/python_try/hugging/new_models/predictive_32_RandomForestRegressor_model.pkl
XGBoostRegressor model loaded from c:/users/swarn/python_codes/python_try/hugging/new_models/predictive_32_XGBoostRegressor_model.pkl
Scaler loaded from scaler.pkl
Label encoder loaded from label_encoder.pkl

Available models:
1. Random Forest Regressor - RMSE: 0.116375
2. XGBoost Regressor - RMSE: 0.096497
Enter the number corresponding to the model you want to use: 1
You have selected: Random Forest Regressor
Fetching stock data...
[*********************100%%**********************]  1 of 1 completed                                                                                                 | 0/2 [00:00<?, ?it/s]
[*********************100%%**********************]  1 of 1 completed█████████████                                                                            | 1/2 [00:02<00:02,  2.78s/it]
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:02<00:00,  1.45s/it]
Calculating technical indicators on recent data...
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 197.96it/s]
Traceback (most recent call last):
  File "C:\Users\siddh\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\utils\_encode.py", line 225, in _encode
    return _map_to_integer(values, uniques)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\siddh\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\utils\_encode.py", line 165, in _map_to_integer
    return np.array([table[v] for v in values])
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\siddh\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\utils\_encode.py", line 165, in <listcomp>
    return np.array([table[v] for v in values])
                     ~~~~~^^^
  File "C:\Users\siddh\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\utils\_encode.py", line 159, in __missing__
    raise KeyError(key)
KeyError: 'WAAREERTL.BO'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "c:\Users\swarn\python_codes\python_try\hugging\predictive_32.py", line 919, in <module>
    main_machine_learning()
  File "c:\Users\swarn\python_codes\python_try\hugging\predictive_32.py", line 800, in main_machine_learning
    recent_dataset['Symbol_Encoded'] = le.transform(recent_dataset['Symbol'])
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\siddh\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\preprocessing\_label.py", line 137, in transform
    return _encode(y, uniques=self.classes_)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\siddh\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\utils\_encode.py", line 227, in _encode
    raise ValueError(f"y contains previously unseen labels: {str(e)}")
ValueError: y contains previously unseen labels: 'WAAREERTL.BO'