Juliabelloni/weather-forecasting
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BaseEstimator�model�5model_name� pollutantc �� � t j j t j j t j � � � }|d|� d|� d�z }t j6 | |� y)a� 7 Saves a given machine learning model to a specified file location.8 9 This function saves a scikit-learn model (or any compatible model) to a 10 `.joblib` file. The file is named based on the provided model name and pollutant.11 The saved model can be loaded later for predictions or further training.12 13 Args:14 model: The machine learning model to be saved (e.g., RandomForestRegressor).15 model_name (str): The name to use when saving the model file.16 pollutant (str, optional): The pollutant associated with the model, used to 17 differentiate models. Defaults to "NO2".18 19 Returns:20 None21 �/ML4IProject/src/models/�_�.joblibN)�os�path�dirname�getcwd�joblib�dump)r r r �root� file_paths �Zc:\Users\Lisa\Documents\2024-2025\ML for industry\ML4IProject\src\models\saving_loading.py�22save_modelr sQ � �" �7�7�?�?�2�7�7�?�?�2�9�9�;�7� 8�D��2�:�,�a� �{�'�R�R�I�23�K�K��y�!� �returnc �� � t j j t j j t j � � � }|d| � d|� d�z }t j24 |� }|S )aj 25 Loads a scikit-learn model from a specified file location.26 27 This function loads a previously saved scikit-learn model from a `.joblib` file.28 The file is identified based on the provided model name and pollutant type.29 30 Args:31 model_name (str): The name of the model file to be loaded (without the extension).32 pollutant (str, optional): The pollutant associated with the model, used to 33 construct the file name. Defaults to "NO2".34 35 Returns:36 loaded_model (BaseEstimator): The loaded scikit-learn model (e.g., RandomForestRegressor).37 38 r r r39 )r r r
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