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� ��'j� � �| � d Z ddlmZmZ ddlZddlZddlm Z ddl m Z ddl m Z ddlmZ ddlmZ G d � d e e � Zy) zwClassifier utilities for MySQL Connector/Python. Provides a scikit-learn compatible classifier backed by HeatWave ML. � )�Optional�UnionN)�ClassifierMixin)� MyBaseMLModel)�ML_TASK)� copy_dict)�MySQLConnectionAbstractc �P � e Zd ZdZ ddedee dee dee dee f d�Zd e e j e j f d e j fd �Zd e e j e j f d e j fd �Zd e e j e j f d e j fd �Zy)� MyClassifiera MySQL HeatWave scikit-learn compatible classifier estimator. Provides prediction and probability output from a model deployed in MySQL, and manages fit, explain, and prediction options as per HeatWave ML interface. Attributes: predict_extra_options (dict): Dictionary of optional parameters passed through to the MySQL backend for prediction and probability inference. _model (MyModel): Underlying interface for database model operations. fit_extra_options (dict): See MyBaseMLModel. Args: db_connection (MySQLConnectionAbstract): Active MySQL connector DB connection. model_name (str, optional): Custom name for the model. fit_extra_options (dict, optional): Extra options for fitting. explain_extra_options (dict, optional): Extra options for explanations. predict_extra_options (dict, optional): Extra options for predict/predict_proba. Methods: predict(X): Predict class labels. predict_proba(X): Predict class probabilities. N� db_connection� model_name�fit_extra_options�explain_extra_options�predict_extra_optionsc � � t j | |t j ||�� t |� | _ t |� | _ y)a Initialize a MyClassifier. Args: db_connection: Active MySQL connector database connection. model_name: Optional, custom model name. fit_extra_options: Optional fit options. explain_extra_options: Optional explain options. predict_extra_options: Optional predict/predict_proba options. Raises: DatabaseError: If a database connection issue occurs. If an operational error occurs during execution. )r r N)r �__init__r �CLASSIFICATIONr r r )�selfr r r r r s �G/opt/nydus/tmp/pip-target-k0fmikie/lib/python/mysql/ai/ml/classifier.pyr zMyClassifier.__init__G sE � �. � � � � � � "� "�!� /� � &/�/D�%E��"�%.�/D�%E��"� �X�returnc �v � | j j || j �� }|d j � S )a Predict class labels for the input features using the MySQL model. References: https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-predict-table.html A full list of supported options can be found under "ML_PREDICT_TABLE Options" Args: X: Input samples as a numpy array or pandas DataFrame. Returns: ndarray: Array of predicted class labels, shape (n_samples,). Raises: DatabaseError: If provided options are invalid or unsupported, or if the model is not initialized, i.e., fit or import has not been called If a database connection issue occurs. If an operational error occurs during execution. ��options� Prediction)�_model�predictr �to_numpy)r r �results r r zMyClassifier.predicth s7 � �0 ���$�$�Q��0J�0J�$�K���l�#�,�,�.�.r c � �� | j j || j �� }t |d j d d j � � �t j |d j �fd�� � S )a* Predict class probabilities for the input features using the MySQL model. References: https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-predict-table.html A full list of supported options can be found under "ML_PREDICT_TABLE Options" Args: X: Input samples as a numpy array or pandas DataFrame. Returns: ndarray: Array of shape (n_samples, n_classes) with class probabilities. Raises: DatabaseError: If provided options are invalid or unsupported, or if the model is not initialized, i.e., fit or import has not been called If a database connection issue occurs. If an operational error occurs during execution. r � ml_resultsr � probabilitiesc �: �� �D �cg c] }| d | �� c}S c c}w )Nr# � )� ml_result� class_name�classess �r �<lambda>z,MyClassifier.predict_proba.<locals>.<lambda>� s) �� �MT�#�MT�z�I�o�.�z�:�W�#�� #s �) r r r �sorted�iloc�keys�np�stack�map)r r r r( s @r � predict_probazMyClassifier.predict_proba� su �� �0 ���$�$�Q��0J�0J�$�K���� �-�2�2�1�5�o�F�K�K�M�N���x�x� �<� � $� $�� � � r c �R � | j j || j �� y)ai Explain model predictions using provided data. References: https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-explain-table.html A full list of supported options can be found under "ML_EXPLAIN_TABLE Options" Args: X: DataFrame for which predictions should be explained. Returns: DataFrame containing explanation details (feature attributions, etc.) Raises: DatabaseError: If provided options are invalid or unsupported, or if the model is not initialized, i.e., fit or import has not been called If a database connection issue occurs. If an operational error occurs during execution. Notes: Temporary input/output tables are cleaned up after explanation. r N)r �explain_predictionsr )r r s r r2 z MyClassifier.explain_predictions� s! � �6 � � �'�'��4�3M�3M�'�Nr )NNNN)�__name__� __module__� __qualname__�__doc__r r �str�dictr r �pd� DataFramer- �ndarrayr r0 r2 r% r r r r . s� � ��6 %)�,0�04�04� F�.� F� �S�M� F� $�D�>� F� (��~� F� (��~� F�B/��r�|�|�R�Z�Z�/�0�/� ���/�6" ��r�|�|�R�Z�Z�/�0�" � ���" �HO��r�|�|�R�Z�Z�/�0�O� � � �Or r )r6 �typingr r �numpyr- �pandasr9 � sklearn.baser �mysql.ai.ml.baser �mysql.ai.ml.modelr �mysql.ai.utilsr �mysql.connector.abstractsr r r% r r �<module>rD s6 ��:� #� � � (� *� %� $� =�TO�=�/� TOr
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