Metadata-Version: 2.1
Name: neptune-sklearn
Version: 0.9.2
Summary: Neptune.ai scikit-learn integration library
Home-page: https://github.com/neptune-ai/neptune-client
Author: neptune.ai
Author-email: contact@neptune.ai
License: MIT License
Description: # Neptune: sklearn integration
        
        See [the official docs](https://docs.neptune.ai/integrations-and-supported-tools/model-training/sklearn).
        
        Minimal example:
        
        ```python
        from sklearn.datasets import load_boston
        from sklearn.ensemble import RandomForestRegressor
        from sklearn.model_selection import train_test_split
        import neptune.new as neptune
        import neptune.new.integrations.sklearn as npt_utils
        
        run = neptune.init(project='common/sklearn-integration',
                           api_token='ANONYMOUS',
                           name='regression-example',
                           tags=['RandomForestRegressor', 'regression'])
        
        parameters = {'n_estimators': 70,
                      'max_depth': 7,
                      'min_samples_split': 3}
        
        
        rfr = RandomForestRegressor(**parameters)
        
        X, y = load_boston(return_X_y=True)
        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=28743)
        
        rfr.fit(X_train, y_train)
        
        run['rfr_summary'] = npt_utils.create_regressor_summary(rfr, X_train, X_test, y_train, y_test)
        ```
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