Metadata-Version: 2.1
Name: OptGBM
Version: 0.7.0
Summary: Optuna + LightGBM \= OptGBM
Home-page: UNKNOWN
Author: Kon
License: MIT License
Description: # OptGBM
        
        ![Python package](https://github.com/Y-oHr-N/OptGBM/workflows/Python%20package/badge.svg?branch=master)
        [![PyPI](https://img.shields.io/pypi/v/OptGBM)](https://pypi.org/project/OptGBM/)
        [![PyPI - License](https://img.shields.io/pypi/l/OptGBM)](https://pypi.org/project/OptGBM/)
        [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/Y-oHr-N/OptGBM/master)
        
        OptGBM (= Optuna + LightGBM) provides a scikit-learn compatible estimator that tunes hyperparameters in LightGBM with Optuna.
        
        ## Examples
        
        ```python
        from optgbm.sklearn import OGBMRegressor
        from sklearn.datasets import load_boston
        
        reg = OGBMRegressor(random_state=0)
        X, y = load_boston(return_X_y=True)
        
        reg.fit(X, y)
        
        score = reg.score(X, y)
        ```
        
        ## Installation
        
        ```
        pip install optgbm
        ```
        
        ## Testing
        
        ```
        python setup.py test
        ```
        
Platform: UNKNOWN
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Provides-Extra: develop
