Metadata-Version: 2.1
Name: lupin4
Version: 0.0.4
Summary: UNKNOWN
Home-page: UNKNOWN
Author: Roryou
License: MIT
Keywords: scorecard,deep learning,wide&deep
Platform: UNKNOWN
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.5
Description-Content-Type: text/markdown
License-File: LICENSE



# lupin4

[![PyPi version][pypi-image]][pypi-url]
[![Python version][python-image]][docs-url]



lupin4 is designed to make the model developing work easily and conveniently.
It contains these functions below in one key operation: data exploratory analysis, feature selection, feature binning, 
data visualization, scorecard modeling(a logistic regression model with excellent interpretability), performance measure.


Let's get started.

## Usage
1.Exploratory Data Analysis  
lupin4.detect()  
lupin4.quality()  
lupin4.IV()  
lupin4.VIF()  
lupin4.PSI()  

2.Feature Selection  
lupin4.select()  
lupin4.stepwise()  

3.Binning  
lupin4.Combiner()  
lupin4.WOETransformer()  
lupin4.bin_stats()  
lupin4.bin_plot()  

4.Modeling  
lupin4.ScoreCard()  

5.Performance Measure  
lupin4.perform()  
lupin4.LIFT()  
lupin4.score_plot()  
lupin4.KS_bucket()  
lupin4.PPSI()  
lupin4.KS()  
lupin4.AUC()  

6.One Key Auto Modeling  
lupin4 also provides a function which runs all the steps above automatically:  
lupin4.auto_model()  

For more details, please refer to the wiki page. Enjoy.  


## Install


via pip

```bash
pip install lupin4 --upgrade -i https://pypi.org/simple
```

via source code

```bash
python setup.py install
```

install_requires = [
        'numpy >= 1.18.4',
        'pandas >= 0.25.1, <=0.25.3',
        'scipy >= 1.3.2',
        'scikit-learn =0.22.2',
        'seaborn >= 0.10.1',
        'statsmodels >= 0.13.1',
        'tensorflow >= 2.2.0, <=2.5.0',
        'hyperopt >= 0.2.7',
        'pickle >= 4.0',
    ]



[pypi-image]: https://img.shields.io/badge/pypi-V0.0.3-%3Cgreen%3E
[python-image]: https://img.shields.io/pypi/pyversions/toad.svg?style=flat-square




