Metadata-Version: 2.1
Name: autowoe
Version: 1.2.3
Summary: Library for automatic interpretable model building (Whitebox AutoML)
Home-page: https://github.com/sberbank-ai-lab/AutoMLWhitebox
Author: Vakhrushev Anton
Author-email: AGVakhrushev@sberbank.ru
Requires-Python: >=3.6.1,<4.0.0
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: Russian
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Typing :: Typed
Requires-Dist: jinja2
Requires-Dist: joblib
Requires-Dist: lightgbm
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: pytest
Requires-Dist: pytz
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: seaborn
Requires-Dist: sphinx
Requires-Dist: sphinx-rtd-theme
Project-URL: Repository, https://github.com/sberbank-ai-lab/AutoMLWhitebox
Description-Content-Type: text/markdown

## Sberbank version of AutoWoE

![GitHub all releases](https://img.shields.io/github/downloads/sberbank-ai-lab/AutoMLWhitebox/total?color=green&logo=github&style=plastic)
![PyPI - Downloads](https://img.shields.io/pypi/dm/autowoe?color=green&label=PyPI%20downloads&logo=pypi&logoColor=orange&style=plastic)


This is the repository for **AutoWoE** library, developed by Sber AI Lab AutoML group. This library can be used for automatic creation of interpretable ML model based on feature binning, WoE features transformation, feature selection and Logistic Regression.

**Authors:** Vakhrushev Anton, Grigorii Penkin

**Library setup** can be done by one of three scenarios below:
- `pip install autowoe` for installation from PyPI
- `bash build_package.sh` for library installation into automatically created virtual environment and WHL files building
- pre-generated WHL file from specific release 

**Usage tutorials** are in Jupyter notebooks in the repository root. For **parameters description** take a look at `parameters_info.md`.

**Bugs / Questions / Suggestions:**:
- Vakhrushev Anton (AGVakhrushev@sberbank.ru)

