Metadata-Version: 2.1
Name: BDMLtools
Version: 0.4.4
Summary: Ml learning tools for busniess data mining
Author: 曾珂
Author-email: zengke403@163.com
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy==1.26.4
Requires-Dist: fastparquet>=0.7.1
Requires-Dist: pandas>=1.3.5
Requires-Dist: plotnine>=0.12.4
Requires-Dist: scikit-learn>=1.4.0
Requires-Dist: category_encoders>=2.3.0
Requires-Dist: lightgbm>=3.3.0
Requires-Dist: probatus>=2.0.0
Requires-Dist: mlxtend>=0.19.0
Requires-Dist: scikit-optimize>=0.9.0
Requires-Dist: shap<=0.44.1
Requires-Dist: IPython
Requires-Dist: openpyxl
Provides-Extra: all
Requires-Dist: numpy==1.26.4; extra == "all"
Requires-Dist: fastparquet>=0.7.1; extra == "all"
Requires-Dist: pandas>=1.3.5; extra == "all"
Requires-Dist: plotnine>=0.12.4; extra == "all"
Requires-Dist: scikit-learn>=1.4.0; extra == "all"
Requires-Dist: category_encoders>=2.3.0; extra == "all"
Requires-Dist: lightgbm>=3.3.0; extra == "all"
Requires-Dist: probatus>=2.0.0; extra == "all"
Requires-Dist: mlxtend>=0.19.0; extra == "all"
Requires-Dist: scikit-optimize>=0.9.0; extra == "all"
Requires-Dist: shap<=0.44.1; extra == "all"
Requires-Dist: IPython; extra == "all"
Requires-Dist: openpyxl; extra == "all"
Requires-Dist: pytest>=6.0.0; extra == "all"
Requires-Dist: pytest-cov>=2.10.0; extra == "all"
Requires-Dist: mock; extra == "all"
Requires-Dist: threadpoolctl>=3.0.0; extra == "all"
Requires-Dist: xgboost>=1.5.0; extra == "all"
Requires-Dist: catboost>=1.1.1; extra == "all"

# BDMLtools

[![PyPI version](https://img.shields.io/pypi/pyversions/BDMLtools.svg)](https://pypi.python.org/pypi/BDMLtools)
[![License](https://img.shields.io/github/license/zk403/mlearn)](https://github.com/zk403/mlearn/blob/main/LICENSE)
[![Build Status](https://github.com/zk403/mlearn/actions/workflows/python-test.yml/badge.svg)](https://github.com/zk403/mlearn/actions/workflows/python-test.yml)
[![codecov](https://codecov.io/gh/zk403/mlearn/main/graphs/badge.svg)](https://app.codecov.io/gh/zk403/mlearn)
[![PyPI release](https://img.shields.io/pypi/v/BDMLtools.svg)](https://pypi.python.org/pypi/BDMLtools)

BDMLtools是适用于常见商业数据分析数据挖掘场景下，中小数据量的二分类模型的机器学习建模工具包。
本模组将集成商业分析场景中二分类模型中常用的机器学习模型，并使之能够兼顾模型开发效率、报告制作与建模流程标准化。
本模组涵盖数据清洗、数据探索、特征工程、评分卡制作、模型评估、统计学逐步回归、机器学习模型及其参数优化等内容

安装: 

+ github

```
pip install git+git://github.com/zk403/mlearn.git
```

+ pypi

```
pip install BDMLtools
```

卸载: 

```
pip uninstall BDMLtools
```

更新
```
v0.4.4
1.varGroupReport的report_brief中加入woe
2.加入WOE绘图功能，可在binAdjust、varReport等中选择y的二轴显示为badrate或woe
3.在模型评估中新增sloping、calibration图
4.修复了诸多绘图bug
5.更新单元测试脚本，更新部分代码说明
```

