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poteman
a0be65232c
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2 years ago | |
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| .idea | 2 years ago | |
| autox | 2 years ago | |
| competition_baseline/biendata_sohu_2022 | 2 years ago | |
| demo | 2 years ago | |
| docs | 2 years ago | |
| img | 2 years ago | |
| test | 2 years ago | |
| .DS_Store | 2 years ago | |
| .gitignore | 2 years ago | |
| LICENSE | 2 years ago | |
| README.md | 2 years ago | |
| README_EN.md | 2 years ago | |
| how_to_contribute.md | 2 years ago | |
| requirements.txt | 2 years ago | |
| run.py | 2 years ago | |
| run_oneclick.py | 2 years ago | |
| setup.py | 2 years ago | |
| submit.py | 2 years ago | |
README.md
English | 简体中文
AutoX是什么？
AutoX一个高效的自动化机器学习工具。
它的特点包括:
- 效果出色: AutoX在多个kaggle数据集上，效果显著优于其他解决方案(见效果对比)。
- 简单易用: AutoX的接口和sklearn类似，方便上手使用。
- 通用: 适用于分类和回归问题。
- 自动化: 无需人工干预，全自动的数据清洗、特征工程、模型调参等步骤。
- 灵活性: 各组件解耦合，能单独使用，对于自动机器学习效果不满意的地方，可以结合专家知识，AutoX提供灵活的接口。
- 比赛上分点总结：整理并公开历史比赛的上分点。
AutoX包含什么内容
- autox_competition: 主要针对于表格类型的数据挖掘竞赛
- autox_server: 用于上线部署的automl服务
- autox_interpreter: 机器学习可解释功能
加入社区
如何为AutoX贡献
目录
安装
github仓库安装
git clone https://github.com/4paradigm/autox.git
## github访问速度较慢时可以通过gitee地址 https://gitee.com/poteman/autox
pip install ./autox
pip安装
## pip安装包可能更新不及时，建议用github安装方式安装最新版本
!pip install automl-x -i https://www.pypi.org/simple/
快速上手
社区案例
比赛案例
见demo文件夹
数据集下载链接：https://pan.baidu.com/s/1p38OuP8_FJp2P_wJwhdFiw?pwd=8mxf
效果对比
不同任务下的效果提升百分比
| data_type | 对比AutoGluon | 对比H2o |
|---|---|---|
| binary classification | 20.44% | 2.98% |
| regression | 37.54% | 39.66% |
| time-series | 28.40% | 32.46% |
详细数据集对比
| data_type | single-or-multi | data_name | metric | AutoX | AutoGluon | H2o |
|---|---|---|---|---|---|---|
| binary classification | single-table | Springleaf | auc | 0.78865 | 0.61141 | 0.78186 |
| binary classification-nlp | single-table | stumbleupon | auc | 0.87177 | 0.81025 | 0.79039 |
| binary classification | single-table | santander | auc | 0.89196 | 0.64643 | 0.88775 |
| binary classification | multi-table | IEEE | accuracy | 0.920809 | 0.724925 | 0.907818 |
| regression | single-table | ventilator | mae | 0.755 | 8.434 | 4.221 |
| regression | single-table | Allstate Claims Severity | mae | 1137.07885 | 1173.35917 | 1163.12014 |
| regression | single-table | zhidemai | mse | 1.0034 | 1.9466 | 1.1927 |
| regression | single-table | Tabular Playground Series - Aug 2021 | rmse | 7.87731 | 10.3944 | 7.8895 |
| regression | single-table | House Prices | rmse | 0.13043 | 0.13104 | 0.13161 |
| regression | single-table | Restaurant Revenue | rmse | 2133204.32146 | 31913829.59876 | 28958013.69639 |
| regression | multi-table | Elo Merchant Category Recommendation | rmse | 3.72228 | 3.80801 | 22.88899 |
| regression-ts | single-table | Demand Forecasting | smape | 13.79241 | 25.39182 | 18.89678 |
| regression-ts | multi-table | Walmart Recruiting | wmae | 4660.99174 | 5024.16179 | 5128.31622 |
| regression-ts | multi-table | Rossmann Store Sales | RMSPE | 0.13850 | 0.20453 | 0.35757 |
| regression-cv | single-table | PetFinder | rmse | 20.1327 | 23.1732 | 21.0586 |
AutoX成就
企业支持
比赛获奖
TODO
功能开发完成后，发布相应的使用demo
若有其他希望AutoX支持的功能，欢迎提issue!
欢迎填写用户调研问卷，让AutoX变得更好!
错误排查
| 错误信息 | 解决办法 |
|---|
AutoX is an efficient automl tool, which is mainly aimed at data mining tasks with tabular data.
Jupyter Notebook CSV Python Markdown Pickle other
