#自动构建树模型 ##自动构建xgboost或lightgbm模型
### 一、训练、自动选变量、自动调参数 1、训练模型
2、shap 或 feature importance自动筛选变量
3、相关性筛选变量
4、PSI筛选变量
5、自动调参
6、逐步剔除变量
7、构建最终模型
### 二、建模相关结果保存 1、将模型文件持久化
2、将变量重要性持久化
3、将模型效果持久化
4、500条x数据用于验证后续部署是否一致
5、模型在建模数据集上的预测结果持久化
## 三、使用教程 请查看ryan_tutorial_code.py。里面有两个例子，一个列子使用的数据集随机生成的数据，一个是虚构现实数据
## 四、依赖包安装（建议先创建虚拟环境，不创建虚拟环境也行，创建虚拟环境是为了不和其它项目有依赖包的冲突，不创建虚拟环境的话在基础python环境执行pip install即可） ####创建虚拟环境 conda create -y –force -n auto_build_tree_model python=3.7.2 ####激活虚拟环境 conda activate auto_build_tree_model
### 依赖包安装方式一
####安装依赖包 pip install pandas==1.2.4
pip install joblib==0.14.1
pip install xgboost==1.2.0
pip install bayesian-optimization==1.1.0
pip install lightgbm==3.2.1
pip install shap==0.36.0
### 依赖包安装方式二，执行如下命令安装依赖的包 pip install -r requirements.txt
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0.1.5 (2023-11-14)
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