We present two related Stata modules, r_ml_stata and c_ml_stata, for fitting popular Machine Learning (ML) methods both in regression and classification settings. Using the recent Stata/Python integration platform (sfi) of Stata 16, these commands provide hyper-parameters' optimal tuning via K-fold cross-validation using greed search. More specifically, they make use of the Python Scikit-learn API to carry out both cross-validation and outcome/label prediction.

中文翻译：

---

使用Stata / Python进行机器学习

我们提供了两个相关的Stata模块r_ml_stata和c_ml_stata，用于在回归和分类设置中都适合流行的机器学习（ML）方法。这些命令使用Stata 16的最新Stata / Python集成平台（sfi），通过使用贪婪搜索的K折交叉验证提供超参数的最佳调整。更具体地说，他们利用Python Scikit-learn API进行交叉验证和结果/标签预测。