Machine Learning using Stata/Python

2021/03/03 by Cerulli, Giovanni
#Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Mathematical Software (cs.MS)

paper · doi:10.48550/arxiv.2103.03122

Abstract

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.

Related

• pystacked: Stacking generalization and machine learning in Stata
• pystacked: Stacking generalization and machine learning in Stata
• Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence
• Machine Learning Algorithms in Statistical Modelling Bridging Theory and Application
• RuleKit 2: Faster and simpler rule learning