Community corner: Stacked generalization
Do you want to use machine learning tools for regression or classification? Do you want to take advantage of combining results from multiple machine learners to improve predictions? With the pystacked command by Achim Ahrens, Christian Hansen, and Mark Schaffer, you can use stacked generalization to combine predictions from linear regression, logistic regression, lasso, elastic net, ridge regression, support vector machines, gradient boosting, random forest, and neural nets.
You can learn about this command and find examples of using pystacked for both classification and regression problems in the Stata Journal article and at the author's webpage. And take a look at the introductory video.
Our open-access article introducing -pystacked- for stacking and machine learning in @Stata is now available online. Watch our short video to see what -pystacked- can do. https://t.co/Xt3mNftu8j pic.twitter.com/QhvHKvqObU
— Achim Ahrens (@acahrens) January 7, 2024
