pystacked: Stacking generalization and machine learning in Stata

Achim Ahrens*, Christian B. Hansen, Mark Edwin Schaffer

*Corresponding author for this work

Research output: Working paper


pystacked implements stacked generalization (Wolpert, 1992) for regression and binary classification via Python's scikit-lear}. Stacking combines multiple supervised machine learners -- the "base" or "level-0" learners -- into a single learner. The currently supported base learners include regularized regression, random forest, gradient boosted trees, support vector machines, and feed-forward neural nets (multi-layer perceptron). pystacked can also be used with as a `regular' machine learning program to fit a single base learner and, thus, provides an easy-to-use API for scikit-learn's machine learning algorithms.
Original languageEnglish
Publication statusPublished - 23 Aug 2022


  • machine learning
  • stacked generalization
  • model averaging
  • Stata
  • Python
  • sci-kit learn


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