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pystacked: Stacking generalization and machine learning in Stata

Author

Listed:
  • Christian B. Hansen

    (University of Chicago)

  • Mark E. Schaffer

    (Heriot-Watt University)

  • Achim Ahrens

    (ETH Zürich)

Abstract

pystacked implements stacked generalization (Wolpert 1992) for regression and binary classification via Python’s scikit-learn. 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 (multilayer perceptron). pystacked can also be used 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.

Suggested Citation

  • Christian B. Hansen & Mark E. Schaffer & Achim Ahrens, 2022. "pystacked: Stacking generalization and machine learning in Stata," Swiss Stata Conference 2022 01, Stata Users Group.
    • Handle: RePEc:boc:csug22:01
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    File URL: http://repec.org/csug2022/Ahrens-Bern2022-pystacked.pdf
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    Cited by:

    1. Nicolas Apfel & Holger Breinlich & Nick Green & Dennis Novy & J. M. C. Santos Silva & Tom Zylkin, 2025. "Out-of-sample gravity predictions and trade policy counterfactuals," Papers 2509.11271, arXiv.org, revised Sep 2025.
    2. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2025. "Model Averaging and Double Machine Learning," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(3), pages 249-269, April.
    3. Marcos Delprato, 2025. "Identifying the post-pandemic determinants of low performing students in Latin America through interpretable Machine Learning SHAP Values-Insights from PISA 2022," Papers 2509.24508, arXiv.org.
    4. Zuchuat, Jeremy & Lalive, Rafael & Osikominu, Aderonke & Pesaresi, Lorenzo & Zweimüller, Josef, 2023. "Duration Dependence in Finding a Job: Applications, Interviews, and Job Offers," CEPR Discussion Papers 18600, C.E.P.R. Discussion Papers.
    5. Bonaccolto-Töpfer, Marina & Satlukal, Sascha, 2024. "Gender differences in reservation wages: New evidence for Germany," Labour Economics, Elsevier, vol. 91(C).
    6. Philipp Bach & Oliver Schacht & Victor Chernozhukov & Sven Klaassen & Martin Spindler, 2024. "Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study," Papers 2402.04674, arXiv.org.

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