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PYSTACKED: Stata module for stacking generalization and machine learning in Stata

Author

Listed:
  • Achim Ahrens

    (ETH Zürich)

  • Christian B. Hansen

    (University of Chicago)

  • Mark E Schaffer

    (Heriot-Watt University)

Programming Language

Stata

Abstract

pystacked implements stacked generalization 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 (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.

Suggested Citation

  • Achim Ahrens & Christian B. Hansen & Mark E Schaffer, 2022. "PYSTACKED: Stata module for stacking generalization and machine learning in Stata," Statistical Software Components S459115, Boston College Department of Economics, revised 01 May 2023.
    • Handle: RePEc:boc:bocode:s459115
    Note: This module should be installed from within Stata by typing "ssc install pystacked". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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    File URL: http://fmwww.bc.edu/repec/bocode/p/pystacked.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/p/pystacked.py
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    File URL: http://fmwww.bc.edu/repec/bocode/p/pystacked.sthlp
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    File URL: http://fmwww.bc.edu/repec/bocode/p/pystacked_p.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/p/pystacked_p.py
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    File URL: http://fmwww.bc.edu/repec/bocode/_/_pyparse.ado
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