Published December 21, 2023 | Version v1
Journal article Open

pystacked: Stacking generalization and machine learning in Stata

  • 1. ETH Zürich
  • 2. University of Chicago
  • 3. Heriot-Watt University

Description

The pystacked command implements stacked generalization (Wolpert, 1992, Neural Networks 5: 241–259) for regression and binary classification via Python's scikit-learn. Stacking combines multiple supervised machine learners—the "base" or "level-0" learners—into one 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 one base learner and thus provides an easy-to-use application programming interface for scikit-learn's machine learning algorithms.

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pystacked-Stacking-generalization-and-machine-learning-in-Stata.pdf

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Additional details

Identifiers

DOI
10.1177/1536867X231212426
Other
oai:uchicago.tind.io:10241

UChicago Information

Division(s)
Booth School of Business
Department(s)
Econometrics and Statistics