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.
CITATION STYLE
Ahrens, A., Hansen, C. B., & Schaffer, M. E. (2023). pystacked: Stacking generalization and machine learning in Stata. Stata Journal, 23(4), 909–931. https://doi.org/10.1177/1536867X231212426
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