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arXiv · 2208.10896

pystacked: Stacking generalization and machine learning in Stata

Achim Ahrens·Christian B. Hansen·Mark E. Schaffer
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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 (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.

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BibTeXRIS

Achim Ahrens, Christian B. Hansen, Mark E. Schaffer. 2022-08-23. pystacked: Stacking generalization and machine learning in Stata. https://arxiv.org/abs/2208.10896

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