pystacked: Stacking generalization and machine learning in Stata
Econometrics
2023-03-07 v2 Machine Learning
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.
Cite
@article{arxiv.2208.10896,
title = {pystacked: Stacking generalization and machine learning in Stata},
author = {Achim Ahrens and Christian B. Hansen and Mark E. Schaffer},
journal= {arXiv preprint arXiv:2208.10896},
year = {2023}
}
Comments
The pystacked package is available here: https://github.com/aahrens1/pystacked