Achim Ahrens, Christian B. Hansen, Mark E. Schaffer
arXiv 23 Aug 2022 · Econometrics · publishedThe Stata Journal Promoting communications on statistics and Stata (2023) · 31 citations (OpenAlex)
arXiv:2208.10896 · PDF · DOI · OpenAlex · Extracted main text
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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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Ahrens, A., C. B. Hansen, and M. E. Schaffer (2020) lassopack: Model selection and prediction with regularized regression in Stata self | 0.644 | 2 | 2 | 100% |
| 2 | Breiman, L (1996) Stacked regressions | 0.644 | 2 | 2 | 100% |
| 3 | Hastie, T., R. Tibshirani, and J. Friedman (2009) The Elements of Statistical Learning | 0.585 | 3 | 1 | 100% |
| 4 | Athey, S., and G. W. Imbens (2019) Machine learning methods that economists should know about | 0.405 | 1 | 1 | 100% |
| 5 | Chernozhukov, V., D. Chetverikov, M. Demirer, E. Duflo, C. Hansen, W… (2018) Double/debiased machine learning for treatment and structural parameters | 0.405 | 1 | 1 | 100% |
| 6 | Droste, M (2020) pylearn | 0.405 | 1 | 1 | 100% |
| 7 | Guenther, N., and M. Schonlau (2018) SVMACHINES: Stata module providing Support Vector Machines for both Classification and Regression | 0.405 | 1 | 1 | 100% |
| 8 | Huntington-Klein, N. C (2021) mlrtime | 0.405 | 1 | 1 | 100% |
| 9 | Pace, R. K., and R. Barry (1997) Sparse spatial autoregressions | 0.405 | 1 | 1 | 100% |
| 10 | van der Laan, M. J., E. C. Polley, and A. E. Hubbard (2007) Super Learner | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 25 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Nonparametric rich covariateswithout saturation | 0.644 | 2 | 2 |
| 2 | Model Averaging and Double Machine Learning | 0.405 | 1 | 1 |
| 3 | Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study | 0.405 | 1 | 1 |