pystacked: Stacking generalization and machine learning in Stata

• Autores: Achim Ahrens, Christian B. Hansen, Mark E. Schaffer
• Localización: The Stata journal, ISSN 1536-867X, Vol. 23, Nº. 4, 2023, págs. 909-931
• Idioma: inglés
• Enlaces
  • Texto completo
• Resumen

  • 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.