Stacked generalization with pystacked #

pystacked implements stacked generalization (Wolpert, 1992) via scikit-learn’s sklearn.ensemble.StackingRegressor and sklearn.ensemble.StackingClassifier. Stacking is a way of combining predictions from multiple supervised machine learners (the “base learners”) into a final prediction to improve performance. The currently-supported base learners are:

  • Linear regression
  • Logistic regression
  • Lasso, ridge and elastic net
  • Support vector machines
  • Gradient boosted trees
  • Random forest
  • Neural nets (Multi-layer Perceptron)

pystacked can also be used with a single base learner and, thus, provides an easy-to-use API for scikit-learn’s machine learning algorithms.

pystacked has just been released (October 2021). Please try it out and let us know if you run into problems. Feedback welcome and appreciated.