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.