pystacked implements stacked generalization (Wolpert, 1992) for regression and binary classification via Python's scikit-lear}. 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.
|Publication status||Published - 23 Aug 2022|
- machine learning
- stacked generalization
- model averaging
- sci-kit learn