Abstract
A new study on Machine Learning is now available. According to news reporting originating from Zurich, Switzerland, by NewsRx correspondents, research stated, “The pystacked command implements stacked generalization (Wolpert, 1992, Neural Networks 5: 241-259) for regression and binary classification via Python’s scikit-learn.” Our news editors obtained a quote from the research from the Swiss Federal Institute of Technology, “Stacking combines multiple supervised machine learners-the ‘base’ or ‘level-0’ learners-into one learner.” According to the news editors, the research concluded: “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.”
NETL
NSTL
Sage