Description
Machine learning experiments can be built with a collection of algorithms for classification, regression, clustering, preprocessing, and data mining. This is useful for students, researchers, and analysts learning or comparing models on datasets.
It can be used through graphical and command-line workflows. Results depend on data quality and model choice, so treat predictions as analysis output that still needs validation.