In this study, we investigate and summarize the performance of a wide range of ML algorithms (using its default hyper-parameter values) on a wide range of OpenML classifications tasks. This will yield a meta-dataset that can be leveraged for algorithm selection and many future studies into learning performance.
Fork the study on [github](https://github.com/openml/study_example), or run it by everware: [](https://everware.rep.school.yandex.net/hub/oauth_login?repourl=https://github.com/openml/study_example)