{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/openml-an-r-package-to-connect-to-the-machine","title":"OpenML: An R Package to Connect to the Machine Learning Platform OpenML","arxiv_id":"1701.01293","date":"2017-01-05","proceeding":null,"authors":["Giuseppe Casalicchio","Jakob Bossek","Michel Lang","Dominik Kirchhoff","Pascal Kerschke","Benjamin Hofner","Heidi Seibold","Joaquin Vanschoren","Bernd Bischl"],"abstract":"OpenML is an online machine learning platform where researchers can easily\nshare data, machine learning tasks and experiments as well as organize them\nonline to work and collaborate more efficiently. In this paper, we present an R\npackage to interface with the OpenML platform and illustrate its usage in\ncombination with the machine learning R package mlr. We show how the OpenML\npackage allows R users to easily search, download and upload data sets and\nmachine learning tasks. Furthermore, we also show how to upload results of\nexperiments, share them with others and download results from other users.\nBeyond ensuring reproducibility of results, the OpenML platform automates much\nof the drudge work, speeds up research, facilitates collaboration and increases\nthe users' visibility online.","url_abs":"http://arxiv.org/abs/1701.01293v2","url_pdf":"http://arxiv.org/pdf/1701.01293v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"openml-an-r-package-to-connect-to-the-machine","repo_url":"https://github.com/mlr-org/mlr","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1701.01293","atlas_url":"https://app.syntology.ai/?focus=1701.01293","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}