{"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/data-driven-advice-for-applying-machine","title":"Data-driven Advice for Applying Machine Learning to Bioinformatics Problems","arxiv_id":"1708.05070","date":"2017-08-08","proceeding":null,"authors":["Randal S. Olson","William La Cava","Zairah Mustahsan","Akshay Varik","Jason H. Moore"],"abstract":"As the bioinformatics field grows, it must keep pace not only with new data\nbut with new algorithms. Here we contribute a thorough analysis of 13\nstate-of-the-art, commonly used machine learning algorithms on a set of 165\npublicly available classification problems in order to provide data-driven\nalgorithm recommendations to current researchers. We present a number of\nstatistical and visual comparisons of algorithm performance and quantify the\neffect of model selection and algorithm tuning for each algorithm and dataset.\nThe analysis culminates in the recommendation of five algorithms with\nhyperparameters that maximize classifier performance across the tested\nproblems, as well as general guidelines for applying machine learning to\nsupervised classification problems.","url_abs":"http://arxiv.org/abs/1708.05070v2","url_pdf":"http://arxiv.org/pdf/1708.05070v2.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":"data-driven-advice-for-applying-machine","repo_url":"https://github.com/rhiever/sklearn-benchmarks","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"data-driven-advice-for-applying-machine","repo_url":"https://github.com/stevensmiley1989/BreastCancer","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"model-selection","task_name":"Model Selection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}