{"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/essential-guidelines-for-computational-method","title":"Essential guidelines for computational method benchmarking","arxiv_id":"1812.00661","date":"2018-12-03","proceeding":null,"authors":["Lukas M. Weber","Wouter Saelens","Robrecht Cannoodt","Charlotte Soneson","Alexander Hapfelmeier","Paul Gardner","Anne-Laure Boulesteix","Yvan Saeys","Mark D. Robinson"],"abstract":"In computational biology and other sciences, researchers are frequently faced\nwith a choice between several computational methods for performing data\nanalyses. Benchmarking studies aim to rigorously compare the performance of\ndifferent methods using well-characterized benchmark datasets, to determine the\nstrengths of each method or to provide recommendations regarding the best\nchoice of method for an analysis. However, benchmarking studies must be\ncarefully designed and implemented to provide accurate and unbiased results.\nHere, we summarize key practical guidelines and recommendations for performing\nhigh-quality benchmarking analyses, based on our own experiences in\ncomputational biology.","url_abs":"http://arxiv.org/abs/1812.00661v2","url_pdf":"http://arxiv.org/pdf/1812.00661v2.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":"essential-guidelines-for-computational-method","repo_url":"https://github.com/chloroExtractorTeam/benchmark","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"benchmarking","task_name":"Benchmarking"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1812.00661","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}