{"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/faster-convergence-with-lexicase-selection-in","title":"Faster Convergence with Lexicase Selection in Tree-based Automated Machine Learning","arxiv_id":"2302.00731","date":"2023-02-01","proceeding":null,"authors":["Nicholas Matsumoto","Anil Kumar Saini","Pedro Ribeiro","Hyunjun Choi","Alena Orlenko","Leo-Pekka Lyytikäinen","Jari O Laurikka","Terho Lehtimäki","Sandra Batista","Jason H. Moore"],"abstract":"In many evolutionary computation systems, parent selection methods can affect, among other things, convergence to a solution. In this paper, we present a study comparing the role of two commonly used parent selection methods in evolving machine learning pipelines in an automated machine learning system called Tree-based Pipeline Optimization Tool (TPOT). Specifically, we demonstrate, using experiments on multiple datasets, that lexicase selection leads to significantly faster convergence as compared to NSGA-II in TPOT. We also compare the exploration of parts of the search space by these selection methods using a trie data structure that contains information about the pipelines explored in a particular run.","url_abs":"https://arxiv.org/abs/2302.00731v1","url_pdf":"https://arxiv.org/pdf/2302.00731v1.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":"faster-convergence-with-lexicase-selection-in","repo_url":"https://github.com/epistasislab/exploration-trie-tpot","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}