{"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/apsis-framework-for-automated-optimization-of","title":"apsis - Framework for Automated Optimization of Machine Learning Hyper Parameters","arxiv_id":"1503.02946","date":"2015-03-10","proceeding":null,"authors":["Frederik Diehl","Andreas Jauch"],"abstract":"The apsis toolkit presented in this paper provides a flexible framework for\nhyperparameter optimization and includes both random search and a bayesian\noptimizer. It is implemented in Python and its architecture features\nadaptability to any desired machine learning code. It can easily be used with\ncommon Python ML frameworks such as scikit-learn. Published under the MIT\nLicense other researchers are heavily encouraged to check out the code,\ncontribute or raise any suggestions. The code can be found at\ngithub.com/FrederikDiehl/apsis.","url_abs":"http://arxiv.org/abs/1503.02946v2","url_pdf":"http://arxiv.org/pdf/1503.02946v2.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":"apsis-framework-for-automated-optimization-of","repo_url":"https://github.com/FrederikDiehl/apsis","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"hyperparameter-optimization","task_name":"Hyperparameter Optimization"}],"methods":[{"method_slug":"random-search","method_name":"Random Search"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}