{"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/libact-pool-based-active-learning-in-python","title":"libact: Pool-based Active Learning in Python","arxiv_id":"1710.00379","date":"2017-10-01","proceeding":null,"authors":["Yao-Yuan Yang","Shao-Chuan Lee","Yu-An Chung","Tung-En Wu","Si-An Chen","Hsuan-Tien Lin"],"abstract":"libact is a Python package designed to make active learning easier for\ngeneral users. The package not only implements several popular active learning\nstrategies, but also features the active-learning-by-learning meta-algorithm\nthat assists the users to automatically select the best strategy on the fly.\nFurthermore, the package provides a unified interface for implementing more\nstrategies, models and application-specific labelers. The package is\nopen-source on Github, and can be easily installed from Python Package Index\nrepository.","url_abs":"http://arxiv.org/abs/1710.00379v1","url_pdf":"http://arxiv.org/pdf/1710.00379v1.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":"libact-pool-based-active-learning-in-python","repo_url":"https://github.com/ntucllab/libact","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"libact-pool-based-active-learning-in-python","repo_url":"https://github.com/CFEL-CMI/Active-Learning-of-PES","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"libact-pool-based-active-learning-in-python","repo_url":"https://github.com/SimiPixel/pool_based_active_learning","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"libact-pool-based-active-learning-in-python","repo_url":"https://github.com/melkherj/puddle","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"libact-pool-based-active-learning-in-python","repo_url":"https://github.com/swanjing/Contextual-Bandits-Active-Learning","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"active-learning","task_name":"Active Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1710.00379","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}