{"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/pool-based-sequential-active-learning-for","title":"Pool-Based Sequential Active Learning for Regression","arxiv_id":"1805.04735","date":"2018-05-12","proceeding":null,"authors":["Dongrui Wu"],"abstract":"Active learning is a machine learning approach for reducing the data labeling\neffort. Given a pool of unlabeled samples, it tries to select the most useful\nones to label so that a model built from them can achieve the best possible\nperformance. This paper focuses on pool-based sequential active learning for\nregression (ALR). We first propose three essential criteria that an ALR\napproach should consider in selecting the most useful unlabeled samples:\ninformativeness, representativeness, and diversity, and compare four existing\nALR approaches against them. We then propose a new ALR approach using passive\nsampling, which considers both the representativeness and the diversity in both\nthe initialization and subsequent iterations. Remarkably, this approach can\nalso be integrated with other existing ALR approaches in the literature to\nfurther improve the performance. Extensive experiments on 11 UCI, CMU StatLib,\nand UFL Media Core datasets from various domains verified the effectiveness of\nour proposed ALR approaches.","url_abs":"http://arxiv.org/abs/1805.04735v1","url_pdf":"http://arxiv.org/pdf/1805.04735v1.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":"pool-based-sequential-active-learning-for","repo_url":"https://github.com/drwuHUST/sAL","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"active-learning","task_name":"Active Learning"},{"task_slug":"diversity","task_name":"Diversity"},{"task_slug":"informativeness","task_name":"Informativeness"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.04735","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}