{"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/an-overview-and-a-benchmark-of-active","title":"An Overview and a Benchmark of Active Learning for Outlier Detection with One-Class Classifiers","arxiv_id":"1808.04759","date":"2018-08-14","proceeding":null,"authors":["Holger Trittenbach","Adrian Englhardt","Klemens Böhm"],"abstract":"Active learning methods increase classification quality by means of user feedback. An important subcategory is active learning for outlier detection with one-class classifiers. While various methods in this category exist, selecting one for a given application scenario is difficult. This is because existing methods rely on different assumptions, have different objectives, and often are tailored to a specific use case. All this calls for a comprehensive comparison, the topic of this article. This article starts with a categorization of the various methods. We then propose ways to evaluate active learning results. Next, we run extensive experiments to compare existing methods, for a broad variety of scenarios. Based on our results, we formulate guidelines on how to select active learning methods for outlier detection with one-class classifiers.","url_abs":"https://arxiv.org/abs/1808.04759v2","url_pdf":"https://arxiv.org/pdf/1808.04759v2.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":"an-overview-and-a-benchmark-of-active","repo_url":"https://github.com/englhardt/OneClassActiveLearning.jl","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"an-overview-and-a-benchmark-of-active","repo_url":"https://github.com/englhardt/SVDD.jl","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"an-overview-and-a-benchmark-of-active","repo_url":"https://github.com/kit-dbis/ocal-evaluation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"active-learning","task_name":"Active Learning"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"outlier-detection","task_name":"Outlier Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1808.04759","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}