{"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/classification-via-local-manifold","title":"Classification via local manifold approximation","arxiv_id":"1903.00985","date":"2019-03-03","proceeding":null,"authors":["Didong Li","David B. Dunson"],"abstract":"Classifiers label data as belonging to one of a set of groups based on input\nfeatures. It is challenging to obtain accurate classification performance when\nthe feature distributions in the different classes are complex, with nonlinear,\noverlapping and intersecting supports. This is particularly true when training\ndata are limited. To address this problem, this article proposes a new type of\nclassifier based on obtaining a local approximation to the support of the data\nwithin each class in a neighborhood of the feature to be classified, and\nassigning the feature to the class having the closest support. This general\nalgorithm is referred to as LOcal Manifold Approximation (LOMA) classification.\nAs a simple and theoretically supported special case having excellent\nperformance in a broad variety of examples, we use spheres for local\napproximation, obtaining a SPherical Approximation (SPA) classifier. We\nillustrate substantial gains for SPA over competitors on a variety of\nchallenging simulated and real data examples.","url_abs":"http://arxiv.org/abs/1903.00985v1","url_pdf":"http://arxiv.org/pdf/1903.00985v1.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":"classification-via-local-manifold","repo_url":"https://github.com/david-dunson/SPAclassifier","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"single-particle-analysis","task_name":"Single Particle Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}