{"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/rgtsvm-support-vector-machines-on-a-gpu-in-r","title":"Rgtsvm: Support Vector Machines on a GPU in R","arxiv_id":"1706.05544","date":"2017-06-17","proceeding":null,"authors":["Zhong Wang","Tinyi Chu","Lauren A Choate","Charles G Danko"],"abstract":"Rgtsvm provides a fast and flexible support vector machine (SVM)\nimplementation for the R language. The distinguishing feature of Rgtsvm is that\nsupport vector classification and support vector regression tasks are\nimplemented on a graphical processing unit (GPU), allowing the libraries to\nscale to millions of examples with >100-fold improvement in performance over\nexisting implementations. Nevertheless, Rgtsvm retains feature parity and has\nan interface that is compatible with the popular e1071 SVM package in R.\nAltogether, Rgtsvm enables large SVM models to be created by both experienced\nand novice practitioners.","url_abs":"http://arxiv.org/abs/1706.05544v1","url_pdf":"http://arxiv.org/pdf/1706.05544v1.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":"rgtsvm-support-vector-machines-on-a-gpu-in-r","repo_url":"https://github.com/Danko-Lab/Rgtsvm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":null,"task_name":"GPU"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":"svm","method_name":"SVM"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}