{"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/liquidsvm-a-fast-and-versatile-svm-package","title":"liquidSVM: A Fast and Versatile SVM package","arxiv_id":"1702.06899","date":"2017-02-22","proceeding":null,"authors":["Ingo Steinwart","Philipp Thomann"],"abstract":"liquidSVM is a package written in C++ that provides SVM-type solvers for\nvarious classification and regression tasks. Because of a fully integrated\nhyper-parameter selection, very carefully implemented solvers, multi-threading\nand GPU support, and several built-in data decomposition strategies it provides\nunprecedented speed for small training sizes as well as for data sets of tens\nof millions of samples. Besides the C++ API and a command line interface,\nbindings to R, MATLAB, Java, Python, and Spark are available. We present a\nbrief description of the package and report experimental comparisons to other\nSVM packages.","url_abs":"http://arxiv.org/abs/1702.06899v1","url_pdf":"http://arxiv.org/pdf/1702.06899v1.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":"liquidsvm-a-fast-and-versatile-svm-package","repo_url":"https://github.com/liquidSVM/liquidSVM","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"AGPL-3.0"}}],"tasks":[{"task_slug":null,"task_name":"GPU"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1702.06899","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}