{"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/using-svm-to-pre-classify-government","title":"Using SVM to pre-classify government purchases","arxiv_id":"1601.02680","date":"2015-12-07","proceeding":null,"authors":["Thiago Marzagão"],"abstract":"The Brazilian government often misclassifies the goods it buys. That makes it\nhard to audit government expenditures. We cannot know whether the price paid\nfor a ballpoint pen (code #7510) was reasonable if the pen was misclassified as\na technical drawing pen (code #6675) or as any other good. This paper shows how\nwe can use machine learning to reduce misclassification. I trained a support\nvector machine (SVM) classifier that takes a product description as input and\nreturns the most likely category codes as output. I trained the classifier\nusing 20 million goods purchased by the Brazilian government between 1999-04-01\nand 2015-04-02. In 83.3% of the cases the correct category code was one of the\nthree most likely category codes identified by the classifier. I used the\ntrained classifier to develop a web app that might help the government reduce\nmisclassification. I open sourced the code on GitHub; anyone can use and modify\nit.","url_abs":"http://arxiv.org/abs/1601.02680v1","url_pdf":"http://arxiv.org/pdf/1601.02680v1.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":"using-svm-to-pre-classify-government","repo_url":"https://github.com/thiagomarzagao/catmatfinder","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}