{"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/the-fuzzy-roc","title":"The Fuzzy ROC","arxiv_id":"1903.01868","date":"2019-03-04","proceeding":null,"authors":["Giovanni Parmigiani"],"abstract":"The fuzzy ROC extends Receiver Operating Curve (ROC) visualization to the\nsituation where some data points, falling in an indeterminacy region, are not\nclassified. It addresses two challenges: definition of sensitivity and\nspecificity bounds under indeterminacy; and visual summarization of the large\nnumber of possibilities arising from different choices of indeterminacy zones.","url_abs":"http://arxiv.org/abs/1903.01868v1","url_pdf":"http://arxiv.org/pdf/1903.01868v1.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":"the-fuzzy-roc","repo_url":"https://github.com/gp1d/fuzzyROC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"sensitivity","task_name":"Sensitivity"},{"task_slug":"specificity","task_name":"Specificity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}