{"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/dipietro-hazari-kappa-a-novel-metric-for","title":"DiPietro-Hazari Kappa: A Novel Metric for Assessing Labeling Quality via Annotation","arxiv_id":"2209.08243","date":"2022-09-17","proceeding":null,"authors":["Daniel M. DiPietro","Vivek Hazari"],"abstract":"Data is a key component of modern machine learning, but statistics for assessing data label quality remain sparse in literature. Here, we introduce DiPietro-Hazari Kappa, a novel statistical metric for assessing the quality of suggested dataset labels in the context of human annotation. Rooted in the classical Fleiss's Kappa measure of inter-annotator agreement, the DiPietro-Hazari Kappa quantifies the the empirical annotator agreement differential that was attained above random chance. We offer a thorough theoretical examination of Fleiss's Kappa before turning to our derivation of DiPietro-Hazari Kappa. Finally, we conclude with a matrix formulation and set of procedural instructions for easy computational implementation.","url_abs":"https://arxiv.org/abs/2209.08243v1","url_pdf":"https://arxiv.org/pdf/2209.08243v1.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":"dipietro-hazari-kappa-a-novel-metric-for","repo_url":"https://github.com/dandip/dh_kappa","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"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}