{"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/penalizing-unfairness-in-binary","title":"Penalizing Unfairness in Binary Classification","arxiv_id":"1707.00044","date":"2017-06-30","proceeding":null,"authors":["Yahav Bechavod","Katrina Ligett"],"abstract":"We present a new approach for mitigating unfairness in learned classifiers.\nIn particular, we focus on binary classification tasks over individuals from\ntwo populations, where, as our criterion for fairness, we wish to achieve\nsimilar false positive rates in both populations, and similar false negative\nrates in both populations. As a proof of concept, we implement our approach and\nempirically evaluate its ability to achieve both fairness and accuracy, using\ndatasets from the fields of criminal risk assessment, credit, lending, and\ncollege admissions.","url_abs":"http://arxiv.org/abs/1707.00044v3","url_pdf":"http://arxiv.org/pdf/1707.00044v3.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":"penalizing-unfairness-in-binary","repo_url":"https://github.com/jjgold012/lab-project-fairness","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"penalizing-unfairness-in-binary","repo_url":"https://github.com/hyungrok-do/fair-glm-cvx","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"binary-classification","task_name":"Binary Classification"},{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"fairness","task_name":"Fairness"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1707.00044","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1707.00044"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jjgold012/lab-project-fairness","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/hyungrok-do/fair-glm-cvx","reach":null}],"summary":{"ran_draft_wrong":1,"unverified":1},"by_repo_kind":{"official":{"samples":2,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":2,"samples":[{"code_sha256_prefix":"127a7b514869d39c","entry":"process_line","repo":"jjgold012/lab-project-fairness","repo_kind":"official","path":"fairness_project/start.py","file_url":"https://github.com/jjgold012/lab-project-fairness/blob/HEAD/fairness_project/start.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"127a7b514869d39c"}},{"code_sha256_prefix":"fbe10a34e18ad421","entry":"load_problem_from_options","repo":"jjgold012/lab-project-fairness","repo_kind":"official","path":"fairness_project/start.py","file_url":"https://github.com/jjgold012/lab-project-fairness/blob/HEAD/fairness_project/start.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"fbe10a34e18ad421"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}