{"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/conformal-risk-control-for-ordinal","title":"Conformal Risk Control for Ordinal Classification","arxiv_id":"2405.00417","date":"2024-05-01","proceeding":null,"authors":["Yunpeng Xu","Wenge Guo","Zhi Wei"],"abstract":"As a natural extension to the standard conformal prediction method, several conformal risk control methods have been recently developed and applied to various learning problems. In this work, we seek to control the conformal risk in expectation for ordinal classification tasks, which have broad applications to many real problems. For this purpose, we firstly formulated the ordinal classification task in the conformal risk control framework, and provided theoretic risk bounds of the risk control method. Then we proposed two types of loss functions specially designed for ordinal classification tasks, and developed corresponding algorithms to determine the prediction set for each case to control their risks at a desired level. We demonstrated the effectiveness of our proposed methods, and analyzed the difference between the two types of risks on three different datasets, including a simulated dataset, the UTKFace dataset and the diabetic retinopathy detection dataset.","url_abs":"https://arxiv.org/abs/2405.00417v1","url_pdf":"https://arxiv.org/pdf/2405.00417v1.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":"conformal-risk-control-for-ordinal","repo_url":"https://github.com/yx8njit/ordinal-conformal-risk-control","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"conformal-prediction","task_name":"Conformal Prediction"},{"task_slug":"diabetic-retinopathy-detection","task_name":"Diabetic Retinopathy Detection"},{"task_slug":"ordinal-classification","task_name":"Ordinal Classification"}],"methods":[{"method_slug":"set","method_name":"SET"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2405.00417","atlas_url":"https://app.syntology.ai/?focus=2405.00417","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.00417"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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/yx8njit/ordinal-conformal-risk-control","reach":{"status":"ok"}}],"summary":{"ran":3},"by_repo_kind":{"official":{"samples":3,"ran":3,"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":3,"samples":[{"code_sha256_prefix":"b9d7b55adc7169f0","entry":"convert2softmax","repo":"yx8njit/ordinal-conformal-risk-control","repo_kind":"official","path":"experiment.py","file_url":"https://github.com/yx8njit/ordinal-conformal-risk-control/blob/HEAD/experiment.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"b9d7b55adc7169f0"}},{"code_sha256_prefix":"84c81a52278c0502","entry":"load_raw_fyxs","repo":"yx8njit/ordinal-conformal-risk-control","repo_kind":"official","path":"experiment.py","file_url":"https://github.com/yx8njit/ordinal-conformal-risk-control/blob/HEAD/experiment.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"84c81a52278c0502"}},{"code_sha256_prefix":"d8c6ad7b1c3705c4","entry":"random_split_data","repo":"yx8njit/ordinal-conformal-risk-control","repo_kind":"official","path":"experiment.py","file_url":"https://github.com/yx8njit/ordinal-conformal-risk-control/blob/HEAD/experiment.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"d8c6ad7b1c3705c4"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}