{"id":20841046,"url":"https://github.com/benchopt/benchmark_cox","last_synced_at":"2026-04-20T18:32:27.134Z","repository":{"id":169312138,"uuid":"644903095","full_name":"benchopt/benchmark_cox","owner":"benchopt","description":"Benchmark of Cox Estimation for survival analysis","archived":false,"fork":false,"pushed_at":"2023-12-06T08:01:49.000Z","size":25,"stargazers_count":0,"open_issues_count":0,"forks_count":2,"subscribers_count":1,"default_branch":"main","last_synced_at":"2026-01-14T11:15:21.192Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/benchopt.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2023-05-24T13:46:56.000Z","updated_at":"2023-06-13T08:15:13.000Z","dependencies_parsed_at":null,"dependency_job_id":"cedd1407-4e84-4625-b0af-19d1ad42b690","html_url":"https://github.com/benchopt/benchmark_cox","commit_stats":null,"previous_names":["badr-moufad/benchmark_cox","benchopt/benchmark_l1_cox"],"tags_count":0,"template":false,"template_full_name":"benchopt/template_benchmark","purl":"pkg:github/benchopt/benchmark_cox","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_cox","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_cox/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_cox/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_cox/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/benchopt","download_url":"https://codeload.github.com/benchopt/benchmark_cox/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_cox/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32059761,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-20T11:35:06.609Z","status":"ssl_error","status_checked_at":"2026-04-20T11:34:48.899Z","response_time":94,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-18T01:18:37.874Z","updated_at":"2026-04-20T18:32:27.119Z","avatar_url":"https://github.com/benchopt.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"Benchmark for Cox estimation\n===============================\n|Build Status| |Python 3.6+|\n\n\nThis benchmark is dedicated to solver of **Cox estimation**:\n\n\n$$\n\\\\min_{w} \\\\frac{1}{n} \\\\sum_{i=1}^{n} -s_i \\\\langle x_i, w \\\\rangle + \\\\log(\\\\textstyle\\\\sum_{y_j \\\\geq y_i} e^{\\\\langle x_j, w \\\\rangle})\n+ \\\\lambda \\\\Big( \\\\rho \\\\lVert w \\\\rVert_1 + \\\\frac{1-\\\\rho}{2} \\\\lVert w \\\\rVert^2_2 \\\\Big)\n$$\n\nwhere $n$ (or ``n_samples``) stands for the number of samples, $p$ (or ``n_features``) stands for the number of features, $s$ the vector of observation censorship, $y$ occurrences times.\n\n\n$$\\\\mathbf{X} \\\\in \\\\mathbb{R}^{n \\\\times p} \\\\ , \\\\, s \\\\in \\\\{ 0, 1 \\\\}^n, \\\\ y \\\\in \\\\mathbb{R}^n, \\\\quad w \\\\in \\\\mathbb{R}^p$$\n\n\nIn the case of tied data, data with observation having the same occurrences time, the objective reads\n\n$$\n\\\\min_{w} \\\\frac{1}{n} \\\\sum_{l=1}^{m} \\\\bigg(\n\\\\sum_{i \\\\in H_{i_l}} - \\\\langle x_i, w \\\\rangle \n+ \\\\log \\\\Bigl(\\\\textstyle \\\\sum_{y_j \\\\geq y_{i_l}} e^{\\\\langle x_j, w \\\\rangle} - \\\\frac{\\\\#(i) - 1}{\\\\lvert H_{i_l} \\\\rvert}\\\\textstyle\\\\sum_{j \\\\in H_{i_l}} e^{\\\\langle x_j, w \\\\rangle}\\\\Bigl)\n\\\\bigg)\n+ \\\\lambda \\\\Big( \\\\rho \\\\lVert w \\\\rVert_1 + \\\\frac{1-\\\\rho}{2} \\\\lVert w \\\\rVert^2_2 \\\\Big)\n$$\n\nwhere $H_{i_l} = \\\\{ i \\\\ | \\\\ s_i = 1 \\\\ ;\\\\ y_{i} = y_{i_l} \\\\}$ is the set of uncensored observations with same occurrence time $y_{i_l}$ and $\\\\#(i)$ the index of observation $i$ in $H_{i_l}$.\n\n\nInstall\n--------\n\nThis benchmark can be run using the following commands:\n\n.. code-block::\n\n   $ pip install -U benchopt\n   $ git clone https://github.com/benchopt/benchmark_l1_cox\n   $ cd benchmark_l1_cox\n   $ benchopt run .\n\nApart from the problem, options can be passed to ``benchopt run``, to restrict the benchmarks to some solvers or datasets, e.g.:\n\n.. code-block::\n\n\t$ benchopt run . -s solver1 -d dataset2 --max-runs 10 --n-repetitions 10\n\n\nUse ``benchopt run -h`` for more details about these options, or visit https://benchopt.github.io/api.html.\n\n\n.. |Build Status| image:: https://github.com/benchopt/benchmark_l1_cox/workflows/Tests/badge.svg\n   :target: https://github.com/#ORG/#BENCHMARK_NAME/actions\n.. |Python 3.6+| image:: https://img.shields.io/badge/python-3.6%2B-blue\n   :target: https://www.python.org/downloads/release/python-360/\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenchopt%2Fbenchmark_cox","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbenchopt%2Fbenchmark_cox","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenchopt%2Fbenchmark_cox/lists"}