{"id":20841064,"url":"https://github.com/benchopt/benchmark_logreg_l1","last_synced_at":"2025-07-18T06:35:51.137Z","repository":{"id":38185004,"uuid":"293871287","full_name":"benchopt/benchmark_logreg_l1","owner":"benchopt","description":"Benchopt benchmark for Sparse Logistic Regression","archived":false,"fork":false,"pushed_at":"2024-02-16T10:45:51.000Z","size":45,"stargazers_count":1,"open_issues_count":1,"forks_count":8,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-05-08T22:06:08.792Z","etag":null,"topics":["benchmark","optimization"],"latest_commit_sha":null,"homepage":"https://benchopt.github.io","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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2020-09-08T16:47:58.000Z","updated_at":"2023-04-11T15:31:50.000Z","dependencies_parsed_at":"2024-02-16T11:38:08.566Z","dependency_job_id":"8be8f1ea-2e9c-4db7-8018-528c56e446ad","html_url":"https://github.com/benchopt/benchmark_logreg_l1","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/benchopt/benchmark_logreg_l1","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_logreg_l1","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_logreg_l1/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_logreg_l1/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_logreg_l1/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/benchopt","download_url":"https://codeload.github.com/benchopt/benchmark_logreg_l1/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_logreg_l1/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265711084,"owners_count":23815468,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["benchmark","optimization"],"created_at":"2024-11-18T01:18:40.368Z","updated_at":"2025-07-18T06:35:51.105Z","avatar_url":"https://github.com/benchopt.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"Benchmark repository for Sparse Logistic Regression\n===================================================\n\n|Build Status| |Python 3.6+|\n\nBenchopt is a package to simplify and make more transparent and\nreproducible the comparisons of optimization algorithms. This benchmark tests algorithms to solve the following problem:\n\n\n$$\\\\min_w \\\\sum_i \\\\log(1 + \\\\exp(-y_i x_i^\\\\top w)) + \\\\lambda \\\\lVert w\\\\rVert_1$$\n\nwhere $n$ (or ``n_samples``) stands for the number of samples, $p$ (or ``n_features``) stands for the number of features, and\n\n$$y \\\\in \\\\mathbb{R}^n, X = [x_1^\\\\top, \\\\dots, x_n^\\\\top]^\\\\top \\\\in \\\\mathbb{R}^{n \\\\times p}$$\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_logreg_l1\n   $ benchopt run benchmark_logreg_l1\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   $ benchopt run benchmark_logreg_l1 -s sklearn -d boston --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_logreg_l1/workflows/Tests/badge.svg\n   :target: https://github.com/benchopt/benchmark_logreg_l1/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_logreg_l1","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbenchopt%2Fbenchmark_logreg_l1","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenchopt%2Fbenchmark_logreg_l1/lists"}