{"id":20841052,"url":"https://github.com/benchopt/benchmark_quantile_regression","last_synced_at":"2025-04-10T13:54:16.220Z","repository":{"id":42862402,"uuid":"352781537","full_name":"benchopt/benchmark_quantile_regression","owner":"benchopt","description":"Benchopt benchmark for Quantile Regression","archived":false,"fork":false,"pushed_at":"2023-07-05T08:30:24.000Z","size":18,"stargazers_count":0,"open_issues_count":5,"forks_count":4,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-03-24T12:39:28.439Z","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}},"created_at":"2021-03-29T20:52:24.000Z","updated_at":"2021-12-02T20:38:20.000Z","dependencies_parsed_at":"2023-01-25T21:45:41.658Z","dependency_job_id":null,"html_url":"https://github.com/benchopt/benchmark_quantile_regression","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":"benchopt/template_benchmark","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_quantile_regression","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_quantile_regression/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_quantile_regression/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benchopt%2Fbenchmark_quantile_regression/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/benchopt","download_url":"https://codeload.github.com/benchopt/benchmark_quantile_regression/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248229335,"owners_count":21068878,"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":[],"created_at":"2024-11-18T01:18:39.153Z","updated_at":"2025-04-10T13:54:16.196Z","avatar_url":"https://github.com/benchopt.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"Quantile Regression Benchmark\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.\nThis benchmark is dedicated to the the L1-regularized quantile regression problem:\n\n\n$$\\\\min_{\\\\beta, \\\\beta_0} \\\\frac{1}{n} \\\\sum_{i=1}^{n} \\\\text{pinball}(y_i, x_i^\\\\top \\\\beta + \\\\beta_0) + \\\\lambda \\\\lVert \\\\beta \\\\rVert_1$$\n\nwhere\n\n$$\\\\text{pinball}(y, \\\\hat{y}) = \\\\alpha \\\\max(y - \\\\hat{y}, 0) + (1 - \\\\alpha) \\\\max(\\\\hat{y} - y, 0)$$\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$$X = [x_1^\\\\top, \\\\dots, x_n^\\\\top]^\\\\top \\\\in \\\\mathbb{R}^{n \\\\times p}$$\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_quantile_regression\n   $ benchopt run benchmark_quantile_regression\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 benchmark_quantile_regression -s scipy -d simulated --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.. |Build Status| image:: https://github.com/benchopt/benchmark_quantile_regression/workflows/Tests/badge.svg\n   :target: https://github.com/benchopt/benchmark_quantile_regression/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_quantile_regression","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbenchopt%2Fbenchmark_quantile_regression","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenchopt%2Fbenchmark_quantile_regression/lists"}