https://github.com/benchopt/benchmark_logreg_l1
Benchopt benchmark for Sparse Logistic Regression
https://github.com/benchopt/benchmark_logreg_l1
benchmark optimization
Last synced: 11 months ago
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Benchopt benchmark for Sparse Logistic Regression
- Host: GitHub
- URL: https://github.com/benchopt/benchmark_logreg_l1
- Owner: benchopt
- Created: 2020-09-08T16:47:58.000Z (almost 6 years ago)
- Default Branch: main
- Last Pushed: 2024-02-16T10:45:51.000Z (over 2 years ago)
- Last Synced: 2025-05-08T22:06:08.792Z (about 1 year ago)
- Topics: benchmark, optimization
- Language: Python
- Homepage: https://benchopt.github.io
- Size: 43.9 KB
- Stars: 1
- Watchers: 3
- Forks: 8
- Open Issues: 1
-
Metadata Files:
- Readme: README.rst
Awesome Lists containing this project
README
Benchmark repository for Sparse Logistic Regression
===================================================
|Build Status| |Python 3.6+|
Benchopt is a package to simplify and make more transparent and
reproducible the comparisons of optimization algorithms. This benchmark tests algorithms to solve the following problem:
$$\\min_w \\sum_i \\log(1 + \\exp(-y_i x_i^\\top w)) + \\lambda \\lVert w\\rVert_1$$
where $n$ (or ``n_samples``) stands for the number of samples, $p$ (or ``n_features``) stands for the number of features, and
$$y \\in \\mathbb{R}^n, X = [x_1^\\top, \\dots, x_n^\\top]^\\top \\in \\mathbb{R}^{n \\times p}$$
Install
--------
This benchmark can be run using the following commands:
.. code-block::
$ pip install -U benchopt
$ git clone https://github.com/benchopt/benchmark_logreg_l1
$ benchopt run benchmark_logreg_l1
Apart from the problem, options can be passed to ``benchopt run``, to restrict the benchmarks to some solvers or datasets, e.g.:
.. code-block::
$ benchopt run benchmark_logreg_l1 -s sklearn -d boston --max-runs 10 --n-repetitions 10
Use ``benchopt run -h`` for more details about these options, or visit https://benchopt.github.io/api.html.
.. |Build Status| image:: https://github.com/benchopt/benchmark_logreg_l1/workflows/Tests/badge.svg
:target: https://github.com/benchopt/benchmark_logreg_l1/actions
.. |Python 3.6+| image:: https://img.shields.io/badge/python-3.6%2B-blue
:target: https://www.python.org/downloads/release/python-360/