https://github.com/tommoral/benchmark_classification

https://github.com/tommoral/benchmark_classification

Last synced: 7 days ago
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• Host: GitHub
• URL: https://github.com/tommoral/benchmark_classification
• Owner: tomMoral
• Created: 2022-12-04T22:32:12.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-09-26T22:56:29.000Z (about 2 months ago)
• Last Synced: 2024-11-02T09:51:36.914Z (14 days ago)
• Language: Python
• Size: 35.2 KB
• Stars: 4
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst

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README

        
Benchmark for classification methods

====================================

|Build Status| |Python 3.6+|

.. warning::

    This benchmark is under development and it only run with a dev version of

    benchopt, from this PR: https://github.com/benchopt/benchopt/pull/511

Benchopt is a package to simplify and make more transparent and

reproducible the comparisons of optimization algorithms.

This benchmark is dedicated to **tabular classification methods**:

$$\\min_{w} f(X, w)$$

where $n$ (or ``n_samples``) stands for the number of samples, $p$ (or ``n_features``) stands for the number of features and

$$X \\in \\mathbb{R}^{n \\times p} \\ , \\quad w \\in \\mathbb{R}^p$$

Install

--------

This benchmark can be run using the following commands:

.. code-block::

   $ pip install -U benchopt

   $ git clone https://github.com/tomMoral/benchmark_classification

   $ benchopt run benchmark_classification

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_classification -s solver1 -d dataset2 --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/tomMoral/benchmark_classification/workflows/Tests/badge.svg

   :target: https://github.com/tomMoral/benchmark_classification/actions

.. |Python 3.6+| image:: https://img.shields.io/badge/python-3.6%2B-blue

   :target: https://www.python.org/downloads/release/python-360/