https://github.com/tommoral/stats-335_tabular_data

classification benchmark on tabular data for STATS 335
https://github.com/tommoral/stats-335_tabular_data

Last synced: 23 days ago
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classification benchmark on tabular data for STATS 335

• Host: GitHub
• URL: https://github.com/tommoral/stats-335_tabular_data
• Owner: tomMoral
• Created: 2023-11-16T00:38:43.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-11-29T18:18:23.000Z (12 months ago)
• Last Synced: 2023-11-29T19:31:51.190Z (12 months ago)
• Language: Python
• Size: 9.77 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst

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README

        
Benchmark for classification methods on tabular data

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

|Build Status| |Python 3.8+|

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**.

The objective is to compare the performance of different ML algorithms on

various tabular datasets. The performance are evaluated on the test set,

to evaluate the generalization performance of the algorithms.

Install

--------

This benchmark can be run using the following commands:

.. code-block::

   $ pip install -U benchopt

   $ git clone https://github.com/tomMoral/stats-335_tabular_data

   $ cd stats-335_tabular_data

   $ benchopt run

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 -s solver1 -d dataset2 --max-runs 10 --n-repetitions 1

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/stats-335_tabular_data/workflows/Tests/badge.svg

   :target: https://github.com/tomMoral/stats-335_tabular_data/actions

.. |Python 3.8+| image:: https://img.shields.io/badge/python-3.8%2B-blue

   :target: https://www.python.org/downloads/release/python-380/