semvec/pypi-packages huggingface dataset:
evofs 1.4.0
Multi-objective evolutionary feature selection.
License: Apache 2.0

EvoFS: Multi-objective evolutionary feature selection
======================================================

|Build|
|Coverage|

|PyPI license|
|PyPI-version|



.. |Build| image:: https://img.shields.io/travis/pietrobarbiero/evofs?label=Master%20Build&style=for-the-badge
    :alt: Travis (.org)
    :target: https://travis-ci.org/pietrobarbiero/evofs

.. |Coverage| image:: https://img.shields.io/codecov/c/gh/pietrobarbiero/evofs?label=Test%20Coverage&style=for-the-badge
    :alt: Codecov
    :target: https://codecov.io/gh/pietrobarbiero/evofs

.. |PyPI license| image:: https://img.shields.io/pypi/l/evofs.svg?style=for-the-badge
   :target: https://pypi.python.org/pypi/evofs/

.. |PyPI-version| image:: https://img.shields.io/pypi/v/evofs?style=for-the-badge
    :alt: PyPI
    :target: https://pypi.python.org/pypi/evofs/

EvoFS is a python package providing a sklearn-like transformer
for multi-objective evolutionary feature selection.

Quick start
-----------

You can install EvoFS along with all its dependencies from
`PyPI <https://pypi.org/project/evofs/>`__:

.. code:: bash

    $ pip install evofs


Citing
----------

If you find EovFS useful in your research, please consider citing the following paper::

    @inproceedings{barbiero2019novel,
      title={A Novel Outlook on Feature Selection as a Multi-objective Problem},
      author={Barbiero, Pietro and Lutton, Evelyne and Squillero, Giovanni and Tonda, Alberto},
      booktitle={International Conference on Artificial Evolution (Evolution Artificielle)},
      pages={68--81},
      year={2019},
      organization={Springer}
    }

Source
------

The source code and minimal working examples can be found on
`GitHub <https://github.com/pietrobarbiero/moea-feature-selection>`__.


Running tests
-------------

You can run all unittests from command line by using python:

.. code:: bash

    $ python -m unittest discover

or coverage:

.. code:: bash

    $ coverage run -m unittest discover


Authors
-------

`Pietro Barbiero <http://www.pietrobarbiero.eu/>`__,
`Giovanni Squillero <https://staff.polito.it/giovanni.squillero/>`__,
and
`Alberto Tonda <https://www.researchgate.net/profile/Alberto_Tonda>`__.

Licence
-------

Copyright 2020 Pietro Barbiero, Giovanni Squillero, and Alberto Tonda.

Licensed under the Apache License, Version 2.0 (the "License"); you may
not use this file except in compliance with the License. You may obtain
a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0.

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

See the License for the specific language governing permissions and
limitations under the License.