.. MAFESE documentation master file, created by
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Welcome to MAFESE's documentation!
==================================

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MAFESE (Metaheuristic Algorithms for FEature SElection) is the largest python library focused on feature selection
using meta-heuristic algorithms.

* **Free software:** GNU General Public License (GPL) V3 license
* **Total Wrapper-based (Metaheuristic Algorithms)**: > 200 methods
* **Total Filter-based (Statistical-based)**: > 15 methods
* **Total Embedded-based (Tree and Lasso)**: > 10 methods
* **Total Unsupervised-based**: >= 4 methods
* **Total datasets**: >= 30 (47 classifications and 7 regressions)
* **Total performance metrics**: >= 61 (45 regressions and 16 classifications)
* **Total objective functions (as fitness functions)**: >= 61 (45 regressions and 16 classifications)
* **Documentation:** https://mafese.readthedocs.io/en/latest/
* **Python versions:** >= 3.8.x
* **Dependencies:** numpy, scipy, scikit-learn, pandas, mealpy, permetrics, plotly, kaleido


Features
--------

- Our library provides all state-of-the-art feature selection methods:
   + Filter-based FS
   + Embedded-based FS
      + Regularization (Lasso-based)
      + Tree-based methods
   + Wrapper-based FS
      + Sequential-based: forward and backward
      + Recursive-based
      + MHA-based: Metaheuristic Algorithms
   + Unsupervised-based FS
- We have implemented all feature selection methods based on scipy, scikit-learn and numpy to increase the speed of the algorithms.


.. toctree::
   :maxdepth: 4
   :caption: Quick Start:

   pages/quick_start.rst

.. toctree::
   :maxdepth: 4
   :caption: Models API:

   pages/mafese.rst

.. toctree::
   :maxdepth: 4
   :caption: Support:

   pages/support.rst



Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`