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

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**PyLWL** is an open-source Python library that provides a unified, extensible, and user-friendly
implementation of *Locally Weighted Learning* (LWL) algorithms for supervised learning.
It implements differentiable and gradient-descent-based local models for both classification and regression tasks.

* **Free software:** GNU General Public License (GPL) V3 license
* **Provided Estimators**: `LwClassifier`, `LwRegressor`, `GdLwClassifier`, `GdLwRegressor`
* **Supported Kernel Functions**: Gaussian, Epanechnikov, Cosin...
* **Supported performance metrics**: >= 67 (47 regressions and 20 classifications)
* **Documentation:** https://pylwl.readthedocs.io
* **Python versions:** >= 3.8.x
* **Dependencies:** numpy, scipy, scikit-learn, pandas, permetrics, torch


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

   pages/quick_start.rst

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

   pages/pylwl.rst

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

   pages/support.rst



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

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