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

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**UniLVQ** is an open-source Python library that provides a unified, extensible, and user-friendly
implementation of **Learning Vector Quantization (LVQ)** algorithms for supervised learning.
It supports both **classification** and **regression** tasks, and is designed to work seamlessly with the **scikit-learn API**.

Built on top of **NumPy** and **PyTorch**, UniLVQ combines rule-based and neural-inspired LVQ variants,
making it suitable for both research and practical applications.

* **Free software:** GNU General Public License (GPL) V3 license
* **Provided Estimators**:
    * **Classification**: `Lvq1Classifier`, `Lvq2Classifier`, `Lvq3Classifier`, `OptimizedLvq1Classifier`, `GlvqClassifier`, `GrlvqClassifier`, `LgmlvqClassifier`
    * **Regression**: `GlvqRegressor`, `GrlvqRegressor`
* **Supported performance metrics**: >= 67 (47 regressions and 20 classifications)
* **Documentation:** https://unilvq.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/unilvq.rst

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

   pages/support.rst



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

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