Welcome to UniLVQ’s documentation!¶

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

Indices and tables¶

• Index

• Module Index

• Search Page