Project details for Simple Generalized Learning Vector Quantization

Screenshot Simple Generalized Learning Vector Quantization 1.0

by fmschleif - June 4, 2015, 10:49:49 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

view (1 today), download ( 1 today ), 0 subscriptions


Simple and hopefully clean and easy to follow implementation of the Generalized Learning Vector Quantizer (GLVQ) - a prototype based classifier originally proposed by Sato & Yamada. I provide the code with variants for metric adaptation (RGLVQ, GMLVQ, LiRaM).

The implementation makes some simplifications and is compositional (e.g. the used metric is a matlab class and not directly implemented in the algorithm). I also use the minFunc toolbox to avoid any direct dependency to the used optimization scheme. Hence the code has much fewer parameters as you will typically find for GLVQ code.

The archive comes with a small demo script showing a typical run for with the different GLVQ variants.

Changes to previous version:

Initial Announcement on

BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
Supported Operating Systems: Platform Independent
Data Formats: Any Format Supported By Matlab
Tags: Classification, Glvq, Liram, Relevance Learning
Archive: download here


No one has posted any comments yet. Perhaps you'd like to be the first?

Leave a comment

You must be logged in to post comments.