A review of learning vector quantization classifiers

David Nova; Pablo A. Estevez

doi:10.1007/s00521-013-1535-3

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arXiv · 1509.07093

A review of learning vector quantization classifiers

David Nova·Pablo A. Estevez

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Abstract

In this work we present a review of the state of the art of Learning Vector Quantization (LVQ) classifiers. A taxonomy is proposed which integrates the most relevant LVQ approaches to date. The main concepts associated with modern LVQ approaches are defined. A comparison is made among eleven LVQ classifiers using one real-world and two artificial datasets.

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cs.LG astro-ph.IM cs.NE stat.ML

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David Nova, Pablo A. Estevez. 2015-09-23. A review of learning vector quantization classifiers. https://doi.org/10.1007/s00521-013-1535-3

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