A review of learning vector quantization classifiers

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Sep 23, 2015
David Nova, Pablo A. Estevez
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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.

* Neural Computing & Applications, vol. 25, pp. 511-524, 2014  * 14 pages  
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