http://arxiv.org/abs/1509.07093
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.
D. Nova and P. Estevez
Thu, 24 Sep 15
53/60
Comments: 14 pages
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