A review of learning vector quantization classifiers
arXiv:1509.07093v1131 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental review for researchers in machine learning, summarizing existing LVQ approaches without introducing new methods.
The authors reviewed Learning Vector Quantization (LVQ) classifiers, proposing a taxonomy and comparing eleven methods on real-world and artificial datasets.
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.