Learning Vector Quantization
Closely related to VQ and SOM is Learning Vector Quantization (LVQ). This name signifies a class of related algorithms, such as LVQ1, LVQ2, LVQ3, and OLVQ1. While VQ and the basic SOM are unsupervised clustering and learning methods, LVQ describes supervised learning. On the other hand, unlike in SOM, no neighborhoods around the “winner” are defined during learning in the basic LVQ, whereby also no spatial order of the codebook vectors is expected to ensue.
Unable to display preview. Download preview PDF.
- [6.1]T. Kohonen: In Advanced Neural Networks, ed. by R. Eckmiller (Elsevier, Amsterdam, Netherlands 1990) p. 137Google Scholar
- [6.2]T. Kohonen: In Proc. IJCNN-90-San Diego, Int. Joint Conf. on Neural Networks (IEEE Service Center, Piscataway, NJ 1990) p. I–545Google Scholar
- [6.4]T. Kohonen: In Artificial Neural Networks, ed. by T. Kohonen, K. Mäkisara, O. Simula, J. Kangas (North-Holland, Amsterdam, Netherlands 1991) p. 11–1357Google Scholar