Classification by the Spherical SOM using Learning Vector Quantization (LVQ)

Abstract

This paper propose the classification by the spherical SOM using learning vector quantization (LVQ) in order to specify this boundary automatically, and try to improve the classification accuracy. As a result of the numerical experiment, a clustering method using the LVQ yielded 98.7 % accuracy. Though it was only data of Iris and Wine, the area where a boundary line exists by using LVQ could be confirmed. But it wasn't possible to specify a boundary line actually. We could improve classificaton accuracy by considering a dendrogram and a spherical map interactively.