Self-organizing map as a new method for clustering and data analysis

Presents an application of self-organizing maps as a method of clustering and data analysis. It is called SOM Analysis. It has some advantages over the traditional clustering algorithms in that it suits more general data distributions and needs less a priori knowledge. It can also be used as a general tool for analysing high-dimensional data relations. Some experimental results are also given in this paper.