Abstract. In many situations, high dimensional data can be considered as sampled functions. We show in this paper how to implement a Self-Organizing Map (SOM) on such data by appro...
Self-organizing maps (SOM) have been recognized as a powerful tool in data exploratoration, especially for the tasks of clustering on high dimensional data. However, clustering on ...
The self-organising map (SOM) has been successfully employed as a nonparametric method for dimensionality reduction and data visualisation. However, for visualisation the SOM requ...
Abstract. We describe a scalable parallel implementation of the self organizing map (SOM) suitable for datamining applications involving clustering or segmentation against large da...
Richard D. Lawrence, George S. Almasi, Holly E. Ru...
— Since we can accumulate a huge amount of data including useless information in these years, it is important to investigate various extraction method of clusters from data inclu...