Applications of the Growing Self Organizing Map on High Dimensional Data

Rasika Amarasiri, Damminda Alahakoon, Kate Smith

ABSTRACT

The Growing Self Organizing Map (GSOM) is a dynamic variant of the Self Organizing Map (SOM). It has been mainly used on low dimensional data sets. In this paper the GSOM is applied on high dimensional data sets and its performance is evaluated. Several modifications to the original GSOM algorithm are presented that enable the GSOM to be applied on high dimensional data .The modified version of the GSOM is called the High Dimensional Growing Self Organizing Map (HDGSOM).