Growing hierarchical self organising map (GHSOM) toolbox: visualisations and enhancements
Aaron Chan, Elias Pampalk · 2002
The Growing Hierarchical Self Organising Map (GHSOM) presents a method of dynamically modeling the data set that is presented. To a certain extent the GHSOM provides a solution to determine the size of the SOM needed, which is done through a growing fashion of neurons. In our development of the GHSOM Toolbox for Matlab presented in this paper, we have discovered that the GHSOM algorithm also provides a visualisation advantage of having the ability of presenting classes and sub-classes of similar data. We also propose two enhancements to the algorithm: (1) Usage of cumulative quantisation errors for better resolution in the growth process and (2) Tidier algorithm for initialisation of sub layer neurons for orientation.