Improved PLSOM algorithm
The original Parameter-Less Self-Organising Map (PLSOM) algorithm was introduced as a solution to the problems the Self-Organising Map (SOM) encounters when dealing with certain types of mapping tasks. Unfortunately the PLSOM suffers from over-sensitivity to outliers and over-reliance on the initial weight distribution. The PLSOM2 algorithm is introduced to address these problems with the PLSOM. PLSOM2 is able to cope well with outliers without exhibiting the problems associated with the standard PLSOM algorithm. The PLSOM2 requires very little computational overhead compared to the standard PLSOM, thanks to an efficient method of approximating the diameter of the inputs, and does not rely on a priori knowledge of the training input space. This paper provides a discussion of the reasoning behind the PLSOM2 and experimental results showing its effectiveness for mapping tasks.
self-organising map neural networks