The self-generating model: An adaptation of the self-organizing map for intelligent agents and data mining

Abstract

We present the Self-Generating Model (SGM), a new version of the Self-organizing Map (SOM) that has been adapted for use in intelligent data mining ALife agents. The SGM sacrifices the topology-preserving ability of the SOM, but is equally accurate, and faster, at identifying handwritten numerals. It achieves a higher accuracy faster than the SOM. Furthermore, it increases model stability and reduces the problem of “wasted” models. We feel that the SGM could be a useful alternative to the SOM when topology preservation is not required.