Making results reliable is one of the major concerns in artificial neural networks research. It is often argued that Self-Organizing Maps are less sensitive than other neural paradigms to problems related to convergence, local minima, etc. This paper introduces objective statistical measures that can be used to assess the stability of the results of SOM, both on the distortion and on the topology preservation points of views.
Cottrell, M., de Bodt, E., & Verleysen, M. (2001). A Statistical Tool to Assess the Reliability of Self-Organizing Maps. In N. Allinson, H. Yin, L. Allinson, J. Slack (ed.), Advances in Self-Organizing Maps (p. p. 7-14). Springer Verlag. https://hdl.handle.net/2078.5/253932