English

Self Organizing Map algorithm and distortion measure

Machine Learning 2008-02-22 v1 Statistics Theory Statistics Theory

Abstract

We study the statistical meaning of the minimization of distortion measure and the relation between the equilibrium points of the SOM algorithm and the minima of distortion measure. If we assume that the observations and the map lie in an compact Euclidean space, we prove the strong consistency of the map which almost minimizes the empirical distortion. Moreover, after calculating the derivatives of the theoretical distortion measure, we show that the points minimizing this measure and the equilibria of the Kohonen map do not match in general. We illustrate, with a simple example, how this occurs.

Cite

@article{arxiv.0802.3150,
  title  = {Self Organizing Map algorithm and distortion measure},
  author = {Joseph Rynkiewicz},
  journal= {arXiv preprint arXiv:0802.3150},
  year   = {2008}
}
R2 v1 2026-06-21T10:14:45.436Z