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Self Organizing Map algorithm and distortion measure

By Joseph Rynkiewicz

Abstract

1 Self Organizing Map algorithm and distortion measure 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

Topics: asymptotic convergence, consistency, Self Organizing Map, empirical processes, Glivenko-Cantelli class, uniform law of large numbers, general neighborhood function
Year: 2008
OAI identifier: oai:CiteSeerX.psu:10.1.1.371.4504
Provided by: CiteSeerX
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