An Unsupervised Learning Method that Produces Organized Representations from Real Information

The neural-network theories aim at two goals in medicine and biology: modeling of the neural structures and functions, and development of computational methods for the analysis of the experimental data. The Self-Organizing Map (SOM) was originally intended for the explanation of certain brain functions and organizations, but it has later been accepted as a new statistical analysis method to many fields of science and technology. At least 3700 scientific works on the SOM have been published. In its basic form, the SOM forms illustrative nonlinear projections of high-dimensional data manifolds, and these projections, usually produced on a two-dimensional display grid, help in the visualization and understanding of the relationships between complex data sets.

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