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Self-organizing map (SOM), or Kohonen Map, is a computational data analysis method which produces nonlinear mappings of data to lower dimensions. Alternatively, the SOM can be viewed as a clustering algorithm which produces a set of clusters organized on a regular grid. The roots of SOM are in neural computation (see neural networks); it has been used as an abstract model for the formation of ordered maps of brain functions, such as sensory feature maps. Several variants have been proposed, ranging from dynamic models to Bayesian variants. The SOM has been used widely as an engineering tool for data analysis, process monitoring, and information visualization, in numerous application areas.
A schematic diagram showing how the SOM grid of units (circles on the left, neighbors connected with lines) corresponds to an “elastic net” in the data space. The mapping from the grid locations,...
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Recommended Reading
Bishop, C. M., Svensén, M., & Williams, C. K. I. (1998). GTM: The generative topographic mapping. Neural Computation, 10, 215–234.
Fort, J. C. (2006). SOM’s mathematics. Neural Networks, 19, 812–816.
Hastie, T., Tibshirani, R., & Friedman, J. (2001). The elements of statistical learning. New York: Springer.
Heskes, T. (2001). Self-organizing maps, vector quantization, and mixture modeling. IEEE Transactions on Neural Networks, 12, 1299–1305.
Kohonen, T. (1982). Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43, 59–69.
Kohonen, T. (2001). Self-organizing maps (3rd ed.). Berlin: Springer.
Kohonen, T., Kaski, S., Lagus, K., Salojärvi, J., Honkela, J., Paatero, V., et al. (2000). Self organization of a massive document collection. IEEE Transactions on Neural Networks, 11, 574–585.
Luttrell, S. P. (1994). A Bayesian analysis of self-organizing maps. Neural Computation, 6, 767–794.
Pöllä, M., Honkela, T., & Kohonen, T. (2009). Bibliography of self-organizing map (SOM) papers: 2002-2005 addendum. Report TKK-ICS-R23, Helsinki University of Technology, Department of Information and Computer Science, Espoo, Finland.
von der Malsburg, C. (1973). Self-organization of orientation sensitive cells in the striate cortex. Kybernetik, 14, 85–100.
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Kaski, S. (2011). Self-Organizing Maps. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_746
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DOI: https://doi.org/10.1007/978-0-387-30164-8_746
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