Machine learningDimensionality reduction

Self-Organizing Map (Kohonen Map)

A self-organizing map is an unsupervised neural network, introduced by Teuvo Kohonen in 1982, that projects high-dimensional data onto a low-dimensional (usually two-dimensional) grid of prototype vectors while preserving the data's topology — nearby inputs map to nearby grid cells. It is used for visualization, clustering, and exploratory analysis, turning complex data into an ordered, interpretable map.

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Sources

  1. Kohonen, T. (1982). Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43(1), 59–69. DOI: 10.1007/BF00337288
  2. Kohonen, T. (1990). The self-organizing map. Proceedings of the IEEE, 78(9), 1464–1480. DOI: 10.1109/5.58325

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Referenced by

ScholarGateSelf-Organizing Map (Self-Organizing Map (Kohonen Map)). Retrieved 2026-06-04 from https://scholargate.app/en/machine-learning/self-organizing-map