A self-organising map (SOM) is a form of unsupervised learning where nodes on a 2D grid (or more geometric lattice structure) act as archetypes or key values for a form of clustering, where like items are allocated to grid points that have some form of relationship. The prime example of a SOM are Kohonen networks. Like other forms of clustering algorithm, SOM can be used for data interpretation where a human expert labels areas on the map, or as a form of {[dimension reduction}} either using the nodes as discrete categorical clusters or using the 2D (or higer diennsional) embedding of the grid or lattice as continuous dimensions.
Used on pages 88, 121, 124, 371
Also known as self-organizing map, self-organizing network