Self-Organizing Maps

Self-organizing maps (SOMs) are not cartographic maps; rather SOMs are mathematical transformations of data to a predefined two-dimensional (2D) structure to reveal data clusters based on similarity. Conceptually, the basic idea of SOM corresponds well to Tobler's first law of geography, but SOMs consider distances in a space of multiple attributes rather than a space of geographic coordinates. Methodologically, SOM computation relates to the suite of multidimensional scaling (MDS) methods (e.g., principal components analysis [PCA], factor analysis, K nearest-neighbor method, and many others) that attempt to project multidimensional variables to limited dimensional (often 2D and 3D) spaces, so that humans can discern meaningful patterns through visualization and analysis. More specifically, Teuvo Kohonen, the inventor of SOM, suggested that SOM is an ordered structure of “local ...

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