Tools for Building, Visualizing, and Evaluating Self-Organizing Maps

A self-organizing map package with three distinguishing features: (1) Automatic cluster centroid detection and visualization using starbursts. (2) Maintains two models of the data: (a) a self-organizing map model (b) a centroid based clustering model. (3) A very efficient stochastic training algorithm based on ideas from tensor algebra.

R package for self-organizing maps contains state of the art learning algorithms, visualizations, and evaluation functions.


Release 4.2

  • supports the Kolgomorov-Smirnov convergence test.
  • supports merging of clusters on the map that are close by
  • supports marginal distribution plots

Reference manual

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5.1 by Lutz Hamel, 3 months ago

Browse source code at

Authors: Lutz Hamel [aut, cre] , Benjamin Ott [aut] , Gregory Breard [aut] , Robert Tatoian [aut] , Michael Eiger [aut] , Vishakh Gopu [aut]

Documentation:   PDF Manual  

GPL license

Imports fields, graphics, ggplot2, hash, stats, grDevices

See at CRAN