Functions for Constructing and Evaluating Self-Organizing Maps

State of the art functions for constructing and evaluating self-organizing maps.

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


The biggest change in the 4.0 release of popsom is the inclusion of a vectorized version of the stochastic SOM training algorithm. This new training algorithm runs up to 10 times faster than the batch algorithm and between 50 to 100 times faster than the traditional stochastic training algorithm. Of course the precise numbers depend strongly on the kind of problem you are working on.

The SOM quality reporting function have been made consistent with our recent publications: see

8/12/16, Kingston, RI, USA

Reference manual

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4.2 by Lutz Hamel, 4 months ago

Browse source code at

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

Documentation:   PDF Manual  

GPL license

Imports som, class, fields, graphics, ggplot2

See at CRAN