Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Ron Wehrens, Johannes Kruisselbrink
Title: Flexible Self-Organizing Maps in kohonen 3.0
Abstract: Self-organizing maps (SOMs) are popular tools for grouping and visualizing data in many areas of science. This paper describes recent changes in package kohonen, implementing several different forms of SOMs. These changes are primarily focused on making the package more useable for large data sets. Memory consumption has decreased dramatically, amongst others, by replacing the old interface to the underlying compiled code by a new one relying on Rcpp. The batch SOM algorithm for training has been added in both sequential and parallel forms. A final important extension of the package's repertoire is the possibility to define and use data-dependent distance functions, extremely useful in cases where standard distances like the Euclidean distance are not appropriate. Several examples of possible applications are presented.

Page views:: 801. Submitted: 2017-03-20. Published: 2018-11-12.
Paper: Flexible Self-Organizing Maps in kohonen 3.0     Download PDF (Downloads: 302)
Supplements:
kohonen_3.0.7.tar.gz: R source package Download (Downloads: 14; 1MB)
v87i07.R: R replication code Download (Downloads: 15; 12KB)
v87i07-benchmarks.zip: R replication materials for benchmarks Download (Downloads: 12; 717KB)

DOI: 10.18637/jss.v087.i07

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.