popsom7: A Fast, User-Friendly Implementation of Self-Organizing Maps (SOMs)

Methods for building self-organizing maps (SOMs) with a number of distinguishing features such automatic centroid detection and cluster visualization using starbursts. For more details see the paper "Improved Interpretability of the Unified Distance Matrix with Connected Components" by Hamel and Brown (2011) in <ISBN:1-60132-168-6>. The package provides user-friendly access to two models we construct: (a) a SOM model and (b) a centroid based clustering model. The package also exposes a number of quality metrics for the quantitative evaluation of the map, Hamel (2016) <doi:10.1007/978-3-319-28518-4_4>. Finally, we reintroduced our fast, vectorized training algorithm for SOM with substantial improvements. It is about an order of magnitude faster than the canonical, stochastic C implementation <doi:10.1007/978-3-030-01057-7_60>.

Version:	7.1.0
Imports:	fields, graphics, ggplot2, hash, stats, som, grDevices
Suggests:	testthat (≥ 3.0.0)
Published:	2025-03-02
DOI:	10.32614/CRAN.package.popsom7
Author:	Lutz Hamel [aut, cre], Benjamin Ott [aut], Gregory Breard [aut], Robert Tatoian [aut], Michael Eiger [aut], Vishakh Gopu [aut]
Maintainer:	Lutz Hamel <lutzhamel at uri.edu>
BugReports:	https://github.com/lutzhamel/popsom7/issues
License:	GPL-3
URL:	https://github.com/lutzhamel/popsom7
NeedsCompilation:	yes
Materials:	NEWS
CRAN checks:	popsom7 results

Documentation:

Reference manual:

popsom7.pdf

Downloads:

Package source:	popsom7_7.1.0.tar.gz
Windows binaries:	r-devel: popsom7_7.1.0.zip, r-release: popsom7_7.1.0.zip, r-oldrel: popsom7_7.1.0.zip
macOS binaries:	r-devel (arm64): popsom7_7.1.0.tgz, r-release (arm64): popsom7_7.1.0.tgz, r-oldrel (arm64): popsom7_7.1.0.tgz, r-devel (x86_64): popsom7_7.1.0.tgz, r-release (x86_64): popsom7_7.1.0.tgz, r-oldrel (x86_64): popsom7_7.1.0.tgz
Old sources:	popsom7 archive

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