popsom: An Efficient Implementation of Kohonen's Self-Organizing Maps (SOMs) with Starburst Visualizations

Kohonen's self-organizing maps with a number of distinguishing features: (1) An efficient, single threaded, stochastic training algorithm inspired by ideas from tensor algebra. Provides significant speedups over traditional single-threaded training algorithms. No special accelerator hardware required (see <doi:10.1007/978-3-030-01057-7_60>). (2) Automatic centroid detection and visualization using starbursts. (3) Two models of the data: (a) a self organizing map model, (b) a centroid based clustering model. (4) A number of easily accessible quality metrics for the self organizing map and the centroid based cluster model (see <doi:10.1007/978-3-319-28518-4_4>).

Getting started

Package details

AuthorLutz Hamel [aut, cre], Benjamin Ott [aut], Gregory Breard [aut], Robert Tatoian [aut], Michael Eiger [aut], Vishakh Gopu [aut]
MaintainerLutz Hamel <lutzhamel@uri.edu>
LicenseGPL-3
Version6.0
URL https://github.com/lutzhamel/popsom
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("popsom")

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popsom documentation built on Dec. 21, 2021, 1:07 a.m.