missSOM: Self-Organizing Maps with Built-in Missing Data Imputation

The Self-Organizing Maps with Built-in Missing Data Imputation. Missing values are imputed and regularly updated during the online Kohonen algorithm. Our method can be used for data visualisation, clustering or imputation of missing data. It is an extension of the online algorithm of the 'kohonen' package. The method is described in the article "Self-Organizing Maps for Exploration of Partially Observed Data and Imputation of Missing Values" by S. Rejeb, C. Duveau, T. Rebafka (2022) <arXiv:2202.07963>.

Version: 1.0.1
Depends: R (≥ 4.0.0)
Imports: Rcpp (≥ 1.0.7), kpodclustr
LinkingTo: Rcpp
Published: 2022-05-05
Author: Sara Rejeb [aut, cre], Tabea Rebafka [ctb], Catherine Duveau [ctb], Ron Wehrens [cph] (Author of included functions from the 'kohonen' package), Johannes Kruisselbrink [cph] (Author of included functions from the 'kohonen' package)
Maintainer: Sara Rejeb <sara.rejeb at live.fr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: missSOM citation info
CRAN checks: missSOM results


Reference manual: missSOM.pdf


Package source: missSOM_1.0.1.tar.gz
Windows binaries: r-devel: missSOM_1.0.1.zip, r-release: missSOM_1.0.1.zip, r-oldrel: missSOM_1.0.1.zip
macOS binaries: r-release (arm64): missSOM_1.0.1.tgz, r-oldrel (arm64): missSOM_1.0.1.tgz, r-release (x86_64): missSOM_1.0.1.tgz, r-oldrel (x86_64): missSOM_1.0.1.tgz
Old sources: missSOM archive


Please use the canonical form https://CRAN.R-project.org/package=missSOM to link to this page.