Package: missSOM 1.0.1

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>.

Authors:Sara Rejeb [aut, cre], Tabea Rebafka [ctb], Catherine Duveau [ctb], Ron Wehrens [cph], Johannes Kruisselbrink [cph]

missSOM_1.0.1.tar.gz
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missSOM.pdf |missSOM.html
missSOM/json (API)

# Install 'missSOM' in R:
install.packages('missSOM', repos = c('https://rejebsara.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • nir - Title Near-infrared data with temperature effects
  • vintages - Wine data
  • wines - Wine data
  • yeast - Title Yeast cell-cycle data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 223 downloads 7 exports 2 dependencies

Last updated 3 years agofrom:72b81b4892. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 08 2024
R-4.5-win-x86_64OKOct 08 2024
R-4.5-linux-x86_64OKOct 08 2024
R-4.4-win-x86_64OKOct 08 2024
R-4.4-mac-x86_64OKOct 08 2024
R-4.4-mac-aarch64OKOct 08 2024
R-4.3-win-x86_64OKOct 08 2024
R-4.3-mac-x86_64OKOct 08 2024
R-4.3-mac-aarch64OKOct 08 2024

Exports:add.cluster.boundariesimputeSOMmapobject.distancessomgridtricolorunit.distances

Dependencies:kpodclustrRcpp