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) doi:10.48550/arXiv.2202.07963.
- Version1.0.1
- R version≥ 4.0.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- missSOM citation info
- Last release05/05/2022
Documentation
Team
Sara Rejeb
Ron Wehrens
Show author detailsRolesCopyright holderTabea Rebafka
Show author detailsRolesContributorJohannes Kruisselbrink
Catherine Duveau
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 195 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,676 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 27 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports2 packages
- Linking To1 package