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Implements self-organising maps combined with hierarchical cluster analysis (SOM-HCA) for clustering and visualization of high-dimensional data. The package includes functions to estimate the optimal map size based on various quality measures and to generate a model using the selected dimensions. It also performs hierarchical clustering on the map nodes to group similar units. Documentation about the SOM-HCA method is provided in Pastorelli et al. (2024) <doi:10.1002/xrs.3388>.
Version: | 0.2.0 |
Depends: | dplyr, kohonen, aweSOM, maptree, RColorBrewer |
Published: | 2025-01-27 |
DOI: | 10.32614/CRAN.package.somhca |
Author: | Gianluca Pastorelli [aut, cre] |
Maintainer: | Gianluca Pastorelli <gianluca.pastorelli at gmail.com> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
CRAN checks: | somhca results |
Reference manual: | somhca.pdf |
Package source: | somhca_0.2.0.tar.gz |
Windows binaries: | r-devel: somhca_0.1.3.zip, r-release: somhca_0.2.0.zip, r-oldrel: somhca_0.2.0.zip |
macOS binaries: | r-release (arm64): somhca_0.2.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): somhca_0.1.3.tgz, r-oldrel (x86_64): not available |
Old sources: | somhca archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.