Self-Organising Maps Coupled with Hierarchical Cluster Analysis
Overview
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 or other data to group similar units. Documentation about the SOM-HCA method is provided in Pastorelli et al. (2024) doi:10.1002/xrs.3388.
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 7
- Examples that run
- 100%6 run in a plain check
- Exported functions with examples
- 86%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing somhca adds 100 packages (53 with compiled code, 90 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
Datasets
People & History
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- 0.4.0Latest
- RR 4.6.0 released · 2026-04-24
- 0.3.02026-02-07 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 0.2.0
- 0.1.32025-01-23
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2025-01-23
- Total releases
- 4 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 23 KB
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