Self-Organizing Maps for Mixed-Attribute Data Using Gower Distance
Overview
Implements a variant of the Self-Organizing Map (SOM) algorithm designed for mixed-attribute datasets. Similarity between observations is computed using the Gower distance, and categorical prototypes are updated via heuristic strategies (weighted mode and multinomial sampling). Provides functions for model fitting, mapping, visualization (U-Matrix and component planes), and evaluation, making SOM applicable to heterogeneous real-world data. For methodological details see Sáez and Salas (2026) doi:10.1007/s41060-025-00941-6.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 6 (1 internal)
- Examples that run
- 100%6 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 88%
- Return-value docs
- 100%
- Help pages citing references
- 83%
Downloads
Dependencies
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- 0.1.0Latest2026-01-27 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-01-27
- Total releases
- 1 / 1 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 4.3.0
- Download size
- 8.9 KB
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