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GowerSom (version 0.1.0)

Self-Organizing Maps for Mixed-Attribute Data Using Gower Distance

Description

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) .

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Version

Install

install.packages('GowerSom')

Version

0.1.0

License

GPL-2

Maintainer

Patricio Salas

Last Published

January 27th, 2026

Functions in GowerSom (0.1.0)

gsom_predict

Predict BMUs for new data using a fitted Gower-SOM
plot_Umatrix

Plot the U-Matrix of a Gower-SOM
gsom_updateCategorical

Update categorical prototype in Gower-SOM (internal)
gsom_Umatrix

Compute the U-Matrix for a trained Gower-SOM
get_bmu_gower

Map observations to BMUs (Best Matching Units) using Gower distance
gsom_Training

Train a Gower-SOM on mixed-attribute data