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)