SOMbrero: an R package for numeric and non-numeric Self-Organizing Maps

Julien Boelaert (1) , Laura Bendhaiba (1) , Madalina Olteanu (1) , Nathalie Vialaneix (1, 2, 3)

1 SAMM - Statistique, Analyse et Modélisation Multidisciplinaire (SAmos-Marin Mersenne)
2 MIAT INRA - Unité de Mathématiques et Informatique Appliquées de Toulouse
3 UPVD - IUT - Département STID - Carcassonne

This paper presents SOMbrero, a new R package for self-organizing maps. Along with the standard SOM algorithm for numeric data, it implements self-organizing maps for contingency tables (''Korresp'') and for dissimilarity data(''relational SOM''), all relying on stochastic (i.e., on-line) training. It offers many graphical outputs and diagnostic tools, and comes with a user-friendly web graphical interface, based on the shiny R package.

Domaines: Statistiques [math.ST]; Théorie [stat.TH]; Machine Learning [stat.ML]

Julien Boelaert, Laura Bendhaiba, Madalina Olteanu, Nathalie Vialaneix. SOMbrero: an R package for numeric and non-numeric Self-Organizing Maps. 10th International Workshop, WSOM 2014, Jul 2014, Mittweida, Germany. pp.219-228. ⟨hal-01018732⟩