This package implements the stochastic (also called on-line) Self-Organising Map (SOM) algorithm for numeric and relational data.
It is based on a grid (see initGrid) which is part of the
parameters given to the algorithm (see initSOM and
trainSOM). Many graphs can help you with the results (see
plot.somRes).
| Package: | SOMbrero |
| Type: | Package |
| Version: | 1.2-3 |
| Date: | 2018-02-05 |
The version of the SOM algorithm implemented in this package is the stochastic version.
Several variants able to handle non-vectorial data are also implemented in their
stochastic versions: type="korresp" for contingency tables, as described
in Cottrell et al., 2004 (with the observation weights defined in Cottrel and
Letremy, 2005) and type="relational" for dissimilarity data, as described
in Olteanu and Villa-Vialaneix, 2015a with the fast implementation of Mariette
et al., 2017. A special focus has been put on representing graphs, as
described in Olteanu and Villa-Vialaneix, 2015b.
Kohonen T. (2001) Self-Organizing Maps. Berlin/Heidelberg: Springer-Verlag, 3rd edition.
Cottrell M., Ibbou S., Letremy P. (2004) SOM-based algorithms for qualitative variables. Neural Networks, 17, 1149-1167.
Cottrell M., Letremy P. (2005) How to use the Kohonen algorithm to simultaneously analyse individuals in a survey. Neurocomputing, 21, 119-138.
Letremy P. (2005) Programmes bases sur l'algorithme de Kohonen et dedies a l'analyse des donnees. SAS/IML programs for 'korresp'. http://samm.univ-paris1.fr/Programmes-SAS-de-cartes-auto.
Mariette J., Rossi F., Olteanu M., Mariette J. (2017) Accelerating stochastic kernel SOM. In: M. Verleysen, XXVth European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2017), i6doc, Bruges, Belgium, 269-274.
Olteanu M., Villa-Vialaneix N. (2015a) On-line relational and multiple relational SOM. Neurocomputing, 147, 15-30.
Olteanu M., Villa-Vialaneix N. (2015b) Using SOMbrero for clustering and visualizing graphs. Journal de la Societe Francaise de Statistique, 156, 95-119.
Rossi F. (2013) yasomi: Yet Another Self-Organising Map Implementation. R package, version 0.3. https://github.com/fabrice-rossi/yasomi
Villa-Vialaneix N. (2017) Stochastic self-organizing map variants with the R package SOMbrero. In: J.C. Lamirel, M. Cottrell, M. Olteanu, 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (Proceedings of WSOM 2017), IEEE, Nancy, France.
initGrid, trainSOM, plot.somRes and
sombreroGUI.