Visualizing large data by the SOM and GTM methods — what are we obtaining?

Author:

Bartkowiak Anna

Publisher

Springer Berlin Heidelberg

Reference10 articles.

1. Bartkowiak A., Szustalewicz A., Evelpidou N., Vassilopoulos A. (2003). Choosing data vectors representing a huge data set: a comparison of Kohonen’s maps and the neural gas method. Proc. First Int. Conf. on Environmental Research and Assessment, Bucharest, Romania, pp. 561–572, print on CD—ROM, ©Ars Docendi P. H, Bucharest, Romania.

2. Bartkowiak A. (2003). SOM and GTM: Comparison in Figures. Report December 2003. http://www.ii.uni.wroc.pl /“aba/papers.html

3. Bishop C.M., Svensèn M., and Williams C. K. I. (1996). The generative topographic mapping. Neural Computation 10 (1), pp. 215–235.

4. Kiviluoto K. (1996). Topology preservation in self-organizing maps. Proceedings ICNN’96, V. 1, IEEE Neural Networks Council, June 1996, Piscataway, New Jersey, USA, pp. 294–299.

5. Kohonen T. (1995). Self-Organizing Maps. Springer Series in Information Sciences, V. 30, Berlin.

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