Aggregating Self-Organizing Maps with Topology Preservation

Conference paper

DOI: 10.1007/978-3-319-28518-4_2

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 428)
Cite this paper as:
Mariette J., Villa-Vialaneix N. (2016) Aggregating Self-Organizing Maps with Topology Preservation. In: Merényi E., Mendenhall M., O'Driscoll P. (eds) Advances in Self-Organizing Maps and Learning Vector Quantization. Advances in Intelligent Systems and Computing, vol 428. Springer, Cham


In the online version of Self-Organizing Maps, the results obtained from different instances of the algorithm can be rather different. In this paper, we explore a novel approach which aggregates several results of the SOM algorithm to increase their quality and reduce the variability of the results. This approach uses the variability of the algorithm that is due to different initialization states. We use simulations to show that our result is efficient to improve the performance of a single SOM algorithm and to decrease the variability of the final solution. Comparison with existing methods for bagging SOMs also show competitive results.


Self-Organizing Maps Aggregation Topology preservation 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.INRA, UR 0875 MIA-TCastanet Tolosan CedexFrance

Personalised recommendations