Machine Learning
Measures for the organization of self-organizing maps
Self-Organizing neural networks
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Self-Organizing Maps
Visual Explorations in Finance
Visual Explorations in Finance
Comparing Self-Organizing Maps
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Data visualisation and manifold mapping using the ViSOM
Neural Networks - New developments in self-organizing maps
The Knowledge Engineering Review
A forecasting solution to the oil spill problem based on a hybrid intelligent system
Information Sciences: an International Journal
A weighted voting summarization of SOM ensembles
Data Mining and Knowledge Discovery
ViSOM - a novel method for multivariate data projection and structure visualization
IEEE Transactions on Neural Networks
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This research presents a novel bio-inspired fusion algorithm based on the application of a topology preserving map called Visualization Induced SOM (ViSOM) under the umbrella of an ensemble summarization algorithm, the Weighted Voting Superposition (WeVoS) The presented model aims to obtain more accurate and robust maps, also increasing the models stability by means of the use of an ensemble training schema and a posterior fusion algorithm, been those very suitable for visualization and also classification purposes This model may be applied alone or under the frame of hybrid intelligent systems, when used for instance in the recovery phase of a case based reasoning system For the sake of completeness, the comparison of the performance with other topology preserving maps and previous fusion algorithms with several public data set obtained from the UCI repository are also included.