Abstract
In this paper ensembles of self organizing NNs through fusion are introduced. In these ensembles not the output signals of the base learners are combined, but their architectures are properly merged. Merging algorithms for fusion and boosting-fusion-based ensembles of SOMs, GSOMs and NG networks are presented and positively evaluated on benchmarks from the UCI database.
This work was supported by the Research Grant Fondecyt 1070220, Chile. The work of C. Moraga was partially supported by the Foundation for the Advancement of Soft Computing, Mieres, Spain.
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Saavedra, C., Salas, R., Allende, H., Moraga, C. (2009). Fusion of Topology Preserving Neural Networks. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds) Hybrid Artificial Intelligence Systems. HAIS 2009. Lecture Notes in Computer Science(), vol 5572. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02319-4_62
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DOI: https://doi.org/10.1007/978-3-642-02319-4_62
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