Capítulo de livro Acesso aberto Revisado por pares

Boosting Unsupervised Competitive Learning Ensembles

2007; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-540-74690-4_35

ISSN

1611-3349

Autores

Emilio Corchado, Bruno Baruque, Hujun Yin,

Tópico(s)

Image Retrieval and Classification Techniques

Resumo

Topology preserving mappings are great tools for data visualization and inspection in large datasets. This research presents a combination of several topology preserving mapping models with some basic classifier ensemble and boosting techniques in order to increase the stability conditions and, as an extension, the classification capabilities of the former. A study and comparison of the performance of some novel and classical ensemble techniques are presented in this paper to test their suitability, both in the fields of data visualization and classification when combined with topology preserving models such as the SOM, ViSOM or ML-SIM.

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