A carregar...
Publicação
Clustering of Symbolic Data based on Affinity Coefficient: Application to a Real Data Set
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 513.52 KB | Adobe PDF |
Orientador(es)
Resumo(s)
In this paper, we illustrate an application of Ascendant Hierarchical Cluster Analysis (AHCA) to complex data taken from the literature (interval data), based on the standardized weighted generalized affinity coefficient, by the method of Wald and Wolfowitz. The probabilistic aggregation criteria used belong to a parametric family of methods under the probabilistic approach of AHCA, named VL methodology. Finally, we compare the results achieved using our approach with those obtained by other authors.
Descrição
Copyright © 2013 Walter de Gruyter GmbH.
Palavras-chave
Ascendant Hierarchical Cluster Analysis Symbolic Data Interval Data Affinity Coefficient VL Methodology
Contexto Educativo
Citação
Sousa, Áurea; Bacelar-Nicolau, Helena; Nicolau, Fernando C.; Silva, Osvaldo (2013). "Clustering of Symbolic Data based on Affinity Coefficient: Application to a Real Data Set". Biometrical Letters, 50(1), 27-38, ISSN (Print) 1896-3811, DOI: 10.2478/bile-2013-0015.
Editora
Walter de Gruyter