Clustering of Symbolic Data based on Affinity Coefficient: Application to a Real Data Set

Sousa, Áurea; Bacelar-Nicolau, Helena; Nicolau, Fernando C.; Silva, Osvaldo

http://hdl.handle.net/10400.3/2660

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Authors

Sousa, Áurea

Bacelar-Nicolau, Helena

Nicolau, Fernando C.

Silva, Osvaldo

Abstract(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.

Description

Keywords

Ascendant Hierarchical Cluster Analysis Symbolic Data Interval Data Affinity Coefficient VL Methodology

URI

http://hdl.handle.net/10400.3/2660

Citation

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.