Copyright © 2013 Walter de Gruyter GmbH.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

Bacelar-Nicolau, Helena

Nicolau, Fernando C.

Silva, Osvaldo

Sousa, Áurea

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

6th Workshop on Statistics, Mathematics and Computation-3rd Portuguese-Polish Workshop on Biometry (6thWSMC and 3rdPPWB), July 3-4, 2012, Universidade da Beira Interior, Covilhã, Portugal (Comunicação).The increasing use of databases, often large ones, in diverse areas of study makes it pertinent to summarise data in terms of their most relevant concepts. These concepts may be described by types of complex data, also known as symbolic data […]. We present some results from the Ascendant Hierarchical Cluster Analysis (AHCA) of symbolic objects described by interval data, in order to illustrate the effectiveness of the Ascendent Hierarchical Cluster Analysis based on the weighted generalized affinity coefficient, for symbolic data. The measure of comparison between the elements was combined with classical aggregation criteria and probabilistic ones. The probabilistic aggregation criteria used in this study belong to a parametric family of methods in the scope of the probabilistic approach of AHCA, named VL methodology and the validation of the clustering results is based on some validation measures. Finally, we compare the results achieved by our approach with the ones obtained by other authors

Clustering of Symbolic Data based on Affinity Coefficient: Application to real data sets

Repositório da Universidade dos Açores

SUMMARY 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.</jats:p

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

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Repositório da Universidade dos Açores