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

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

Open Access
|Jun 2013

Abstract

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.

DOI: https://doi.org/10.2478/bile-2013-0015 | Journal eISSN: 2199-577X | Journal ISSN: 1896-3811
Language: English
Page range: 27 - 38
Published on: Jun 5, 2013
Published by: Polish Biometric Society
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2013 Áurea Sousa, Helena Bacelar-Nicolau, Fernando C. Nicolau, Osvaldo Silva, published by Polish Biometric Society
This work is licensed under the Creative Commons License.