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

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

doi:10.2478/bile-2013-0015

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

Biometrical Letters

Volume 50 (2013): Issue 1 (June 2013)

By: Áurea Sousa, Helena Bacelar-Nicolau, Fernando C. Nicolau and Osvaldo Silva

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.

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Articles in this issue

DOI: https://doi.org/10.2478/bile-2013-0015 | Journal eISSN: 2199-577X | Journal ISSN: 1896-3811

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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

Keywords:

Ascendant Hierarchical Cluster Analysis,

Symbolic Data,

Interval Data,

Affinity Coefficient,

VL Methodology

Related subjects:

Life sciences,

Bioinformatics,

Life sciences, other,

Mathematics,

Probability and statistics,

Applied mathematics

© 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.

Volume 50 (2013): Issue 1 (June 2013)