<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></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.

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

University of Azores, Department of Mathematics, CEEAplA, and CMATI, 9501-855-Ponta Delgada, Portugal

University of Lisbon, Faculty of Psychology, Laboratory of Statistics and Data Analysis 1649-013-Lisboa, Portugal, and DataScience

New University of Lisbon, FCT, Department of Mathematics, 2829-516-Caparica, Portugal, and DataScience

University of Azores, Department of Mathematics, CMATI, 9501-855-Ponta Delgada, Portugal

Biometrical Letters

In this paper, we illustrate an application of Ascendant Hierarchical Cluster Analysis (AHCA) to complex data taken from the literature (interval data), based...

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

Online veröffentlicht: 05. Juni 2013

Seitenbereich: 27 - 38

DOI: https://doi.org/10.2478/bile-2013-0015

This content is open access.