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

• Autorzy: Áurea Sousa , Helena Bacelar-Nicolau , Fernando C. Nicolau , Osvaldo Silva
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

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

• Wydawca: De Gruyter Open
• Czasopismo: Biometrical Letters
• Rocznik: 2013
• Tom: 50
• Numer: 1
• Strony: 27-38

Daty

wydano

2013-06-01

online

2013-06-05

Twórcy

autor

Áurea Sousa

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

autor

Helena Bacelar-Nicolau

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

autor

Fernando C. Nicolau

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

autor

Osvaldo Silva

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

Bibliografia

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Identyfikatory

DOI

10.2478/bile-2013-0015