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

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....

A Global Approach to the Comparison of Clustering Results

Osvaldo SilvaHelena Bacelar-NicolauFernando C. Nicolau — 2012

Biometrical Letters

The discovery of knowledge in the case of Hierarchical Cluster Analysis (HCA) depends on many factors, such as the clustering algorithms applied and the strategies developed in the initial stage of Cluster Analysis. We present a global approach for evaluating the quality of clustering results and making a comparison among different clustering algorithms using the relevant information available (e.g. the stability, isolation and homogeneity of the clusters). In addition, we present a visual method...

Comparison of Multivariate Analysis Methodologies in a Palliative Care Setting

This study is focused on measuring the quality and the satisfaction with the palliative care provided to oncology patients in domicile. The SERVQUAL methodology adapted for the Portuguese context was used to evaluate the quality of palliative care and patient satisfaction. The Portuguese SERVQUAL questionnaire is composed of five perception scales and two questionnaires, one about the patient and another about the caregiver. The data analysis presented is the analysis of the answers to the five...

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