Clustering of Variables Based on Watson Distribution on Hypersphere: A Comparison of Algorithms |
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Authors: | Adelaide Figueiredo Paulo Gomes |
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Institution: | 1. School of Economics and LIAAD-INESC TEC, University of Porto, Porto, Portugaladelaide@fep.up.pt;3. Statistics Portugal, Lisbon, Portugal;4. Nova University of Lisbon, ISEGI, Lisbon, Portugal |
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Abstract: | We consider n individuals described by p variables, represented by points of the surface of unit hypersphere. We suppose that the individuals are fixed and the set of variables comes from a mixture of bipolar Watson distributions. For the mixture identification, we use EM and dynamic clusters algorithms, which enable us to obtain a partition of the set of variables into clusters of variables.Our aim is to evaluate the clusters obtained in these algorithms, using measures of within-groups variability and between-groups variability and compare these clusters with those obtained in other clustering approaches, by analyzing simulated and real data. |
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Keywords: | Dynamic clusters algorithm EM algorithm Hierarchical clustering Principal cluster component analysis Variable clustering Watson distribution |
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