Abstract
Two key questions in Clustering problems are how to determine the number of groups properly and measure the strength of group-assignments. These questions are specially involved when the presence of certain fraction of outlying data is also expected.
Any answer to these two key questions should depend on the assumed probabilistic-model, the allowed group scatters and what we understand by noise. With this in mind, some exploratory “trimming-based” tools are presented in this work together with their justifications. The monitoring of optimal values reached when solving a robust clustering criteria and the use of some “discriminant” factors are the basis for these exploratory tools.
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Research partially supported by the Spanish Ministerio de Ciencia e Innovación, grant MTM2008-06067-C02-01, and 02 and by Consejería de Educación y Cultura de la Junta de Castilla y León, GR150.
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García-Escudero, L.A., Gordaliza, A., Matrán, C. et al. Exploring the number of groups in robust model-based clustering. Stat Comput 21, 585–599 (2011). https://doi.org/10.1007/s11222-010-9194-z
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DOI: https://doi.org/10.1007/s11222-010-9194-z