Abstract
Some clustering methods are compared in a simulation study. The data used in the analysis are generated in a mixture modeling framework. The methods included are some hierarchical methods, A:-means as implemented in the FASTCLUS procedure of SAS and cluster analysis by means of normal mixtures with the NORMIX program. We demonstrate that the poor recovery found in some studies for normal mixture type of clustering is partly due to the use of bad initial values, and partly due to the specification of covariance structure within the cluster. We further find that an important factor in the relative success of FASTCLUS lies in the initial seed selection.
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© 2000 Springer-Verlag Berlin · Heidelberg
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Hajnal, I., Loosveldt, G. (2000). The Effects of Initial Values and the Covariance Structure on the Recovery of some Clustering Methods. In: Kiers, H.A.L., Rasson, JP., Groenen, P.J.F., Schader, M. (eds) Data Analysis, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59789-3_7
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DOI: https://doi.org/10.1007/978-3-642-59789-3_7
Publisher Name: Springer, Berlin, Heidelberg
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