Abstract
In the cluster analysis, to determine the unknown number of clusters we use a criterion based on a classical location test statistic, Hotelling’s T 2. At each clustering level, its theoretical threshold is studied in view of its statistical distribution and a multiple comparison problem. In order to examine its performance, extensive experiments are done with synthetic data generated from multivariate normal distributions and a set of real image data.
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Choi, K., Kim, DH., Choi, T. (2006). Estimating the Number of Clusters Using Multivariate Location Test Statistics. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_43
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DOI: https://doi.org/10.1007/11881599_43
Publisher Name: Springer, Berlin, Heidelberg
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