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Estimating the number of clusters using multivariate location test statistics

Authors
Choi, KyungmeeKim, Deok-HwanChoi, Taeryon
Issue Date
2006
Publisher
SPRINGER-VERLAG BERLIN
Keywords
information retrieval; clustering; p-values; multiple comparison procedures
Citation
FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, PROCEEDINGS, v.4223, pp.373 - 382
Journal Title
FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, PROCEEDINGS
Volume
4223
Start Page
373
End Page
382
URI
https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/24617
ISSN
0302-9743
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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