Estimating the number of clusters using multivariate location test statistics
- Authors
- Choi, Kyungmee; Kim, Deok-Hwan; Choi, 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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Collections - College of Science and Technology > Science & Technology > Journal Articles
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