Estimating the Number of Clusters using Hotelling's

Title & Authors
Estimating the Number of Clusters using Hotelling's
Choi, Kyung-Mee;

Abstract
In the cluster analysis, Hotelling's $\small{T^2}$ can be used to estimate the unknown number of clusters based on the idea of multiple comparison procedure. Especially, its threshold is obtained according to the probability of committing the type one error. Examples are used to compare Hotelling's $\small{T^2}$ with other classical location test statistics such as Sum-of-Squared Error and Wilks' $\small{\Lambda}$ The hierarchical clustering is used to reveal the underlying structure of the data. Also related criteria are reviewed in view of both the between variance and the within variance.
Keywords
Multiple Comparison Procedure;Type One Error;Bonferroni-Type Significance Level;
Language
English
Cited by
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