Validating clusters using the Hopkins statistic

Document Type

Conference Proceeding

Publication Date

12-1-2004

Abstract

A novel scheme for cluster validity using a test for random position hypothesis is proposed. The random position hypothesis is tested against an alternative clustered hypothesis on every cluster produced by a partitioning algorithm. A test statistic such as the well-known Hopkins statistic could be used as a basis to accept or reject the random position hypothesis, which is also the null hypothesis in this case. The Hopkins statistic is known to be a fair estimator of randomness in a data set. The concept is borrowed from the clustering tendency domain and its applicability to validating clusters is shown here using two artificially constructed test data sets.

Identifier

11144327629 (Scopus)

ISBN

[0780383532]

Publication Title

IEEE International Conference on Fuzzy Systems

External Full Text Location

https://doi.org/10.1109/FUZZY.2004.1375706

ISSN

10987584

First Page

149

Last Page

153

Volume

1

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