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
Recommended Citation
Banerjee, Amit and Davé, Rajesh N., "Validating clusters using the Hopkins statistic" (2004). Faculty Publications. 20041.
https://digitalcommons.njit.edu/fac_pubs/20041
