@inproceedings{9f319c91c5904817afdaf1d48267266d,
title = "Validating clusters using the Hopkins statistic",
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.",
author = "Amit Banerjee and Dav{\'e}, \{Rajesh N.\}",
year = "2004",
doi = "10.1109/FUZZY.2004.1375706",
language = "English (US)",
isbn = "0780383532",
series = "IEEE International Conference on Fuzzy Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "149--153",
booktitle = "2004 IEEE International Conference on Fuzzy Systems - Proceedings",
address = "United States",
note = "2004 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2004 ; Conference date: 25-07-2004 Through 29-07-2004",
}