@inproceedings{d979cbc99f144b6b932ba4176ce6dc56,
title = "A cluster validity index based on frequent pattern",
abstract = "Since a clustering algorithm can produce as many partitions as desired, one need to assess their quality in order to select the partition that most represents the structure in the data. This is the rationale for the cluster-validity (CV) problem and indices. This paper proposes a CV index for fuzzy-clustering algorithm, such as the fuzzy c-means (FCM) or its derivatives. Given a fuzzy partition, this new index uses global information and is based on more logical reasoning than geometrical features. Experimental results on artificial and benchmark datasets are given to demonstrate the performance of the proposed index, as compared with traditional and recent indices",
keywords = "cluster, index, frequent pattern",
author = "Hongyan Cui and Kuo Zhang and Xu Huang and Yunjie Liu",
year = "2013",
language = "English",
volume = "1",
series = "International Symposium on Wireless Personal Multimedia Communications (WPMC)",
publisher = "IEEE, Institute of Electrical and Electronics Engineers",
pages = "1--6",
editor = "Ashutosh Dutta",
booktitle = "International Symposium on Wireless Personal Multimedia Communications, WPMC",
address = "United States",
note = "16th International Symposium on Wireless Personal Multimedia Communications, 2013 ; Conference date: 24-06-2013 Through 27-06-2013",
}