Clustering Validity Assessment: Finding the optimal partitioning of a data set (2001)
by
Maria Halkidi
,
Michalis Vazirgiannis
| Citations: | 21 - 2 self |
BibTeX
@MISC{Halkidi01clusteringvalidity,
author = {Maria Halkidi and Michalis Vazirgiannis},
title = {Clustering Validity Assessment: Finding the optimal partitioning of a data set},
year = {2001}
}
Years of Citing Articles
Bookmark
 |
 |
 |
 |
 |
 |
OpenURL
Abstract
Clustering is a mostly unsupervised procedure and the majority of the clustering algorithms depend on certain assumptions in order to define the subgroups present in a data set. As a consequence, in most applications the resulting clustering scheme requires some sort of evaluation as regards its validity.
