Format

Send to

Choose Destination
  • PMID: 23609062 was deleted because it is a duplicate of PMID: 23929864
IEEE/ACM Trans Comput Biol Bioinform. 2013 Mar-Apr;10(2):401-14. doi: 10.1109/TCBB.2013.32.

How many clusters: a validation index for arbitrary-shaped clusters.

Author information

1
CIFASIS, French Argentine International Center for Information and Systems Sciences, UPCAM, France.

Abstract

Clustering validation indexes are intended to assess the goodness of clustering results. Many methods used to estimate the number of clusters rely on a validation index as a key element to find the correct answer. This paper presents a new validation index based on graph concepts, which has been designed to find arbitrary shaped clusters by exploiting the spatial layout of the patterns and their clustering label. This new clustering index is combined with a solid statistical detection framework, the gap statistic. The resulting method is able to find the right number of arbitrary-shaped clusters in diverse situations, as we show with examples where this information is available. A comparison with several relevant validation methods is carried out using artificial and gene expression data sets. The results are very encouraging, showing that the underlying structure in the data can be more accurately detected with the new clustering index. Our gene expression data results also indicate that this new index is stable under perturbation of the input data.

PMID:
23929864
DOI:
10.1109/TCBB.2013.32
[Indexed for MEDLINE]

Supplemental Content

Loading ...
Support Center