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[CBL09] Determining the number of clusters in CROKI2 algorithm
Conférence Internationale avec comité de lecture : MSDM'09 Meeting on Statistics and Data Mining, March 2009, pp.62-65, Hammamet, Tunisia,Mots clés: Number of Clusters, Clustering, Biclustering, Machine Learning, Data Mining, Validity Indices
Résumé:
One of the major problems in clustering is the need
of specifying the optimal number of clusters in some
clustering algorithms. Some block clustering
algorithms suffer from the same limitation that the
number of clusters needs to be specified by a human
user. This problem has been subject of wide research.
Numerous indices were proposed in order to find
reasonable number of clusters. In this paper, we aim to
extend the use of these indices to block clustering
algorithms. Therefore, an exami nation of some indices
for determining the number of clusters in CROKI2
algorithm is conducted on both real data extracted
from Metz web site and synthetic data sets being
generated according to a methodology that will be
explained later. The purpose of the paper is to test the
performance and ability of some indices to detect the
proper number of clusters on rows and columns and to
compare our new index with some other indexes.
Equipe:
msdma
BibTeX
| @inproceedings { | |||
| CBL09, | |||
| title | = | "{Determining the number of clusters in CROKI2 algorithm}", | |
| author | = | " M. Charrad and M. Ben Ahmed and Y. Lechevallier and G. Saporta ", | |
| booktitle | = | "{MSDM'09 Meeting on Statistics and Data Mining}", | |
| year | = | 2009, | |
| month | = | "March", | |
| pages | = | "62-65", | |
| address | = | "Hammamet, Tunisia", | |
| } | |||
