[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


@inproceedings {
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}",
address="Hammamet, Tunisia",