The recovery performance of two-mode clustering methods: Monte Carlo experiment

Reference : The recovery performance of two-mode clustering methods: Monte Carlo experiment


	Document type :	Parts of books : Contribution to collective works
	Discipline(s) :	Social & behavioral sciences, psychology : Multidisciplinary, general & others
	To cite this reference:	http://hdl.handle.net/10993/8199

Title :	The recovery performance of two-mode clustering methods: Monte Carlo experiment
Language :	English
Author, co-author :	Krolak-Schwerdt, Sabine [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Languages, Culture, Media and Identities (LCMI) >]
	Wiedenbeck, Michael [> >]
Publication date :	2006
Main document title :	Studies in classification, data analysis and knowledge organization
Editor :	Spiliopoulou, M.
	Kruse, R.
	Borgelt, C.
	Nürnberger, A.
	Gaul, W.
Publisher :	Springer
Collection and collection volume :	Vol. 31: From data and information analysis to knowledge engineering
Pages :	190 - 197
Peer reviewed :	Yes
City :	Berlin
Abstract :	[en] In this paper, a Monte Carlo study on the performance of two–mode cluster methods is presented. The synthetical data sets were generated to correspond to two types of data consisting of overlapping as well as disjoint clusters. Furthermore, the data sets differed in cluster number, degrees of within-group homogeneity and between-group heterogeneity as well as degree of cluster overlap. We found that the methods performed very differently depending on type of data, number of clusters, homogeneity and cluster overlap.
Permalink :	http://hdl.handle.net/10993/8199

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