A voting-merging clustering algorithm

Dimitriadou, Evgenia and Weingessel, Andreas and Hornik, Kurt ORCID: https://orcid.org/0000-0003-4198-9911 (1999) A voting-merging clustering algorithm. Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science", 31. SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, Vienna.


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In this paper we propose an unsupervised voting-merging scheme that is capable of clustering data sets, and also of finding the number of clusters existing in them. The voting part of the algorithm allows us to combine several runs of clustering algorithms resulting in a common partition. This helps us to overcome instabilities of the clustering algorithms and to improve the ability to find structures in a data set. Moreover, we develop a strategy to understand, analyze and interpret these results. In the second part of the scheme, a merging procedure starts on the clusters resulting by voting, in order to find the number of clusters in the data set.

Item Type: Paper
Keywords: cluster algorithms / unsupervised learning / partition / number of clusters
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Departments > Marketing > Service Marketing und Tourismus
Depositing User: Repository Administrator
Date Deposited: 04 Mar 2002 12:04
Last Modified: 24 Oct 2019 13:41
URI: https://epub.wu.ac.at/id/eprint/94


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