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Some Thoughts on Simulation Studies to Compare Clustering Methods

Hennig, Christian


Simulation studies are often used to compare different clustering methods, be it with the aim of promoting a new method, or for investigating the quality of existing methods from a neutral point of view. I will go through a number of aspects of designing and running such studies, including the definition and measurement of clustering quality, the choice of models to generate data from, aggregation and visualisation of results, and also limits of what we can learn from such studies. The paper may be useful for researchers who run such simulation studies and for those interested in the results of them. Some aspects are relevant for more general simulation studies, also outside the domain of cluster analysis.

Verlagsausgabe §
DOI: 10.5445/KSP/1000087327/24
Veröffentlicht am 04.11.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2018
Sprache Englisch
Identifikator ISSN: 2363-9881
KITopen-ID: 1000125695
Erschienen in Archives of Data Science, Series A
Band 5
Heft 1
Seiten P24, 21 S. online
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