Identifying Groups: A Comparison of Methodologies
Journal of Data SciencePublished 5 April 2021Open access
Abdolreza Eshghi, Dominique Haughton, Pascal Legrand, Maria Skaletsky, Sam Woolford
Citations93
SJR quartileQ3
SJR score0.39
SNIP0.69
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TL;DR
This is the first contribution in the literature to compare three clustering techniques in a context where the classes are not known in advance, and proposes some novel measures of the quality of a clustering.
Abstract
This paper describes and compares three clustering techniques: traditional clustering methods, Kohonen maps and latent class models. The paper also proposes some novel measures of the quality of a clustering. To the best of our knowledge, this is the first contribution in the literature to compare these three techniques in a context where the classes are not known in advance.
Keywords
Social SciencesEngineeringComputer Science
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