Item

Clustering mixed data

Abstract
Mixture model clustering proceeds by fitting a finite mixture of multivariate distributions to data, the fitted mixture density then being used to allocate the data to one of the components. Common model formulations assume that either all the attributes are continuous or all the attributes are categorical. In this paper, we consider options for model formulation in the more practical case of mixed data: multivariate data sets that contain both continuous and categorical attributes.
Type
Journal Article
Type of thesis
Series
Citation
Hunt, L.A. & Jorgensen, M.A. (2011). Clustering mixed data. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1(4), 352-361.
Date
2011
Publisher
Wiley
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