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      • Computing and Mathematical Sciences
      • Computing and Mathematical Sciences Papers
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      Clustering mixed data

      Hunt, Lynette Anne; Jorgensen, Murray A.
      DOI
       10.1002/widm.33
      Link
       onlinelibrary.wiley.com
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      Citation
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      Hunt, L.A. & Jorgensen, M.A. (2011). Clustering mixed data. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1(4), 352-361.
      Permanent Research Commons link: https://hdl.handle.net/10289/5551
      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.
      Date
      2011
      Type
      Journal Article
      Publisher
      Wiley
      Collections
      • Computing and Mathematical Sciences Papers [1454]
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