Model-based multidimensional clustering of categorical data

  title={Model-based multidimensional clustering of categorical data},
  author={Tao Chen and Nevin Lianwen Zhang and Tengfei Liu and Kin Man Poon and Yi Wang},
  journal={Artif. Intell.},
Existing models for cluster analysis typically consist of a number of attributes that describe the objects to be partitioned and one single latent variable that represents the clusters to be identified. When one analyzes data using such a model, one is looking for one way to cluster data that is jointly defined by all the attributes. In other words, one performs unidimensional clustering. This is not always appropriate. For complex data with many attributes, it is more reasonable to consider… CONTINUE READING
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