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Dimensional Stacking

  • Partitioning of the n-dimensional attribute space in 2-D subspaces, which are ‘stacked’ into each other
  • Partitioning of the attribute value ranges into classes. The important attributes should be used on the outer levels.
  • Adequate for data with ordinal attributes of low cardinality
  • But, difficult to display more than nine dimensions
  • Important to map dimensions appropriately

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