Taxonomizer: Interactive Construction of Fully Labeled Hierarchical Groupings from Attributes of Multivariate Data

@article{Mahmood2020TaxonomizerIC,
  title={Taxonomizer: Interactive Construction of Fully Labeled Hierarchical Groupings from Attributes of Multivariate Data},
  author={Salman Mahmood and Klaus Mueller},
  journal={IEEE Transactions on Visualization and Computer Graphics},
  year={2020},
  volume={26},
  pages={2875-2890}
}
  • Salman Mahmood, K. Mueller
  • Published 2020
  • Computer Science, Medicine
  • IEEE Transactions on Visualization and Computer Graphics
Organizing multivariate data spaces by their dimensions or attributes can be a rather difficult task. Most of the work in this area focuses on the statistical aspects such as correlation clustering, dimension reduction, and the like. These methods typically produce hierarchies in which the leaf nodes are labeled by the attribute names while the inner nodes are often represented by just a statistical measure and criterion, such as a threshold. This makes them difficult to understand for… Expand

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