Evaluation of Clusterings -- Metrics and Visual Support

  title={Evaluation of Clusterings -- Metrics and Visual Support},
  author={Elke Achtert and Sascha Goldhofer and Hans-Peter Kriegel and Erich Schubert and Arthur Zimek},
  journal={2012 IEEE 28th International Conference on Data Engineering},
When comparing clustering results, any evaluation metric breaks down the available information to a single number. However, a lot of evaluation metrics are around, that are not always concordant nor easily interpretable in judging the agreement of a pair of clusterings. Here, we provide a tool to visually support the assessment of clustering results in comparing multiple clusterings. Along the way, the suitability of a couple of clustering comparison measures can be judged in different… CONTINUE READING
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