Evaluation of Clusterings -- Metrics and Visual Support
Elke Achtert, Sascha Goldhofer, Hans‐Peter Kriegel, Erich Schubert, Arthur Zimek · 2012
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 scenarios.