Title :
Evaluation of Clusterings -- Metrics and Visual Support
Author :
Achtert, Elke ; Goldhofer, Sascha ; Kriegel, Hans-Peter ; Schubert, Erich ; Zimek, Arthur
Author_Institution :
Inst. for Inf., Ludwig-Maximilians-Univ. Munchen, München, Germany
Abstract :
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.
Keywords :
data visualisation; pattern clustering; clustering evaluation; evaluation metrics; multiple clusterings; visual support; Clustering algorithms; Complexity theory; Conferences; Data visualization; Measurement; Noise; Visualization;
Conference_Titel :
Data Engineering (ICDE), 2012 IEEE 28th International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4673-0042-1
DOI :
10.1109/ICDE.2012.128