DocumentCode
2458732
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
fYear
2012
fDate
1-5 April 2012
Firstpage
1285
Lastpage
1288
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering (ICDE), 2012 IEEE 28th International Conference on
Conference_Location
Washington, DC
ISSN
1063-6382
Print_ISBN
978-1-4673-0042-1
Type
conf
DOI
10.1109/ICDE.2012.128
Filename
6228189
Link To Document