Evaluation of clusterings - Metrics and visual support

Elke Achtert*, Sascha Goldhofer, Hans Peter Kriegel, Erich Schubert, Arthur Zimek

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Abstrakt

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.

OriginalsprogEngelsk
TitelProceedings of the 2012 IEEE 28th International Conference on Data Engineering
ForlagIEEE
Publikationsdato30. jul. 2012
Sider1285-1288
ISBN (Trykt)978-1-4673-0042-1
ISBN (Elektronisk)978-0-7695-4747-3
DOI
StatusUdgivet - 30. jul. 2012
Udgivet eksterntJa
BegivenhedIEEE 28th International Conference on Data Engineering - Arlington, USA
Varighed: 1. apr. 20125. apr. 2012

Konference

KonferenceIEEE 28th International Conference on Data Engineering
LandUSA
ByArlington
Periode01/04/201205/04/2012
SponsorMicrosoft, National Science Foundation (NSF), EMC, Greenplum, IBM Research
NavnProceedings - International Conference on Data Engineering
ISSN1084-4627

Citationsformater

Achtert, E., Goldhofer, S., Kriegel, H. P., Schubert, E., & Zimek, A. (2012). Evaluation of clusterings - Metrics and visual support. I Proceedings of the 2012 IEEE 28th International Conference on Data Engineering (s. 1285-1288). IEEE. Proceedings - International Conference on Data Engineering https://doi.org/10.1109/ICDE.2012.128