A survey on unsupervised outlier detection in high-dimensional numerical data
Statistical Analysis and Data Mining
Interactive data mining with 3D-parallel-coordinate-trees
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Subsampling for efficient and effective unsupervised outlier detection ensembles
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Pronunciation extraction from phoneme sequences through cross-lingual word-to-phoneme alignment
SLSP'13 Proceedings of the First international conference on Statistical Language and Speech Processing
QuEval: beyond high-dimensional indexing à la carte
Proceedings of the VLDB Endowment
Data Mining and Knowledge Discovery
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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.