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A clustering analysis platform to promote streamlined evaluation, comparison and reproducibility of clustering results in the future. This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. ClustEval allows biomedical researchers to pick the appropriate tool for their data type and allows method developers to compare their tool to the state of the art.

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ClustEval classification

ClustEval specifications

Web user interface
Computer skills:
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ClustEval support



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Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark; Computational Systems Biology, Max Planck Institute for Informatics, Saarbrücken, Germany; Cluster of Excellence for Multimodal Computing and Interaction, Saarland University, Saarbrücken, Germany

Funding source(s)

The SDU2020 funding initiative at the University of Southern Denmark; the International Max Planck Research School on Computer Science; the Saarland University Graduate School for Computer Science; the Cluster of Excellence for Multimodal Computing and Interaction (MMCI)

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