The area under the ROC curve as a measure of clustering quality

DOI10.1007/s10618-022-00829-0zbMath1497.62150arXiv2009.02400OpenAlexW3083050659WikidataQ114690136 ScholiaQ114690136MaRDI QIDQ2147411

Ivan G. Costa, Pablo A. Jaskowiak, Ricardo J. G. B. Campello

Publication date: 20 June 2022

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2009.02400

zbMATH Keywords

area under curvereceiver operating characteristicsarea under curve for clusteringAUC/ROCclustering validationqualitative/visual clustering evaluation

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• Silhouettes
• clValid
• HandTill2001
• NbClust
• clusterCrit

Cites Work

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• ROC curves in cost space
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• Well-Separated Clusters and Optimal Fuzzy Partitions
• Measuring the Power of Hierarchical Cluster Analysis
• Relative clustering validity criteria: A comparative overview
• Measures of Association for Cross Classifications
• A simple generalisation of the area under the ROC curve for multiple class classification problems
• On clustering validation techniques