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V-measure×Silhouetten-Koeffizient×
FachgebietModellevaluationModellevaluation
FamilieMCDMMCDM
Entstehungsjahr20071987
UrheberAndrew Rosenberg, Julia HirschbergPeter Rousseeuw
TypEntropy-based metricCluster quality metric
Wegweisende QuelleRosenberg, A., & Hirschberg, J. (2007). V-measure: A conditional entropy-based external cluster evaluation measure. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (pp. 410-420). link ↗Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53-65. DOI ↗
AliasnamenV-measure score, homogeneity completeness V-measuresilhouette coefficient, silhouette index
Verwandt55
ZusammenfassungV-measure, introduced by Rosenberg and Hirschberg in 2007, is an external clustering evaluation metric based on the harmonic mean of homogeneity and completeness. It measures whether clusters contain only points from a single true class (homogeneity) and whether all points from a true class are assigned to the same cluster (completeness). Values range from 0 to 1.The Silhouette Coefficient, introduced by Peter Rousseeuw in 1987, is a metric that measures how similar an object is to its own cluster compared to other clusters. It ranges from -1 to 1, where values close to 1 indicate well-separated and cohesive clusters, values near 0 suggest overlapping clusters, and negative values indicate misclustered points.
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ScholarGateMethoden vergleichen: V-measure · Silhouette Score. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare