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Dunn Index×Tröghet×
ÄmnesområdeModellutvärderingModellutvärdering
FamiljMCDMMCDM
Ursprungsår19741967
UpphovspersonJoseph C. DunnStuart Lloyd, James MacQueen
TypCluster quality metricClustering quality metric
UrsprungskällaDunn, J. C. (1974). Well-separated clusters and optimal fuzzy partitions. Journal of Cybernetics, 4(1), 95-104. DOI ↗Lloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129-137. DOI ↗
AliasDunn's index, separation coefficientWCSS, within-cluster sum of squares, cluster cohesion
Närliggande55
SammanfattningThe Dunn Index, introduced by Joseph C. Dunn in 1974, is a metric that captures cluster quality by measuring the ratio of the minimum between-cluster distance to the maximum within-cluster diameter. Higher values indicate well-separated and compact clusters, with better clustering quality.Inertia, also called Within-Cluster Sum of Squares (WCSS), is a measure of cluster cohesion that quantifies how tightly points are grouped around their cluster centroids. Lower values indicate more compact, cohesive clusters. Inertia is the primary objective function for k-means clustering and has been a fundamental metric since the method's introduction.
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ScholarGateJämför metoder: Dunn Index · Inertia (Within-Cluster Sum of Squares). Hämtad 2026-06-19 från https://scholargate.app/sv/compare