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Inertia (Within-Cluster Sum of Squares)×شاخص دان×
حوزهارزیابی مدلارزیابی مدل
خانوادهMCDMMCDM
سال پیدایش19671974
پدیدآورStuart Lloyd, James MacQueenJoseph C. Dunn
نوعClustering quality metricCluster quality metric
منبع بنیادینLloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129-137. DOI ↗Dunn, J. C. (1974). Well-separated clusters and optimal fuzzy partitions. Journal of Cybernetics, 4(1), 95-104. DOI ↗
نام‌های دیگرWCSS, within-cluster sum of squares, cluster cohesionDunn's index, separation coefficient
مرتبط55
خلاصهInertia, 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.The 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.
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ScholarGateمقایسهٔ روش‌ها: Inertia (Within-Cluster Sum of Squares) · Dunn Index. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare