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Zotrvačnosť×Calinski-Harabasz Index×
OdborHodnotenie modelovHodnotenie modelov
RodinaMCDMMCDM
Rok vzniku19671974
TvorcaStuart Lloyd, James MacQueenTadeusz Calinski, Jerzy Harabasz
TypClustering quality metricCluster quality metric
Pôvodný zdrojLloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129-137. DOI ↗Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics, 3(1), 1-27. DOI ↗
Ďalšie názvyWCSS, within-cluster sum of squares, cluster cohesionvariance ratio criterion, pseudo F-statistic, CH index
Príbuzné55
ZhrnutieInertia, 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 Calinski-Harabasz Index, also called the Variance Ratio Criterion, was introduced by Calinski and Harabasz in 1974. It is a metric that measures the ratio of between-cluster variance to within-cluster variance, adjusted for the number of clusters and data points. Higher values indicate better-separated, more compact clusters.
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ScholarGatePorovnať metódy: Inertia (Within-Cluster Sum of Squares) · Calinski-Harabasz Index. Získané 2026-06-20 z https://scholargate.app/sk/compare