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Estadística de la bretxa×Índex Calinski-Harabasz×
CampAvaluació de modelsAvaluació de models
FamíliaMCDMMCDM
Any d'origen20011974
Autor originalRobert Tibshirani, Guenther Walther, Trevor HastieTadeusz Calinski, Jerzy Harabasz
TipusStatistical criterionCluster quality metric
Font seminalTibshirani, R., Walther, G., & Hastie, T. (2001). Estimating the number of clusters in a data set via the gap statistic. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 63(2), 411-423. DOI ↗Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics, 3(1), 1-27. DOI ↗
Àliesgap index, Tibshirani gap statisticvariance ratio criterion, pseudo F-statistic, CH index
Relacionats55
ResumThe Gap Statistic, developed by Tibshirani, Walther, and Hastie in 2001, is a principled statistical method for determining the optimal number of clusters in a dataset. It compares the observed within-cluster sum of squares to the expected value under a null hypothesis of no clustering structure, providing a theoretically grounded approach to cluster number selection.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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