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إحصاءة الفجوة (Gap Statistic)×مؤشر كالينسكي-هاراباز×
المجالتقييم النماذجتقييم النماذج
العائلةMCDMMCDM
سنة النشأة20011974
صاحب الطريقةRobert Tibshirani, Guenther Walther, Trevor HastieTadeusz Calinski, Jerzy Harabasz
النوعStatistical criterionCluster quality metric
المصدر التأسيسيTibshirani, 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 ↗
الأسماء البديلةgap index, Tibshirani gap statisticvariance ratio criterion, pseudo F-statistic, CH index
ذات صلة55
الملخصThe 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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ScholarGateقارن الطرق: Gap Statistic · Calinski-Harabasz Index. استُرجع بتاريخ 2026-06-19 من https://scholargate.app/ar/compare