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ΠεδίοΑξιολόγηση ΜοντέλωνΑξιολόγηση Μοντέλων
ΟικογένειαMCDMMCDM
Έτος προέλευσης20011967
ΔημιουργόςRobert Tibshirani, Guenther Walther, Trevor HastieStuart Lloyd, James MacQueen
ΤύποςStatistical criterionClustering quality metric
Θεμελιώδης πηγήTibshirani, 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 ↗Lloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129-137. DOI ↗
Εναλλακτικές ονομασίεςgap index, Tibshirani gap statisticWCSS, within-cluster sum of squares, cluster cohesion
Συναφείς55
ΣύνοψηThe 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.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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ScholarGateΣύγκριση μεθόδων: Gap Statistic · Inertia (Within-Cluster Sum of Squares). Ανακτήθηκε στις 2026-06-17 από https://scholargate.app/el/compare