Comparer des méthodes

	Méthode du coude	Statistique de l'écart
Domaine	Évaluation de modèles	Évaluation de modèles
Famille	MCDM	MCDM
Année d'origine	1953	2001
Auteur d'origine	Robert Thorndike	Robert Tibshirani, Guenther Walther, Trevor Hastie
Type	Heuristic optimization criterion	Statistical criterion
Source fondatrice	Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer Series in Statistics.	Tibshirani, 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.
Alias	elbow analysis, knee detection	gap index, Tibshirani gap statistic
Apparentées	5	5
Résumé	The Elbow Method is a heuristic for selecting the optimal number of clusters in partitional clustering. Introduced by Robert Thorndike in 1953, it involves fitting clustering models for increasing numbers of clusters and plotting the within-cluster sum of squares (WCSS) against the number of clusters. The 'elbow' occurs where the rate of WCSS decrease sharply changes, suggesting an optimal cluster count.	The 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.