Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Score de Silhouette× | Indice de Calinski-Harabasz× | |
|---|---|---|
| Domaine | Évaluation de modèles | Évaluation de modèles |
| Famille | MCDM | MCDM |
| Année d'origine≠ | 1987 | 1974 |
| Auteur d'origine≠ | Peter Rousseeuw | Tadeusz Calinski, Jerzy Harabasz |
| Type | Cluster quality metric | Cluster quality metric |
| Source fondatrice≠ | Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53-65. DOI ↗ | Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics, 3(1), 1-27. DOI ↗ |
| Alias≠ | silhouette coefficient, silhouette index | variance ratio criterion, pseudo F-statistic, CH index |
| Apparentées | 5 | 5 |
| Résumé≠ | The Silhouette Coefficient, introduced by Peter Rousseeuw in 1987, is a metric that measures how similar an object is to its own cluster compared to other clusters. It ranges from -1 to 1, where values close to 1 indicate well-separated and cohesive clusters, values near 0 suggest overlapping clusters, and negative values indicate misclustered points. | 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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