Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Indexul Rand Ajustat× | Scorul Siluetă× | |
|---|---|---|
| Domeniu | Evaluarea modelelor | Evaluarea modelelor |
| Familie | MCDM | MCDM |
| Anul apariției≠ | 1985 | 1987 |
| Autorul original≠ | Lawrence Hubert, Phipps Arabie | Peter Rousseeuw |
| Tip≠ | External similarity metric | Cluster quality metric |
| Sursa seminală≠ | Hubert, L., & Arabie, P. (1985). Comparing partitions. Journal of Classification, 2(1), 193-218. DOI ↗ | 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 ↗ |
| Denumiri alternative | ARI, adjusted Rand coefficient | silhouette coefficient, silhouette index |
| Înrudite | 5 | 5 |
| Rezumat≠ | The Adjusted Rand Index (ARI), developed by Hubert and Arabie in 1985, is an external clustering evaluation metric that measures the agreement between a predicted clustering and a ground truth labeling. It ranges from -1 to 1, where 1 indicates perfect agreement, 0 indicates random clustering, and negative values indicate performance worse than random chance. | 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. |
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