Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Siluettikerroin× | Dunn-indeksi× | |
|---|---|---|
| Tieteenala | Mallien arviointi | Mallien arviointi |
| Menetelmäperhe | MCDM | MCDM |
| Syntyvuosi≠ | 1987 | 1974 |
| Kehittäjä≠ | Peter Rousseeuw | Joseph C. Dunn |
| Tyyppi | Cluster quality metric | Cluster quality metric |
| Alkuperäislähde≠ | 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 ↗ | Dunn, J. C. (1974). Well-separated clusters and optimal fuzzy partitions. Journal of Cybernetics, 4(1), 95-104. DOI ↗ |
| Rinnakkaisnimet | silhouette coefficient, silhouette index | Dunn's index, separation coefficient |
| Liittyvät | 5 | 5 |
| Tiivistelmä≠ | 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 Dunn Index, introduced by Joseph C. Dunn in 1974, is a metric that captures cluster quality by measuring the ratio of the minimum between-cluster distance to the maximum within-cluster diameter. Higher values indicate well-separated and compact clusters, with better clustering quality. |
| ScholarGateAineisto ↗ |
|
|