Vertaile menetelmiä
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| Siluettikerroin× | Davies-Bouldin-indeksi× | |
|---|---|---|
| Tieteenala | Mallien arviointi | Mallien arviointi |
| Menetelmäperhe | MCDM | MCDM |
| Syntyvuosi≠ | 1987 | 1979 |
| Kehittäjä≠ | Peter Rousseeuw | David L. Davies, Donald W. Bouldin |
| 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 ↗ | Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(2), 224-227. DOI ↗ |
| Rinnakkaisnimet | silhouette coefficient, silhouette index | DBI, Davies Bouldin index |
| 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 Davies-Bouldin Index, introduced by Davies and Bouldin in 1979, is a metric for evaluating clustering quality based on the average similarity between each cluster and its most similar neighboring cluster. Lower values indicate better clustering, with a minimum of 0 representing perfectly separated, non-overlapping clusters. |
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