Porównaj metody
Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.
| Miara V× | Współczynnik sylwetki× | |
|---|---|---|
| Dziedzina | Ocena modeli | Ocena modeli |
| Rodzina | MCDM | MCDM |
| Rok powstania≠ | 2007 | 1987 |
| Twórca≠ | Andrew Rosenberg, Julia Hirschberg | Peter Rousseeuw |
| Typ≠ | Entropy-based metric | Cluster quality metric |
| Źródło pierwotne≠ | Rosenberg, A., & Hirschberg, J. (2007). V-measure: A conditional entropy-based external cluster evaluation measure. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (pp. 410-420). link ↗ | 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 ↗ |
| Inne nazwy | V-measure score, homogeneity completeness V-measure | silhouette coefficient, silhouette index |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | V-measure, introduced by Rosenberg and Hirschberg in 2007, is an external clustering evaluation metric based on the harmonic mean of homogeneity and completeness. It measures whether clusters contain only points from a single true class (homogeneity) and whether all points from a true class are assigned to the same cluster (completeness). Values range from 0 to 1. | 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. |
| ScholarGateZbiór danych ↗ |
|
|