Scalable and Distributed Silhouette Approximation
The silhouette is one of the most widely used measures to assess the quality of a $k$-clustering of a dataset of $n$ elements. Its evaluation requires no information beyond the clustering assignment. In addition, the silhouette is extremely easy to interpret, providing a score to measure the quality of a clustering as a whole or for each element. The exact computation of the: (i) silhouette of each element of a dataset; and (ii) the global silhouette of the clustering; require $Θ(n^2)$ distance calculations, under general metrics. The quadratic complexity $Θ(n^2)$ is extremely prohibitive, especially on massive modern datasets. Surprisingly, existing approximate methods using $O(n^2)$ dis...
| Authors | Ilie Sarpe, Federico Altieri, Andrea Pietracaprina et al. |
|---|---|
| Primary category | cs.DS |
| Published | 2 July 2026 |
| Last updated at source | 2 July 2026 |
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