Efficient Centroid-Linkage Clustering
Fuente:
arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917687692623872 |
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| author | Bateni, MohammadHossein Dhulipala, Laxman Fletcher, Willem Gowda, Kishen N Hershkowitz, D Ellis Jayaram, Rajesh Łącki, Jakub |
| author_facet | Bateni, MohammadHossein Dhulipala, Laxman Fletcher, Willem Gowda, Kishen N Hershkowitz, D Ellis Jayaram, Rajesh Łącki, Jakub |
| contents | We give an efficient algorithm for Centroid-Linkage Hierarchical Agglomerative Clustering (HAC), which computes a $c$-approximate clustering in roughly $n^{1+O(1/c^2)}$ time. We obtain our result by combining a new Centroid-Linkage HAC algorithm with a novel fully dynamic data structure for nearest neighbor search which works under adaptive updates.
We also evaluate our algorithm empirically. By leveraging a state-of-the-art nearest-neighbor search library, we obtain a fast and accurate Centroid-Linkage HAC algorithm. Compared to an existing state-of-the-art exact baseline, our implementation maintains the clustering quality while delivering up to a $36\times$ speedup due to performing fewer distance comparisons. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_05066 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Efficient Centroid-Linkage Clustering Bateni, MohammadHossein Dhulipala, Laxman Fletcher, Willem Gowda, Kishen N Hershkowitz, D Ellis Jayaram, Rajesh Łącki, Jakub Data Structures and Algorithms We give an efficient algorithm for Centroid-Linkage Hierarchical Agglomerative Clustering (HAC), which computes a $c$-approximate clustering in roughly $n^{1+O(1/c^2)}$ time. We obtain our result by combining a new Centroid-Linkage HAC algorithm with a novel fully dynamic data structure for nearest neighbor search which works under adaptive updates. We also evaluate our algorithm empirically. By leveraging a state-of-the-art nearest-neighbor search library, we obtain a fast and accurate Centroid-Linkage HAC algorithm. Compared to an existing state-of-the-art exact baseline, our implementation maintains the clustering quality while delivering up to a $36\times$ speedup due to performing fewer distance comparisons. |
| title | Efficient Centroid-Linkage Clustering |
| topic | Data Structures and Algorithms |
| url | https://arxiv.org/abs/2406.05066 |