Interpretable Clustering Using Dempster-Shafer Theory
This study presents DSClustering, a novel algorithm that merges clustering validity with interpretability using the Dempster-Shafer theory. Traditional clustering methods like K-means, DBSCAN, and agglomerative clustering, while widely used for their efficiency and accuracy, often fall short in tran...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Graz University of Technology
2025-08-01
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| Series: | Journal of Universal Computer Science |
| Subjects: | |
| Online Access: | https://lib.jucs.org/article/164694/download/pdf/ |
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