Minimum Description Length based Granular-Ball Tree Regularization for Spectral Clustering
This paper proposes Minimum Description Length based Granular-Ball Tree Regularized Spectral Clustering (MDL-GBTRSC), a fixed-K method that uses granular balls as regional descriptors for sample-level affinity construction rather than as reduced graph nodes. A reciprocal-neighborhood continuity term is incorporated into an MDL-based refinement criterion to construct a granular-ball hierarchy, and the structural scales of the terminal regions are transferred to the original sample graph before spectral partitioning. Experiments on 18 real and 20 synthetic datasets, comprising 109,969 samples in total, compare MDL-GBTRSC with nine competing methods. On the 17 real datasets completed by all ...
| Authors | Zeqiang Xian, Caihui Liu, Yong Zhang et al. |
|---|---|
| Primary category | cs.LG |
| Published | 21 May 2026 |
| Last updated at source | 29 September 2026 |
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