Scaffold-Constrained Subset Dynamic Programming for Exact SSE Clustering
Exact Euclidean \(K\)-means partitions \(n\) observations into \(K\) unlabelled clusters, but the unrestricted search is generally exponential. We use data-derived geometric graphs to precondition an exact subset dynamic program: as a result only connected vertex subsets are admitted as clusters, while sum-of-squared-errors (SSE) loss is unchanged. A remaining-set recurrence minimises fixed-\(K\) or penalised SSE, with exact factorisation over the connected components of each remaining set. The central question we study is how much computational support can be removed while preserving an unrestricted optimum. Graph inclusion gives monotone coverage and support relations, and a bottleneck ...
| Authors | Yordan P. Raykov, Max A. Little |
|---|---|
| Primary category | math.ST |
| Published | 24 September 2026 |
| Last updated at source | 24 September 2026 |
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