Subgroup Discovery with Small and Alternative Feature Sets
Summary: Subgroup discovery with small and alternative feature sets: limit to few features, seek subgroups with other features. SMT-based formulation enables solver search; NP-hardness proven for both constraints; evaluation on datasets shows quality subgroups. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jakob Bach
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 182 | Mining Frequent Patterns without Candidate Generation | 2000 | SIGMOD | 0.00036955562 |
| 1,609 | Exploratory Mining and Pruning Optimizations of Constrained Association Rules | 1998 | SIGMOD | 0.00011166163 |
| 1,942 | SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging | 2021 | SIGMOD | 0.00010010569 |
| 3,170 | Looking for Trouble: Analyzing Classifier Behavior via Pattern Divergence | 2021 | SIGMOD | 7.4517805e-05 |
| 6,689 | REDS: Rule Extraction for Discovering Scenarios | 2021 | SIGMOD | 4.9575975e-05 |
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