arxivcs.LGcs.AI2026-07-08
Complexity-Budgeted, Interaction-Aware Interpretable Model for Tabular Data
Inherently interpretable classifiers for tabular data typically rely on sparse features, rules, or patterns that users can inspect directly. The marginal feature-screening step common to these methods can discard variables whose predictive value emerges only through joint configu…