RCProb: Probabilistic rule extraction from classification tree ensembles

arXiv:2604.25304 · cs.LG · Submitted 2026-04-28 · Read on arXiv

cs.LG

Submitted: 2026-04-28

Updated: 2026-09-03

Comments: Figure 1 improved; supersedes v2. 52 pages, 4 figures. Submitted to ESWA

Code: https://github.com/jobregon1212/rulecosi

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Interpretability — 12× in this paper · explained in 15 episodes
• Generalization — 10× in this paper · explained in 13 episodes
• Pruning — 10× in this paper · explained in 4 episodes
• Decision Tree — 7× in this paper
• Regularization — 6× in this paper · explained in 3 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Robustness — 5× in this paper · explained in 5 episodes
• Aggregation — 4× in this paper · explained in 1 episode
• Benchmark — 4× in this paper · explained in 2 episodes
• Ensemble Learning — 4× in this paper · explained in 2 episodes
• F1 Score — 4× in this paper · explained in 3 episodes
• Gradient Boosting Machines — 3× in this paper
• Random Forests — 3× in this paper
• Bayesian Framework — 2× in this paper · explained in 3 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Empirical Coverage — 2× in this paper · explained in 2 episodes
• Explainability — 2× in this paper · explained in 3 episodes
• Accountability — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Optimized Rule Ensemble — 1× in this paper
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Structural Constraints — 1× in this paper · explained in 2 episodes
• Two-Stage Framework — 1× in this paper · explained in 2 episodes

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