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stat.ML2025
One Permutation Is All You Need: Fast, Deterministic Feature Importance and Model Stress-Testing
Albert Dorador
Reliable estimation of feature contributions in machine learning models is essential for transparency, algorithmic fairness, and regulatory compliance. While permutation feature im…
cs.HC2025
Optimizing Feature Ordering in Radar Charts for Multi-Profile Comparison
Albert Dorador
Radar charts are widely used to visualize multivariate data and compare multiple profiles across features. However, the visual clarity of radar charts can be severely compromised w…
stat.ME2025
TRUST: Transparent, Robust and Ultra-Sparse Trees
Albert Dorador
Piecewise-constant regression trees remain popular for their interpretability, yet often lag behind black-box models like Random Forest in predictive accuracy. In this work, we int…