4 projects
swift-monitoring
SWIFT: SHAP-Weighted Impact Feature Testing for Model-Aware Distribution Monitoring
treecf
Constrained, threshold-aware counterfactual explanations for tree ensembles (XGBoost, LightGBM, CatBoost, sklearn) on a bundled Rust genetic engine.
flaggam
FlagGAM: rule-basis generalized additive models for explainable tabular prediction (Zhao & Welsch, 2026; from-scratch implementation).
concept-graph-xai
Concept-graph aware visualisation of model feature usage and importance, with concept-level ablation metrics.
