A federated RuleFit method using differentially private histograms for consistent cutoffs, local GBDT rule generation, and federated dual averaging for l1-regularized coefficients matches centralized RuleFit performance in simulations and delivers interpretable results on real medical data.
Interpretability of clinical decision support systems based on artificial intelligence from technological and medical perspective: A systematic review
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Federated Rule Ensemble Method in Medical Data
A federated RuleFit method using differentially private histograms for consistent cutoffs, local GBDT rule generation, and federated dual averaging for l1-regularized coefficients matches centralized RuleFit performance in simulations and delivers interpretable results on real medical data.