MOSS formulates stable rule-set construction as a bi-objective integer program and uses a cutting-plane method to trace the accuracy-stability Pareto frontier, outperforming SIRUS, RuleFit, FIRE, and GLRM on average.
Sparse classification: a scalable discrete optimization perspective.Machine Learning, 110:3177–3209, 2021
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MOSS: Multi-Objective Optimization for Stable Rule Sets
MOSS formulates stable rule-set construction as a bi-objective integer program and uses a cutting-plane method to trace the accuracy-stability Pareto frontier, outperforming SIRUS, RuleFit, FIRE, and GLRM on average.