SR4-Fit: A Unified Interpretable Rule-Based Machine Learning Framework for Informative and Trustworthy Decision-Making
Sarse Relaxed Regularized Regression Rule-Fit is proposed, an intrinsically interpretable algorithm for both classification and regression that produces compact and stable rule sets without sacrificing performance, demonstrating that interpretability and predictive reliability need not be mutually exclusive.
S. Krishnan, Dean F. Hougen
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