Explainable Machine Learning for Compressive Stress Prediction in Cement-Based Construction Materials: A Systematic Benchmarking and SHAP Interpretability Study
This study addresses three recurring weaknesses of the machine learning literature in this area: model comparisons are seldom made under one shared data split and are rarely validated statistically; raw mix-design variables are usually passed to the learner without encoding established concrete science; and analysis co...