Sandesh G. Patil

Prediction of Concrete Compressive Strength for Ready-Mix Concrete: A Comparative Evaluation of Algorithms with Explainability Analysis

This paper benchmarks twelve machine learning algorithms for that purpose on the public concrete compressive strength database, under one preprocessing and evaluation protocol, and finds a stacked ensemble of XGBoost, LightGBM, CatBoost and extremely randomized trees was the most accurate model.