Gradient Boosting Reaches R² of 0.940 Predicting Concrete Strength in Scientific Reports Study of 1,030 Observations
Scientific Reports published a study on concrete compressive strength prediction on November 13, 2026. The study used the UCI Concrete Compressive Strength dataset, comprising 1,030 observations and 428 mixtures, and compared Linear Regression, Support Vector Regression, Random Forest and Gradient Boosting. A strength-stratified 80/20 split gave 824 training and 206 held-out observations; hyperparameters were selected by five-fold cross-validation within the training partition and the held-out set was used once. Gradient Boosting performed best, with R² of 0.940, RMSE of 4.07 MPa and MAE of 2.70 MPa, followed by Random Forest at R² of 0.926 and Support Vector Regression at R² of 0.887. Because most mixtures are tested at several ages, the authors also ran mixture-grouped cross-validation, which lowered the Gradient Boosting score from 0.933 to 0.862 with the ranking preserved. SHAP attributions ranked age, cement, water and slag as the leading predictors. The authors said the framework supports preliminary mixture screening with laboratory verification, and that external validation remains necessary. The research received no external funding.
(Source: Scientific)
Source: Scientific
Published by GSM · USA (original Chinese edition)
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