Predicting rubberized concrete compressive strength using machine learning: A feature importance and partial dependence analysis

In this study, a machine learning model, namely LightGBM, is developed to predict rubberized concrete's compressive strength (CS) using 11 input parameters. The model's performance is measured using several different statistical criteria after being trained on a dataset containing 275 samples.