Dataset for "An Explainable Ensemble Machine Learning Approach for Coefficient of Compressibility Prediction of Chengdu Clay"

This dataset contains the geotechnical parameters of Chengdu Clay used in the study titled “An Explainable Ensemble Machine Learning Approach for Coefficient of Compressibility Prediction”. The data includes [water content, specific gravity, liquidity index, plasticity index, and the measured coefficient of compressibility (av)] collected from [borehole samples in Chengdu, China]. The dataset comprises a total of [338] samples and is organized in a single CSV file. It is intended to be used for training and validating machine learning models for predicting soil compressibility, ensuring the reproducibility of the aforementioned study.