Machine learning-based pedo transfer function for estimating the soil compression index

The primary objective of this research is to develop an ML-PTF on the extreme gradient boosting (XGB) framework capable of estimating soil compression index with high precision and low effort. Furthermore, advancing the quantitative knowledge of which soil structural indicators determine soil compressibility using correlation analysis.