This code repository contains the machine learning models and analysis used in the study "Utilizing Advanced Machine Learning Approaches for Predicting Bioaccessibility of Cd, Pb, and As: Informing Soil Environmental Criteria Derivation in Chinese Sites". We leverage ensemble learning algorithms to predict the bioaccessibility of Cadmium (Cd), Lead (Pb), and Arsenic (As) in soil, aiming to inform the derivation of soil environmental criteria in Chinese contexts.
The following libraries are required:
- numpy
- pandas
- scikit-learn
- matplotlib
- xgboost
- catboost
- pytorch
To install these dependencies, run the following command:
pip install numpy pandas scikit-learn matplotlib