ABSTRACT
This practice focuses on one of the simplest yet effective machine learning models, the random forest model. We will first introduce basic concepts in random forest modeling and then apply this model to an example of predicting soil organic carbon (SOC) distributions across the ecosystems of North Macedonia, a country in Southeast Europe. We will compare the predicting results from the random forest with linear regression models. At the end of this practice, we will discuss the interpretability of the random forest model.
