Fig. 3

Schematic diagram of random forests (RFs). An RF is an ensemble learning approach that consists of multiple decision trees. In the process of training the RF model, each decision tree is trained in sequence, and the training samples of each tree are extracted from the original datasets by a randomized sampling method. The features used in each decision tree are also obtained by random sampling. The joint prediction of multiple decision trees improves the accuracy of the RF model