Fig. 4.

a The relationship between the number of decision trees in random forest and the performance of the model. When the number of decision trees was set to 10, 25, 40, 55, 70, 85 and 100, respectively, the performance of random forest model shows a trend of rising first and then declining, and its inflection point appeared at 70. b Area under curve (AUC) at different final partition index. The Gini index demonstrated a better effect compared with Information gain index. For Gini index model, the AUC is 0.864. c AUC at different number of sub-samples (Nsub) randomly sampled for each decision tree in training. The best performance was acquired when Nsub was equal to the log₂N which AUC is 0.871. d Area under curve (AUC) at different minimum number of samples (Nmin) partitioned by each node. The best performance was acquired when Nmin was equal to 6 which AUC is 0.914