Using machine learning classifiers, the best model is obtained by testing the different parameters of the selected model with the positive and negative sample genes provided by the user for a certain trait, and predicting whether the direct connection point in the positive sample belongs to the trait (Note: If the number of directly connected genes of the positive sample exceeds 300 genes, the program will randomly select 300 genes ).