However, for the models trained the SVM method and ECFPs (Tables S20–S24), feature selection won't influence the performance relative to the full features, since there is no significant difference among these models according to the criterion (p-value < 0.0001). However, it is worth mentioning that the model trained with 128 features (AM92, F1 = 0.905) has significant difference of F1-score compared with the counterpart trained with 512 features (AM44, F1 = 0.921) based on the criterion (p-value < 0.0001).