Table 2 Highest AUC values obtained from RF and SVM for different feature sets
From: BaPreS: a software tool for predicting bacteriocins using an optimal set of features
Feature set | Machine learning model | AUC |
|---|---|---|
MDG-reduced | RF | 0.9873 |
SVM | 0.9809 | |
t-test-reduced | RF | 0.9864 |
SVM | 0.9794 |