Skip to main content
. 2024 Feb 8;13(2):168. doi: 10.3390/antibiotics13020168

Table 8.

The analysis of the cross-prediction performance of RF, ET, and SVC-based models for GP, GN, and GV ABPs, respectively, using AAB binary feature of NC-terminal on different validation datasets.

Validation Dataset Performance Measures Models
Gram-Positive Gram-Negative Gram-Variable
Gram-positive
ABPs
Sn 80.7 50.0 67.7
Sp 90.3 89.3 87.6
Acc 85.5 69.6 77.7
AUC 0.93 0.85 0.88
AUPRC 0.92 0.83 0.87
MCC 0.71 0.43 0.57
Gram-negative
ABPs
Sn 66.0 92.4 91.1
Sp 89.4 94.9 87.3
Acc 77.7 93.6 89.2
AUC 0.89 0.98 0.93
AUPRC 0.85 0.98 0.92
MCC 0.57 0.87 0.78
Gram-variable
ABPs
Sn 80.2 76.2 83.9
Sp 87.4 92.0 90.1
Acc 83.8 84.1 87.0
AUC 0.91 0.93 0.94
AUPRC 0.89 0.93 0.93
MCC 0.68 0.69 0.74

Sn: Sensitivity, Sp: Specificity, Acc: Accuracy, MCC: Matthews correlation coefficient, AUC: Area under the receiver operating characteristic curve, AUPRC: Area under the precision-recall curve.