Encoding | ML algorithm | Sensitivity | Specificity | Accuracy | MCC |
---|---|---|---|---|---|
AAC | OET-KNN | 71.34 | 81.08 | 76.28 | 0.5271 |
KNN | 75.72 | 74.87 | 75.29 | 0.5058 | |
SVM | 70.96 | 83.47 | 77.30 | 0.5492 | |
GBM | 71.86 | 83.75 | 77.89 | 0.5606 | |
RF | 68.11 | 85.13 | 76.73 | 0.5409 | |
PseAAC | OET-KNN | 73.05 | 81.38 | 77.27 | 0.5465 |
KNN | 74.24 | 79.38 | 76.84 | 0.5370 | |
SVM | 70.59 | 83.98 | 77.37 | 0.5511 | |
GBM | 74.99 | 86.07 | 80.60 | 0.6149 | |
RF | 68.84 | 84.86 | 76.95 | 0.5446 | |
PAAC | OET-KNN | 68.94 | 72.09 | 70.53 | 0.4105 |
KNN | 72.96 | 66.26 | 69.57 | 0.3930 | |
SVM | 76.15 | 84.22 | 80.24 | 0.6060 | |
GBM | 71.33 | 85.01 | 77.84 | 0.5661 | |
RF | 71.00 | 81.67 | 76.41 | 0.5301 | |
SAAC | OET-KNN | 66.63 | 72.88 | 69.80 | 0.3960 |
KNN | 69.75 | 68.81 | 69.28 | 0.3856 | |
SVM | 72.51 | 85.85 | 79.27 | 0.5895 | |
GBM | 73.90 | 85.95 | 80.00 | 0.6034 | |
RF | 67.82 | 87.02 | 77.54 | 0.5595 | |
Pse-PSSM, \(\lambda =0\) | OET-KNN | 86.57 | 92.75 | 89.70 | 0.7953 |
KNN | 85.22 | 90.44 | 87.86 | 0.7580 | |
SVM | 83.23 | 90.05 | 86.68 | 0.7350 | |
GBM | 83.41 | 90.45 | 86.98 | 0.7409 | |
RF | 79.45 | 92.53 | 86.08 | 0.7269 | |
Pse-PSSM, \(\lambda =1\) | OET-KNN | 85.92 | 91.79 | 88.89 | 0.7788 |
KNN | 85.89 | 89.06 | 87.50 | 0.7501 | |
SVM | 86.75 | 92.22 | 89.52 | 0.7912 | |
GBM | 85.00 | 92.19 | 88.64 | 0.7744 | |
RF | 79.86 | 93.66 | 86.85 | 0.7433 | |
Pse-PSSM, \(\lambda =2\) | OET-KNN | 85.51 | 91.90 | 88.75 | 0.7762 |
KNN | 85.65 | 88.28 | 86.98 | 0.7397 | |
SVM | 86.83 | 92.06 | 89.48 | 0.7904 | |
GBM | 84.86 | 91.72 | 88.34 | 0.7682 | |
RF | 79.80 | 93.70 | 86.84 | 0.7432 |