Table 5.
Training dataset | Testing dataset | ||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Sub dataset | Classifier | Accuracy | TP | TN | FP | FN | Sensitivity | Specificity | AUC ROC | Sub dataset | Classifier | Accuracy | TP | TN | FP | FN | Sensitivity | Specificity | AUC ROC |
5 Attributes | GEP | 100 | 17.13 | 82.87 | 0 | 0 | 100 | 100 | 1 | 5 Attributes | GEP | 99.45 | 16.57 | 82.87 | 0 | 0.55 | 96.77 | 100 | 1 |
SVM | 98.90 | 16.02 | 82.87 | 0 | 1.10 | 93.55 | 100 | 1 | SVM | 98.90 | 16.02 | 82.87 | 0 | 1.10 | 93.55 | 100 | 1 | ||
MLP | 100 | 17.13 | 82.87 | 0 | 0 | 100 | 100 | 1 | MLP | 99.45 | 16.57 | 82.87 | 0 | 0.55 | 96.77 | 100 | 1 | ||
RBF | 100 | 17.13 | 82.87 | 0 | 0 | 100 | 100 | 1 | RBF | 98.34 | 16.02 | 82.32 | 0.55 | 1.10 | 93.55 | 99.33 | 0.998 | ||
10 Attributes | GEP | 99.17 | 15.70 | 83.47 | 0 | 0.83 | 95 | 100 | 0.9 | 10 Attributes | GEP | 91.67 | 13.33 | 78.33 | 0 | 8.33 | 61.54 | 100 | 0.9 |
SVM | 99.45 | 16.57 | 82.87 | 0 | 0.55 | 96.77 | 100 | 0.999 | SVM | 99.45 | 16.57 | 82.87 | 0 | 0.55 | 96.77 | 100 | 0.998 | ||
MLP | 100 | 17.13 | 82.87 | 0 | 0 | 100 | 100 | 1 | MLP | 99.45 | 16.57 | 82.87 | 0 | 0.55 | 96.77 | 100 | 0.998 | ||
RBF | 99.45 | 16.57 | 82.87 | 0 | 0.55 | 96.77 | 100 | 1 | RBF | 97.24 | 14.92 | 82.32 | 0.55 | 2.21 | 87.10 | 99.33 | 0.998 | ||
20 Attributes | GEP | 99.17 | 14.05 | 85.12 | 0 | 0.83 | 94.44 | 100 | 0.9 | 20 Attributes | GEP | 91.67 | 13.33 | 78.33 | 0 | 8.33 | 61.54 | 100 | 0.9 |
SVM | 99.45 | 16.57 | 82.87 | 0 | 0.55 | 96.77 | 100 | 0.999 | SVM | 99.45 | 16.57 | 82.87 | 0 | 0.55 | 96.77 | 100 | 0.998 | ||
MLP | 98.34 | 15.47 | 82.87 | 0 | 1.66 | 90.32 | 100 | 0.999 | MLP | 98.34 | 15.47 | 82.87 | 0 | 1.66 | 90.32 | 100 | 0.991 | ||
RBF | 98.90 | 16.02 | 82.87 | 0 | 1.10 | 93.55 | 100 | 0.979 | RBF | 97.24 | 14.92 | 82.32 | 0.55 | 2.21 | 87.10 | 99.33 | 0.920 | ||
AS | GEP | 99.31 | 11.72 | 87.59 | 0 | 0.69 | 94.44 | 100 | 0.9 | AS | GEP | 91.67 | 27.78 | 63.89 | 0 | 8.33 | 76.92 | 100 | 0.9 |
SVM | 100 | 12.41 | 87.59 | 0 | 0 | 100 | 100 | 1 | SVM | 94.4 | 30.56 | 63.89 | 5.56 | 0 | 100 | 92 | 0.9 | ||
MLP | 97.9 | 10.34 | 87.59 | 2.07 | 0 | 100 | 97.69 | 0.9 | MLP | 94.4 | 30.56 | 63.89 | 5.56 | 0 | 100 | 92 | 0.9 | ||
RBF | 98.25 | 10.69 | 87.59 | 1.72 | 0 | 100 | 98 | 0.9 | RBF | 94.4 | 30.56 | 63.89 | 5.56 | 0 | 100 | 92 | 0.9 | ||
All Dataset | GEP | 100 | 49.66 | 50.34 | 0 | 0 | 100 | 100 | 1 | All Dataset | GEP | 83.33 | 33.33 | 50 | 0 | 16.67 | 66.67 | 100 | 0.7 |
SVM | 99.45 | 16.57 | 82.87 | 0 | 0.55 | 96.77 | 100 | 0.998 | SVM | 95.03 | 14.36 | 80.66 | 2.21 | 2.76 | 83.87 | 97.33 | 0.980 | ||
MLP | 99.45 | 16.57 | 82.87 | 0 | 0.55 | 96.77 | 100 | 1 | MLP | 93.92 | 14.36 | 79.56 | 3.31 | 2.76 | 83.87 | 96 | 0.960 | ||
RBF | 100 | 17.13 | 82.87 | 0 | 0 | 100 | 100 | 1 | RBF | 94.48 | 13.81 | 80.66 | 2.21 | 3.31 | 80.65 | 97.33 | 0.981 |