Table 13 Results of classifiers (in %) with Dispersion Ratio.
Classifier | Training accuracy | Testing accuracy | Precision | Sensitivity | Specificity | F1 score | AUC |
|---|---|---|---|---|---|---|---|
LR | 80.7 | 80.3 | 80 | 85 | 75 | 83 | 87 |
DT | 87.6 | 82.4 | 79 | 93 | 63 | 85 | 91 |
RF | 88.6 | 85.3 | 85 | 89 | 80 | 87 | 93 |
KNN | 78.8 | 71.4 | 75 | 72 | 71 | 73 | 76 |
SVM | 80.9 | 81.9 | 83 | 85 | 79 | 84 | 87 |
GNB | 81.5 | 79.8 | 82 | 81 | 79 | 82 | 87 |
XGBoost | 100 | 91.2 | 92 | 92 | 91 | 92 | 96 |
AdaBoost | 86.7 | 83.6 | 85 | 86 | 81 | 85 | 90 |
SGD | 74.7 | 72.1 | 84 | 62 | 86 | 71 | 75 |
GB | 99.1 | 89.9 | 90 | 92 | 87 | 91 | 96 |
ETC | 86.1 | 84 | 84 | 88 | 79 | 86 | 91 |
CatBoost | 87.4 | 84.5 | 96 | 75 | 96 | 84 | 95 |
LightGBM | 95.3 | 86.1 | 95 | 79 | 94 | 86 | 96 |
MLP | 71 | 67.6 | 64 | 94 | 33 | 77 | 85 |
RNN | 87.4 | 83.6 | 92 | 55 | 94 | 69 | 75 |
LSTM | 86.7 | 83.2 | 91 | 62 | 93 | 74 | 77 |
GRU | 87.4 | 84 | 92 | 63 | 94 | 75 | 78 |
Bi-LSTM | 87.4 | 81.1 | 94 | 66 | 94 | 77 | 80 |
Bi-GRU | 82.4 | 83.2 | 94 | 66 | 94 | 77 | 80 |
CNN | 86.3 | 85.9 | 94 | 69 | 95 | 79 | 82 |
Hybrid Model | 100 | 100 | 100 | 100 | 100 | 100 | 100 |
