Table 14 Classification results on the proposed feature selection approach for grapes rot leaves
Method | FPR | Precision (%) | Sensitivity (%) | Specificity (%) | FNR (%) | Accuracy |
|---|---|---|---|---|---|---|
DT | 0.074 | 92.25 | 92.55 | 94.3 | 7.6 | 92.4 |
Q-SVM | 0.052 | 95.05 | 94.70 | 92.5 | 5.1 | 94.9 |
C-SVM | 0.052 | 95.05 | 94.07 | 92.5 | 5.1 | 94.9 |
QDA | 0.056 | 95.05 | 94.35 | 88.7 | 5.1 | 94.9 |
F-KNN | 0.045 | 96.05 | 95.50 | 92.5 | 4.2 | 95.8 |
W-KNN | 0.044 | 96.05 | 95.50 | 92.5 | 5.1 | 94.9 |
EBT | 0.044 | 96.50 | 95.50 | 92.5 | 4.2 | 95.8 |
ESDA | 0.053 | 95.05 | 94.70 | 92.5 | 5.1 | 94.9 |
M-SVM | 0.037 | 97.10 | 96.25 | 92.5 | 3.4 | 96.6 |