Table 7 Performance assessment of PDDNet‑EA and PDDNet‑LVE models
From: Using transfer learning-based plant disease classification and detection for sustainable agriculture
Performance Criteria | PDDNet‑EA model (%) | PDDNet‑LVE Model (%) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
identifier | NB | LR | RF | KNN | SVM | NB | LR | RF | KNN | SVM |
F1- scores | 0.685 | 0.942 | 0.771 | 0.853 | 0.913 | 0.684 | 0.944 | 0.774 | 0.856 | 0.916 |
Recall | 0.670 | 0.967 | 0.793 | 0.876 | 0.928 | 0.672 | 0.968 | 0.795 | 0.877 | 0.926 |
Precision | 0.932 | 0.975 | 0.932 | 0.839 | 0.908 | 0.934 | 0.977 | 0.930 | 0.840 | 0.909 |