Table 4.
Comparison between Precision, recall, F1, and Accuracy of experiments without SMOT for dataset 1.
| ML Classifiers | Class/Average | Precision | Recall | F1-Score | Accuracy |
|---|---|---|---|---|---|
| DT | AVM | 97.86 % | 97.16 % | 97.51 % | 98.76 % |
| Normal | 99.06 % | 99.29 % | 99.18 % | ||
| Average | 98.46 % | 98.23 % | 98.34 % | ||
| KNN | AVM | 100.00 % | 75.89 % | 86.29 % | 93.99 % |
| Normal | 92.59 % | 100.00 % | 96.15 % | ||
| Average | 96.30 % | 87.94 % | 91.22 % | ||
| LR | AVM | 100.00 % | 92.91 % | 96.32 % | 98.23 % |
| Normal | 97.70 % | 100.00 % | 98.84 % | ||
| Average | 98.85 % | 96.45 % | 97.58 % | ||
| NB | AVM | 61.94 % | 58.87 % | 60.36 % | 80.74 % |
| Normal | 86.57 % | 88.00 % | 87.28 % | ||
| Average | 74.26 % | 73.43 % | 73.82 % | ||
| RF | AVM | 100.00 % | 88.65 % | 93.98 % | 97.17 % |
| Normal | 96.37 % | 100.00 % | 98.15 % | ||
| Average | 98.19 % | 94.33 % | 96.07 % | ||
| SVM | AVM | 100.00 % | 81.56 % | 89.84 % | 95.40 % |
| Normal | 94.24 % | 100.00 % | 97.03 % | ||
| Average | 97.12 % | 90.78 % | 93.44 % |