Table 5 Summary of the best classification results.
Classifiers | Dataset (description) | Confusion matrix | Accuracy | Precision | Recall | F1 score | ||
|---|---|---|---|---|---|---|---|---|
Bagging (NB) | D1 (Loreto Subset-1) | Class | LBW | ABW | 89.47 | 89.1 | 89.4 | 0.89 |
LBW | 7 | 11 | ||||||
ABW | 7 | 139 | ||||||
LR | Loreto (D2 with mean, mode) | LBW | 4 | 14 | 88.81 | 86.8 | 88.8 | 0.86 |
ABW | 4 | 142 | ||||||
LR | Total Dataset (100% smote) | LBW | 6 | 12 | 90.24 | 87.6 | 90.2 | 0.89 |
ABW | 4 | 142 | ||||||
Bagging (REP) | Total Dataset (Balance) | LBW | 11 | 7 | 78.13 | 87.3 | 78.1 | 0.81 |
ABW | 29 | 117 | ||||||
