Table 4 Classifiers and their Accuracy, Precision, Recall and F1-score without Normalization.
Classifier | Image Matrix | Accuracy | Precision | Recall | F1-Score |
|---|---|---|---|---|---|
SVM | 64 | 86% | 0.80 | 0.88 | 0.84 |
128 | 86% | 0.83 | 0.83 | 0.83 | |
256 | 88% | 0.83 | 0.89 | 0.86 | |
KNN | 64 | 80% | 0.72 | 0.87 | 0.79 |
128 | 81% | 0.78 | 0.76 | 0.77 | |
256 | 83% | 0.85 | 0.72 | 0.78 | |
RF | 64 | 83% | 0.75 | 0.89 | 0.82 |
128 | 84% | 0.76 | 0.86 | 0.81 | |
256 | 84% | 0.79 | 0.85 | 0.80 | |
XGBoost | 64 | 86% | 0.80 | 0.88 | 0.84 |
128 | 86% | 0.83 | 0.83 | 0.83 | |
256 | 88% | 0.83 | 0.89 | 0.86 |
