Figure 1:
Figure 2:
Figure 3:
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Figure 5:
Figure 6:
Performance measure of case 1 (combined features + PCA)
| Algorithm | Accuracy | Precision | Recall | F-1 Score |
|---|---|---|---|---|
| LR | 0.99 | 0.99 | 0.97 | 0.98 |
| K-NN | 0.98 | 0.97 | 0.96 | 0.97 |
| SVM | 0.98 | 0.97 | 0.96 | 0.97 |
Performance measure of case 2 (combined features + LDA)
| Algorithm | Accuracy | Precision | Recall | F-1 Score |
|---|---|---|---|---|
| LR | 0.97 | 0.96 | 0.92 | 0.94 |
| K-NN | 0.96 | 0.96 | 0.90 | 0.92 |
| SVM | 0.96 | 0.96 | 0.90 | 0.92 |
Performance measure of case 3 (combined features)
| Algorithm | Accuracy | Precision | Recall | F-1 Score |
|---|---|---|---|---|
| LR | 0.98 | 0.96 | 0.96 | 0.96 |
| K-NN | 0.95 | 0.96 | 0.89 | 0.92 |
| SVM | 0.95 | 0.96 | 0.89 | 0.92 |
Comparison with other techniques
| References | Classifier | Accuracy (%) |
|---|---|---|
| [41] | Decision tree | 99 |
| [42] | Multilayer perceptron neural network | 99 |
| [43] | ANN | 98.30 |
| [44] | SVM | 97.98 |
| [45] | PCA with RF | 92.69 |
| [45] | PCA with ANN | 97.55 |
| Proposed model | LR | 99 |