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Comparison of results from the different SVM classification algorithm designed.
| Classifiers | Kernel | (ACC, SEN, SEP) |
|---|---|---|
| Extracted features-SVM | Poly | (0.90, 0.88, 0.88) |
| RBF | (0.90, 0.90, 0.88) | |
| Linear | (0.89, 0.87, 0.87) | |
|
| ||
| All variables-SVM | Poly | (0.85, 0.85, 0.83) |
| RBF | (0.86, 0.85, 0.85) | |
| Linear | (0.83, 0.83, 0.85) | |
|
| ||
| Six variables-SVM | Poly | (0.86, 0.85, 0.85) |
| RBF | (0.87, 0.86, 0.85) | |
| Linear | (0.85, 0.85, 0.83) | |
Note: ACC, SEN, and SEP denote accuracy, sensitivity, and specificity, respectively.
