Table 18 Comparison of accuracy achieved by different combinations of feature extraction (ABC and ABC-PSO), feature selection methods (HS, DFA, and EHA), and classifiers (SVM with RBF kernel) on NITP and PIDD datasets.
Feature extraction method | Feature selection method | Classifiers | Accuracy (%) | |
|---|---|---|---|---|
NITP dataset | PIDD | |||
ABC | Without FS | SVM (RBF) | 87.14 | 88.83 |
ABC PSO | 88.57 | 89.74 | ||
ABC | With HS | SVM (RBF) | 88.57 | 93.63 |
ABC PSO | 91.42 | 92.85 | ||
ABC | With DFA | SVM (RBF) | 91.42 | 95.45 |
ABC PSO | 92.85 | 96.36 | ||
ABC | With EHA | SVM (RBF) | 94.28 | 94.28 |
ABC PSO | 97.14 | 98.57 | ||
