Table 13 FS vs. FE for multiclass classification with 22 features
Models | Accuracy (%) | Precision (%) | Re-call (%) | F1-score (%) | MCC | FS (s) | Training (s) | Inference (ms) |
|---|---|---|---|---|---|---|---|---|
Feature selection | ||||||||
 DT | 73.52 | 59.02 | 35.47 | 32.53 | 0.4781 | 7.82 | 1.60 | 19.29 |
 RF | 69.24 | 28.63 | 21.32 | 16.82 | 0.3446 | 10.19 | 790.10 | |
 kNN | 72.55 | 60.57 | 30.39 | 28.82 | 0.4451 | 0.64 | 192,447.54 | |
 NB | 19.36 | 34.90 | 41.03 | 17.70 | 0.2758 | 1.58 | 99.98 | |
 MLP | 73.52 | 59.02 | 35.47 | 32.53 | 0.4781 | 107.55 | 179.01 | |
Feature extraction | ||||||||
 DT | 77.25 | 72.18 | 48.18 | 45.00 | 0.5840 | 4.92 | 3.47 | 12.93 |
 RF | 77.14 | 61.21 | 45.24 | 40.45 | 0.5716 | 25.02 | 922.89 | |
 kNN | 51.86 | 41.04 | 31.09 | 29.50 | 0.5809 | 1.23 | 200,249.55 | |
 NB | 55.84 | 37.60 | 63.32 | 41.57 | 0.4618 | 1.92 | 169.60 | |
 MLP | 77.43 | 66.47 | 46.00 | 41.50 | 0.5793 | 180.86 | 135.30 | |