Table 14 FS vs. FE for multiclass classification with 33 features
Models | Accuracy (%) | Precision (%) | Re-call (%) | F1-score (%) | MCC | FS (s) | Training (s) | Inference (ms) |
|---|---|---|---|---|---|---|---|---|
Feature selection | ||||||||
 DT | 77.23 | 77.23 | 45.69 | 41.00 | 0.5750 | 8.28 | 1.20 | 15.34 |
 RF | 70.21 | 37.68 | 23.57 | 20.42 | 0.3751 | 26.77 | 1558.13 | |
 kNN | 76.23 | 65.60 | 40.58 | 37.63 | 0.5440 | 0.69 | 225,211.54 | |
 NB | 32.64 | 29.45 | 45.45 | 23.91 | 0.2758 | 0.96 | 157.66 | |
 MLP | 77.28 | 66.66 | 45.83 | 41.26 | 0.5762 | 158.29 | 198.80 | |
Feature extraction | ||||||||
 DT | 77.62 | 67.34 | 48.67 | 45.53 | 0.5831 | 6.13 | 5.18 | 21.81 |
 RF | 77.33 | 61.54 | 45.64 | 41.19 | 0.5753 | 30.58 | 901.71 | |
 kNN | 66.34 | 46.62 | 33.70 | 30.94 | 0.4532 | 0.66 | 227,584.21 | |
 NB | 44.71 | 42.86 | 57.43 | 39.01 | 0.3895 | 1.67 | 233.32 | |
 MLP | 77.45 | 68.01 | 46.00 | 41.50 | 0.5792 | 213.14 | 194.79 | |