Table 16 FS vs. FE for multiclass classification with 77 (full) features
Models | Accuracy (%) | Precision (%) | Re-call (%) | F1-score (%) | MCC | FS (s) | Training (s) | Inference (ms) |
|---|---|---|---|---|---|---|---|---|
Feature selection | ||||||||
 DT | 51.29 | 33.16 | 25.02 | 16.00 | 0.2450 | 0 | 1.94 | 16.79 |
 RF | 69.38 | 29.90 | 21.68 | 19.06 | 0.3507 | 13.46 | 758.22 | |
 kNN | 57.24 | 48.56 | 34.46 | 25.69 | 0.3720 | 0.48 | 187,612.41 | |
 NB | 20.14 | 34.66 | 41.28 | 19.76 | 0.1973 | 0.79 | 257.37 | |
 MLP | 77.47 | 67.96 | 46.03 | 41.56 | 0.5796 | 151.02 | 117.19 | |
Feature extraction | ||||||||
 DT | 54.98 | 38.23 | 34.68 | 22.60 | 0.2982 | 3.98 | 10.01 | 16.80 |
 RF | 76.84 | 62.80 | 44.55 | 39.72 | 0.5661 | 48.97 | 801.26 | |
 kNN | 57.25 | 45.09 | 34.42 | 25.47 | 0.3718 | 0.49 | 188,883.26 | |
 NB | 22.50 | 34.92 | 42.80 | 22.52 | 0.2204 | 0.76 | 322.33 | |
 MLP | 77.46 | 68.01 | 46.05 | 41.53 | 0.5796 | 116.71 | 118.47 | |