Table 7 FS vs. FE for binary classification with 22 features
Models | Accuracy (%) | Precision (%) | Re-call (%) | F1-score (%) | MCC | FS (s) | Training (s) | Inference (ms) |
|---|---|---|---|---|---|---|---|---|
Feature selection | ||||||||
 DT | 81.27 | 80.00 | 78.55 | 79.15 | 0.5853 | 7.82 | 0.46 | 11.85 |
 RF | 77.72 | 84.92 | 69.30 | 70.57 | 0.5192 | 8.99 | 776.08 | |
 kNN | 78.65 | 85.26 | 70.66 | 72.19 | 0.5398 | 0.07 | 196,772.36 | |
 NB | 78.34 | 85.02 | 70.24 | 71.69 | 0.5324 | 0.17 | 28.58 | |
 MLP | 81.27 | 80.00 | 78.55 | 79.15 | 0.5853 | 56.56 | 174.12 | |
Feature extraction | ||||||||
 DT | 85.94 | 84.49 | 85.55 | 84.94 | 0.7119 | 4.92 | 1.84 | 12.71 |
 RF | 86.54 | 85.11 | 86.37 | 85.63 | 0.7147 | 26.44 | 631 | |
 kNN | 64.29 | 62.85 | 63.80 | 62.82 | 0.7287 | 0.05 | 193,070.46 | |
 NB | 84.77 | 83.26 | 84.75 | 83.83 | 0.6799 | 0.19 | 37.25 | |
 MLP | 86.53 | 85.11 | 86.42 | 85.64 | 0.7151 | 128.43 | 478.01 | |