Table 4.
The performance of different classification algorithms on 5-class-dataset according to fgose.
| Algorithm | Acc (%) | Acc rank | Rec1 (%) | Rec2 (%) | Rec3 (%) | Rec4 (%) | Rec5 (%) |
|---|---|---|---|---|---|---|---|
| NB | 59.46 ± 3.22 | 6 | 50.51 | 11.11 | 0.99 | 2.02 | 83.95 |
| RF | 64.97 ± 2.72 | 2 | 46.21 | 0.00 | 0.00 | 0.00 | 96.64 |
| KNN(k = 5) | 55.89 ± 3.72 | 8 | 35.86 | 0.00 | 0.99 | 10.61 | 82.43 |
| KNN(k = 6) | 56.20 ± 1.74 | 7 | 35.35 | 0.00 | 0.00 | 9.09 | 83.62 |
| DT | 63.16 ± 1.58 | 4 | 55.05 | 0.00 | 0.00 | 1.52 | 89.26 |
| RI | 62.67 ± 2.33 | 5 | 47.47 | 0.00 | 0.00 | 5.05 | 90.89 |
| DL | 64.37 ± 1.56 | 3 | 55.30 | 0.00 | 1.98 | 3.54 | 90.67 |
| GBT | 64.97 ± 1.62 | 1 | 59.85 | 0.00 | 0.99 | 1.01 | 90.46 |
| Avg Acc | 61.46 |