Table 7.
Performance statistics of three optimal ML models (with the highest classification accuracy at the 3, 5 and 11 s time window on the CBS test dataset) used for classifying walking, standing, grazing, lying and running on the CBS test dataset.
| Time Window | Model | Performance | Walking | Standing | Grazing | Lying | Running |
|---|---|---|---|---|---|---|---|
| 3 s | Stacking | Precision (%) | 99.3 | 81.9 | 98.5 | 75.8 | 90.3 |
| Recall (%) | 95.4 | 72.8 | 100.0 | 85.4 | 75.7 | ||
| F-score (%) | 97.3 | 77.1 | 99.3 | 80.3 | 82.4 | ||
| 5 s | ELM | Precision (%) | 99.6 | 73.2 | 95.4 | 89.9 | -- |
| Recall (%) | 88.6 | 91.9 | 100.0 | 69.3 | -- | ||
| F-score (%) | 93.8 | 81.4 | 97.6 | 78.3 | -- | ||
| 11 s | ELM | Precision (%) | 97.9 | 63.3 | 82.4 | 92.5 | -- |
| Recall (%) | 59.1 | 94.6 | 100.0 | 52.6 | -- | ||
| F-score (%) | 73.7 | 75.9 | 90.4 | 67.1 | -- |