Table 12.
The evaluation metrics for machine learning used by the 56 HGR models.
| Evaluation Metric | IDs of the SPS |
|---|---|
| Accuracy | All HGR models, except SPS 18, SPS 37, and SPS 38 |
| Recall | SPS 2, SPS 3, SPS 4, SPS 8, SPS 9, SPS 12, SPS 14, SPS 17, SPS 18, SPS 19, SPS 24, SPS 26, SPS 28, SPS 29, SPS 31, SPS 33, SPS 35, SPS 36, SPS 39, SPS 40, SPS 42, SPS 44, SPS 46, SPS 49, SPS 53, SPS 55, and SPS 56 |
| Precision | SPS 2, SPS 8, SPS 9, SPS 14, SPS 35, SPS 36, SPS 44, SPS 53, and SPS 56 |
| Accuracy per User | SPS 1, SPS 5, SPS 6, SPS 16, SPS 26, SPS 31, SPS 33, SPS 38, SPS 39, SPS 48, SPS 52, SPS 53, and SPS 56 |
| Recall per User | SPS 15, and SPS 26 |
| Precision per User | SPS 15, and SPS 39 |
| Median of the Accuracy per User | SPS 6 |
| Standard Deviation of the Accuracy per User | SPS 1, SPS 5, SPS 7, SPS 20, SPS 35 |
| Standard Deviation of the Accuracy per Class | SPS 17 |
| Standard Deviation of each User Accuracy | SPS 5 |
| Standard Deviation of the Recalls of each Class | SPS 17 |
| Kappa Index | SPS 46 |
| Accuracy Error | SPS 37 |