Table 2 Comparison of solutions to the data imbalance issue on the edge detection dataset.
From: Self-training in significance space of support vectors for imbalanced biomedical event data
Class label | Precision (%) | Recall (%) | F-measure (%) | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Â | Under-sampling | Class weighting | STSS | Under-sampling | Class weighting | STSS | Under-sampling | Class weighting | STSS |
AtLoc | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Cause | 100.0 | 42.24 | 47.36 | 4.48 | 25.95 | 43.67 | 8.51 | 32.14 | 45.44 |
Cause-Theme | 100.0 | 63.07 | 76.4 | 40.47 | 63.32 | 50.21 | 57.62 | 63.19 | 60.59 |
Site | 0.0 | 20.78 | 29.3 | 0.0 | 12.37 | 33.21 | 0.0 | 15.5 | 31.13 |
Theme | 53.87 | 60.91 | 57.16 | 42.21 | 62.37 | 90.83 | 47.33 | 61.63 | 70.16 |
ToLoc | 26.91 | 57.39 | 48.2 | 99.74 | 54.33 | 96.11 | 42.38 | 55.81 | 64.2 |
Negative | 89.66 | 92.35 | 100.0 | 100.0 | 100.0 | 100.0 | 94.54 | 96.02 | 100.0 |