Research Article
Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset
Table 7
Comparisons of predictive performance among different sampling methods.
| Group | Training phase | Testing phase | AC (%) | SE (%) | SP (%) | AC (%) | SE (%) | SP (%) | G-mean | AUC |
| Random undersampling with OB1 | 68.57 | 74.82 | 62.32 | 63.16 | 77.00 | 62.36 | 0.6929 | 0.7590 | Random undersampling with OB2 | 68.92 | 68.92 | 68.92 | 68.30 | 70.03 | 68.20 | 0.6909 | 0.7495 | Clustering-based kNN undersampling with OB1 | 71.25 | 75.66 | 66.84 | 63.40 | 76.19 | 62.20 | 0.6884 | 0.7526 | Clustering-based kNN undersampling with OB2 | 71.25 | 71.25 | 71.25 | 67.28 | 69.84 | 67.00 | 0.6840 | 0.7515 | One-sided selection + OB1 | 77.80 | 82.59 | 35.62 | 94.54 | 0 | 100 | 0 | 0.7007 | One-sided selection + OB2 | 89.75 | 1.41 | 99.79 | 71.43 | 41.98 | 73.13 | 0.5541 | 0.6626 |
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