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Table F.9
[Resubstitution prediction] – Measures from confusion matrices
| Measures per class | ||||
|---|---|---|---|---|
| “0” | “+1” | “+2” | ||
| tree bagger | Accuracy | 99.93% | 98.69% | 98.75% |
| Precision | 99.93% | 94.41% | 100% | |
| Sensitivity | 99.80% | 99.94% | 97.53% | |
| Specificity | 99.97% | 98.34% | 100% | |
| F-score | 99.87% | 97.10% | 98.75% | |
| gentle boost | Accuracy | 92.27% | 80.10% | 87.78% |
| Precision | 92.85% | 52.84% | 96.35% | |
| Sensitivity | 78.01% | 85.68% | 78.77% | |
| Specificity | 97.71% | 78.53% | 96.96% | |
| F-score | 84.79% | 65.37% | 86.68% | |
| svm (linear) | Accuracy | 91.95% | 83.01% | 90.96% |
| Precision | 88.86% | 60.71% | 89.95% | |
| Sensitivity | 80.98% | 63.66% | 92.41% | |
| Specificity | 96.13% | 88.44% | 89.47% | |
| F-score | 84.74% | 62.15% | 91.16% | |
| svm (rbf) | Accuracy | 92.41% | 81.30% | 88.86% |
| Precision | 90.70% | 55.14% | 94.62% | |
| Sensitivity | 80.81% | 78.79% | 82.63% | |
| Specificity | 96.84% | 82% | 95.21% | |
| F-score | 85.47% | 64.87% | 88.22% | |
| Average per-class | ||
|---|---|---|
| tree bagger | Accuracy | 99.12% |
| Error rate | 0.88% | |
| Precision | 98.11% | |
| Sensitivity | 99.09% | |
| F-score | 98.60% | |
| gentle boost | Accuracy | 86.72% |
| Error rate | 13.28% | |
| Precision | 80.68% | |
| Sensitivity | 80.82% | |
| F-score | 80.75% | |
| svm (linear) | Accuracy | 88.64% |
| Error rate | 11.36% | |
| Precision | 79.84% | |
| Sensitivity | 79.02% | |
| F-score | 79.43% | |
| svm (rbf) | Accuracy | 87.52% |
| Error rate | 12.48% | |
| Precision | 80.15% | |
| Sensitivity | 80.74% | |
| F-score | 80.45% | |
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