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Table F.10
[Test prediction] – Measures from confusion matrices.
| Measures per class | ||||
|---|---|---|---|---|
| “0” | “+1” | “+2” | ||
| tree bagger | Accuracy | 72.51% | 51.87% | 54.84% |
| Precision | 50.31% | 9.65% | 55.31% | |
| Sensitivity | 32% | 14.29% | 54.76% | |
| Specificity | 87.95% | 62.42% | 54.92% | |
| F-score | 39.12% | 11.52% | 55.04% | |
| gentle boost | Accuracy | 71.44% | 43.62% | 55.93% |
| Precision | 45.99% | 10.65% | 57.22% | |
| Sensitivity | 19.81% | 21.26% | 50.25% | |
| Specificity | 91.13% | 49.90% | 61.71% | |
| F-score | 27.70% | 14.19% | 53.51% | |
| svm (linear) | Accuracy | 71.87% | 51.99% | 53.91% |
| Precision | 48.15% | 5.84% | 53.89% | |
| Sensitivity | 24.78% | 7.87% | 60.07% | |
| Specificity | 89.83% | 64.38% | 47.63% | |
| F-score | 32.72% | 6.70% | 56.82% | |
| svm (rbf) | Accuracy | 71.60% | 46.24% | 56.26% |
| Precision | 46.91% | 10.26% | 57.15% | |
| Sensitivity | 21.90% | 18.75% | 53.28% | |
| Specificity | 90.55% | 53.96% | 59.29% | |
| F-score | 29.86% | 13.26% | 55.15% | |
| Average per-class | ||
|---|---|---|
| tree bagger | Accuracy | 59.74% |
| Error rate | 40.26% | |
| Precision | 38.42% | |
| Sensitivity | 33.68% | |
| F-score | 35.90% | |
| gentle boost | Accuracy | 57% |
| Error rate | 43% | |
| Precision | 37.95% | |
| Sensitivity | 30.44% | |
| F-score | 33.79% | |
| svm (linear) | Accuracy | 59.26% |
| Error rate | 40.74% | |
| Precision | 35.96% | |
| Sensitivity | 30.91% | |
| F-score | 33.24% | |
| svm (rbf) | Accuracy | 58.03% |
| Error rate | 41.97% | |
| Precision | 38.11% | |
| Sensitivity | 31.31% | |
| F-score | 34.38% | |
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