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Table F.19
[Resubstitution prediction] – Measures from confusion matrices.
| Measures per class | ||||||
|---|---|---|---|---|---|---|
| C1 | C2 | C3 | C4 | C5 | ||
| tree bagger | Accuracy | 99.98% | 99.95% | 99.94% | 99.97% | 100% |
| Precision | 99.86% | 99.91% | 99.92% | 99.91% | 100% | |
| Sensitivity | 100% | 99.91% | 99.81% | 99.94% | 100% | |
| Specificity | 99.98% | 99.97% | 99.98% | 99.98% | 100% | |
| F-score | 99.93% | 99.91% | 99.87% | 99.92% | 100% | |
| gentle boost | Accuracy | 99.55% | 98.81% | 98.20% | 98.62% | 99.66% |
| Precision | 98.24% | 98.62% | 96.99% | 94.83% | 98.70% | |
| Sensitivity | 98.24% | 97.01% | 95.14% | 98.55% | 99.26% | |
| Specificity | 99.74% | 99.49% | 99.12% | 98.63% | 99.74% | |
| F-score | 98.24% | 97.81% | 96.06% | 96.65% | 98.98% | |
| svm (linear) | Accuracy | 99.93% | 98.80% | 97.60% | 98.53% | 99.81% |
| Precision | 99.62% | 98.84% | 95.35% | 94.47% | 99.52% | |
| Sensitivity | 99.86% | 96.76% | 94.16% | 98.49% | 99.33% | |
| Specificity | 99.94% | 99.57% | 98.63% | 98.53% | 99.90% | |
| F-score | 99.74% | 97.79% | 94.75% | 96.44% | 99.42% | |
| svm (rbf) | Accuracy | 99.89% | 99.56% | 99.44% | 99.65% | 99.87% |
| Precision | 99.43% | 99.64% | 98.68% | 98.77% | 99.59% | |
| Sensitivity | 99.71% | 98.75% | 98.91% | 99.49% | 99.63% | |
| Specificity | 99.92% | 99.87% | 99.60% | 99.69% | 99.92% | |
| F-score | 99.57% | 99.19% | 98.79% | 99.13% | 99.61% | |
| Average per-class | ||
|---|---|---|
| tree bagger | Accuracy | 99.97% |
| Error rate | 0.03% | |
| Precision | 99.92% | |
| Sensitivity | 99.93% | |
| F-score | 99.93% | |
| gentle boost | Accuracy | 98.97% |
| Error rate | 1.03% | |
| Precision | 97.48% | |
| Sensitivity | 97.64% | |
| F-score | 97.56% | |
| svm (linear) | Accuracy | 98.93% |
| Error rate | 1.07% | |
| Precision | 97.56% | |
| Sensitivity | 97.72% | |
| F-score | 97.64% | |
| svm (rbf) | Accuracy | 99.68% |
| Error rate | 0.32% | |
| Precision | 99.22% | |
| Sensitivity | 99.30% | |
| F-score | 99.26% | |
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