Table 2.
Specificity and Sensitivity of different models (95% confidence interval)
| Partial Data fields | Model s | Phase | Specificity | Sensitivity |
|---|---|---|---|---|
| RC-NN on Part1 | Train | 99.91 (97.95-99.93) | 99.58 (97.62-100) | |
| Test | 99.37 (97.41-100) | 100.00 (98.04-100) | ||
| RC-NN on Part2 | Train | 99.27 (96.92-100) | 92.49 (90.13-94.84) | |
| Test | 99.51(97.16-100) | 89.28 (86.93-91.63) | ||
| Neural Network Model | Train | 99.42 (97.26-100) | 97.04 (94.88-99.19) | |
| Test | 99.37 (97.21-100) | 96.57 (94.41-98.72) | ||
| Genetic Programming | Train | 99.51 (96.76-100) | 90.53 (87.77-93.25) | |
| Test | 98.00 (95.26-99.65) | 91.47 (88.72-94.21) | ||
| All Data fields | Neural Network Model | Train | 93.54 (91.77-95.30) | 100.00 (98.23-100) |
| Test | 93.04 (91.27-94.80) | 94.44 (92.67-96.21) | ||
| Random Forest | Train | 100.00 (97.35-100) | 100.00 (97.15-100) | |
| Test | 99.24 (96.59-100) | 90.24 (87.40-93.08) | ||
| Support Vector Machine | Train | 99.84 (97.64-100) | 89.64 (87.44-91.83) | |
| Test | 99.69 (97.49-100) | 83.12 (80.92-85.31) | ||
| Random Forest | Train | 99.98 (97.59-100) | 100 (97.61-100) | |
| Test | 99.47 (96.82-100) | 89.20 (86.55-91.84) | ||
| Support Vector Machine | Train | 99.84 (97.64-100) | 90.49 (88.29-92.68) | |
| Test | 99.62 (97.42-100) | 84.13 (81.93-86.32) | ||
| Ensembled | Train | 99.89 (98.32-100) | 96.58 (95.01-98.15) | |
| Test | 99.54 (97.97-100) | 90.21 (88.64-91.78) |