Table 3.
Performance of machine-learning algorithms to detect significant aortic regurgitation
| Classifier | Accuracy | Area-under-the-curve | True positive rate | True negative rate |
|---|---|---|---|---|
| Ensemble | 0.91 | 0.73 | 0.75 | 0.92 |
| Random forest | 0.91 | 0.72 | 0.71 | 0.91 |
| k-nearest neighbor | 0.89 | 0.55 | 0.00 | 0.89 |
| Support vector machine | 0.89 | 0.50 | 0.11 | 0.00 |
| Kernel support vector machine | 0.89 | 0.50 | 0.11 | 0.00 |
| Naïve Bayes | 0.89 | 0.73 | 0.50 | 0.90 |
| Karnel naïve Bayes | 0.89 | 0.73 | 0.50 | 0.90 |
| Decision tree | 0.89 | 0.76 | 0.50 | 0.94 |