Table 3 Summary of prognosis indicators and their corresponding accuracies
From: Machine learning in critical care: state-of-the-art and a sepsis case study
Method | AUC | Error rate | Sens. | Spec. |
|---|---|---|---|---|
LR-FA | 0.78 | 0.24 | 0.65 | 0.80 |
LR | 0.75 | 0.30 | 0.64 | 0.72 |
APACHE II | 0.70 | 0.28 | 0.82 | 0.55 |
RVM | 0.86 | 0.18 | 0.67 | 0.87 |
SVM-Quotient | 0.89 | 0.18 | 0.70 | 0.86 |
SVM-Fisher | 0.76 | 0.18 | 0.68 | 0.86 |
SVM-EXP | 0.75 | 0.21 | 0.70 | 0.82 |
SVM-INV | 0.62 | 0.22 | 0.70 | 0.82 |
SVM-CENT | 0.75 | 0.21 | 0.70 | 0.82 |
SVM-GAUSS | 0.83 | 0.24 | 0.65 | 0.81 |
SVM-LIN | 0.62 | 0.26 | 0.62 | 0.78 |
SVM-POLY | 0.69 | 0.28 | 0.71 | 0.76 |