Table 1 Six evaluate performances for different classifiers
Classifier | Accuracy | Sensitivity | Specificity | NPV | PPV | AUC |
|---|---|---|---|---|---|---|
SVM | 85.14% | 79.39% | 89.56% | 84.98% | 85.38% | 85.11% |
RF | 85.14% | 82.46% | 87.21% | 86.62% | 83.19% | 91.38% |
GlmNet | 86.29% | 82.46% | 89.23% | 86.89% | 85.45% | 92.6% |
LDA | 86.48% | 81.14% | 90.57% | 86.22% | 86.85% | 92.51% |
LG | 86.48% | 83.33% | 88.89% | 87.42% | 85.20% | 92.84% |
K-NN | 84.95% | 74.56% | 92.93% | 82.63% | 89.01% | — |