Algorithms | Accuracy | Speificity | Precision | PPV | NPV | AUCa |
---|---|---|---|---|---|---|
SVM-train | 0.868 | 0.992 | 0.912 | 0.912 | 0.864 | 0.936 |
SVM-test | 0.863 | 0.989 | 0.889 | 0.889 | 0.861 | 0.814 |
KNN-train | 0.859 | 0.971 | 0.761 | 0.761 | 0.870 | 0.861 |
KNN-test | 0.829 | 0.968 | 0.667 | 0.667 | 0.843 | 0.743 |
RandomForest-train | 0.959 | 0.989 | 0.949 | 0.949 | 0.962 | 0,986 |
RandomForest-test | 0.863 | 0.947 | 0.706 | 0.706 | 0.890 | 0.787 |
ExtraTrees-train | 0.964 | 1.000 | 1.000 | 1.000 | 0.957 | 0.994 |
ExtraTrees-test | 0.846 | 0.936 | 0.647 | 0.647 | 0.880 | 0.751 |
XGBoost-train | 0.878 | 0.984 | 0.867 | 0.867 | 0.880 | 0.931 |
XGBoost-test | 0.863 | 0.979 | 0.818 | 0.818 | 0.868 | 0.863 |