Table 8 Model evaluation(7–3)
From: A diabetes prediction model based on Boruta feature selection and ensemble learning
Accuracy | Recall | F1 Index | Kappa | Precision | MCC | |
|---|---|---|---|---|---|---|
XGBoost [5] | 0.877 | 0.849 | 0.864 | 0.732 | 0.977 | 0.754 |
REL [27] | 0.974 | 0.975 | 0.973 | 0.946 | 0.952 | 0.946 |
GD [6] | 0.896 | 0.886 | 0.889 | 0.778 | 0.875 | 0.778 |
ARS [7] | 0.967 | 0.941 | 0.909 | 0.972 | 1.000 | 0.913 |
Bagging | 0.922 | 0.904 | 0.916 | 0.833 | 0.980 | 0.841 |
Boosting | 0.982 | 0.990 | 0.984 | 0.969 | 0.958 | 0.969 |
My model | 0.980 | 0.982 | 0.971 | 0.952 | 0.962 | 0.950 |