Table 5 Model Results using 37 variables with an MI score grater than 0
From: Machine learning based model for the early detection of Gestational Diabetes Mellitus
Model | Sn (Recall) | Sp | Acc | F1-score | Precision |
|---|---|---|---|---|---|
RandomForestClassifier | 78.40% | 77.80% | 77.89% | 78.64% | 79.82% |
GradientBoostingClassifier | 81.10% | 76.99% | 78.89% | 80.01% | 80.05% |
AdaBoostClassifier | 81.77% | 75.14% | 78.33% | 79.77% | 78.81% |
DecisionTreeClassifier | 75.34% | 78.36% | 76.56% | 76.99% | 79.61% |
LogisticRegression | 77.05% | 73.39% | 75.83% | 75.91% | 75.60% |
SVC | 78.10% | 74.43% | 76.17% | 77.42% | 78.12% |
GaussianNB | 81.64% | 69.66% | 76.44% | 78.03% | 75.92% |
KNeighborsClassifier | 79.92% | 58.55% | 71.00% | 71.63% | 65.43% |
CatBoostClassifier | 86.14% | 73.99% | 80.50% | 81.21% | 77.69% |
XGBClassifier | 79.41% | 77.76% | 78.39% | 79.21% | 80.04% |
LGBMClassifier | 70.63% | 66.51% | 69.94% | 69.17% | 68.96% |
Stacking | 90.19% | 83.50% | 87.22% | 87.99% | 86.16% |