Table 4 Machine learning algorithms results UCI heart disease
From: Machine learning-based identification of patients with a cardiovascular defect
Metrics | XGBoost | AdaBoost | Gradient Boost | Extra Trees | LightGbm | SGDC | Nu svc | Stacking algorithm |
|---|---|---|---|---|---|---|---|---|
Accuracy | 92.37 | 91.66 | 90.27 | 94.44 | 94.44 | 92.36 | 93.75 | 95.83 |
Specificity | 92.24 | 93.24 | 90.54 | 94.59 | 94.59 | 91.89 | 93.24 | 94.59 |
Precision | 92 | 90.98 | 90.54 | 94.59 | 94.59 | 93.15 | 94.52 | 97 |
Recall | 93.24 | 93.24 | 90.54 | 94.59 | 94.59 | 91.89 | 93.24 | 95 |
F score | 92.61 | 92 | 90.54 | 94.59 | 94.59 | 92.51 | 93.87 | 96 |