Research Article
Cardiovascular Disease Detection using Ensemble Learning
Table 5
Comparison of proposed and baseline approaches classifiers performance to detect cardiovascular disease.
| Method | Models | Accuracy (%) |
| Baseline approach [30] | LR | 85.54 | RF | 86.03 | DT | 85.93 | NB | 83.38 | KNN | 84.56 | SVM | 86.63 | MLP | 87.23 |
| Baseline approach [31] | GA-ANN | 73.43 | ANN | 68.35 | Logistic regression | 72.35 | Decision tree | 61.72 | Random forest | 68.94 | Support vector machine | 72.16 | K-nearest neighbor | 68.34 |
| Proposed approach | ML ensemble | 88.70 |
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