Classification on Kaggle Cardiovascular Disease Dataset I
82.3AccuracyCNN–LSTM + KNN + XGB
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| CNN–LSTM + KNN + XGBGroup=Proposed model2026.01 | 82.3 | 84 | 83.5 | 83.6 | |
| CNN–LSTMGroup=Combinational DL2026.01 | 80 | 81.8 | 81.4 | 81.3 | |
| RF + DT + NB + LRGroup=Combinational ML2026.01 | 79.5 | 79.7 | 79.4 | 79.5 | |
| RF + DT + KNN + NB + SVM + LGBM + XGB + MLP + LRGroup=Combinational ML2026.01 | 79 | 79.2 | 79 | 79.1 | |
| XGBGroup=Ensemble-based2026.01 | 78.9 | 79.3 | 79.2 | 79.4 | |
| CNNGroup=Deep learning2026.01 | 78.8 | 80 | 79.8 | 80.1 | |
| KNNGroup=Machine learning2026.01 | 78.3 | 79.1 | 79.2 | 79.4 | |
| LGBMGroup=Ensemble-based2026.01 | 78.1 | 78.9 | 78.6 | 78.7 | |
| LSTMGroup=Deep learning2026.01 | 78 | 80.1 | 79.9 | 80 | |
| AdaBoostGroup=Ensemble-based2026.01 | 77.9 | 78.8 | 78.7 | 78.9 | |
| RFGroup=Machine learning2026.01 | 77.8 | 78.1 | 78.2 | 78.3 | |
| SVMGroup=Machine learning2026.01 | 77.5 | 77.9 | 77.7 | 77.8 | |
| DTGroup=Machine learning2026.01 | 77.3 | 78.2 | 78.3 | 78.4 | |
| LRGroup=Machine learning2026.01 | 76.8 | 77.8 | 77.4 | 77.2 | |
| MLPGroup=Machine learning2026.01 | 76.8 | 77.9 | 77.8 | 77.6 | |
| NBGroup=Machine learning2026.01 | 75.5 | 75.9 | 76 | 75.8 |