Table 15 Experimental results on Hungarian dataset with 10 features
From: A hybrid cost-sensitive ensemble for heart disease prediction
Mean ± SD | RF | LR | SVM | ELM | KNN | Proposed ensemble |
|---|---|---|---|---|---|---|
E (%) | 72.73 ± 6.29 | 73.85 ± 7.06 | 72.72 ± 6.78 | 69.94 ± 8.26 | 60.09 ± 10.59 | 79.87 ± 7.32 |
Precision (%) | 72.72 ± 8.17 | 73.38 ± 8.14 | 71.78 ± 8.31 | 69.18 ± 10.08 | 53.77 ± 13.27 | 80.89 ± 7.89 |
Recall (%) | 49.00 ± 16.03 | 52.92 ± 14.85 | 44.30 ± 17.06 | 44.39 ± 20.61 | 37.77 ± 18.40 | 66.38 ± 14.13 |
G-mean | 62.75 ± 11.18 | 65.96 ± 10.60 | 60.44 ± 12.46 | 58.39 ± 14.78 | 45.48 ± 14.87 | 75.75 ± 9.22 |
MC (%) | 109.40  ± 31.01 | 103.24 ± 32.31 | 118.24 ± 33.24 | 123.00 ± 42.83 | 148.60 ± 48.07 | 74.08 ± 32.11 |
Specificity (%) | 82.62 ± 5.75 | 83.40 ± 5.22 | 85.57 ± 5.62 | 80.65 ± 8.26 | 59.28 ± 13.55 | 87.31 ± 3.60 |
AUC (%) | 67.38 ± 10.99 | 68.59 ± 10.98 | 65.43 ± 10.99 | 61.67 ± 13.98 | 50.81 ± 15.55 | 77.64 ± 8.31 |