Research Article
Heart Risk Failure Prediction Using a Novel Feature Selection Method for Feature Refinement and Neural Network for Classification
Table 2
Results of different subsets of features for the heart disease dataset.
| | | | | | Sens. (%) | Spec. (%) | |
| 12 | 4 | 3 | 83.09 | 90.00 | 85.36 | 93.87 | 0.799 | 12 | 11 | 8 | 87.92 | 90.00 | 85.36 | 93.87 | 0.799 | 11 | (5, 6) | 4 | 82.60 | 91.11 | 85.36 | 95.91 | 0.822 | 11 | (11, 12) | 4 | 81.15 | 90.00 | 87.80 | 91.83 | 0.798 | 10 | (4 to 6) | 7 | 85.99 | 90.00 | 82.92 | 95.91 | 0.801 | 7 | (3 to 8) | 49 | 95.16 | 91.11 | 87.80 | 93.87 | 0.820 | 6 | (6 to 12) | 6 | 81.15 | 91.11 | 95.12 | 87.75 | 0.825 | 13 | ā | 1 | 85.02 | 90.00 | 87.80 | 91.83 | 0.798 |
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