Research Article
Machine Learning-Based Model to Predict Heart Disease in Early Stage Employing Different Feature Selection Techniques
Table 3
Feature score using FST1.
| Order | Feature | Feature name | Code | Scores |
| 1 | 9 | exang | EIA | 70.95 | 2 | 3 | cp | CPT | 69.77 | 3 | 10 | Oldpeak | OP | 68.55 | 4 | 8 | Thalach | MHR | 65.12 | 5 | 12 | ca | NMV | 64.05 | 6 | 11 | Slope | PES | 40.90 | 7 | 13 | thal | TS | 31.80 | 8 | 2 | Sex | SEX | 25.79 | 9 | 1 | Age | AGE | 16.12 | 10 | 4 | trestbps | RBP | 6.46 | 11 | 7 | restecg | REC | 5.78 | 12 | 5 | chol | CM | 2.20 | 13 | 6 | fbs | FBS | 0.24 |
|
|