Table 1 Description of variables UCI heart dataset
From: Machine learning-based identification of patients with a cardiovascular defect
Variable | Description |
|---|---|
Age | Age in years (29 to 77) |
Sex | Gender instance (0 = Female, 1 = Male) |
ChestPainType | Chest pain type (1: typical angina, 2: atypical angina, 3: non- anginal pain, 4: asymptomatic) |
RestBloodPressure | Resting blood pressure in mm Hg[94, 200] |
ChestPainType | Serum cholesterol in mg/dl[126, 564] |
FastingBloodSugar | Fasting blood sugar> 120 mg/dl (0 = False, 1= True) |
ResElectrocardiograp | Resting ECG results (0: normal, 1: ST-T wave abnormality, 2: LV hypertrophy) |
MaxHeartRate | Maximum heart rate achieved[71,202] |
ExerciseInduced | Exercise-induced angina (0: No, 1: Yes) |
Oldpeak | ST depression induced by exercise relative to rest [0.0, 62.0] |
Slope | Slope of the peak exercise ST segment (1: up-sloping, 2: flat, 3: downsloping) |
MajorVessels | Number of major vessels colored by fluoroscopy (values 0 - 3) |
Thal | Defect types: value 3: normal, 6: fixed defect, 7: irreversible defect |
HeartDisease | Target : value 0: absence of disease, 1 or 2 or 3 or 4 or 5: presence of cardiovascular disease |