Coronary Heart Disease Prediction
This example demonstrates prediction of Coronary Heart Disease (CHD) heart disease using binary classification.
The dataset collected from Boston University. The data set has categorized into 4 different risk factors as
demographic, behavioral, medical and physical.
Dataset description
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The dataset collected from Boston University. The dataset has 15 attributes and class label. The patients were observed for 10 years on various risk factors as categorized into 4 different risk factors as demographic, behavioral, medical and physical.
**Demographic Risks:**
- gender
- age
- education (1: high school, 2: diploma, 3: college, 4: higher than degree)
**Behavioral Risks:**
- CurrentSmoker - Current smoker or not
- CigsPerDay - Average number of cigarettes smoked per day
**Medical experiments:**
- BPMeds - Patient is under blood pressure medication
- PrevalentStroke - Previously had a stroke or not
- PrevalentHyp - Prevalent Hypertension or not
- Diabetes - Patient has diabetes or not
- TotChol - Total Cholesterol
- Glucose - Glucose level
**Physical examination:**
- DiaBP - Diastolic blood pressure
- BMI - Body mass index
- Heart - Rate Heart Rate
- SysBP - Symbolic blood pressure
**Prediction Label:**
TenYearCHD 10 year risk of coronary heart disease CHD (Class)
**Distribution of continuous attributes**
![Gaussian distributions ][1]
[1]: https://mfkwma.dm.files.1drv.com/y4myHV-mOBu_GdGEwywKovQZGUVgXiSsdUwfe5VVnRRn8ZKj_PcObqnPzNDucG-uhXZ3A0A0UR7cftFwa3EXbM67QK4ESY4YHrF07m9dt5Wd4Z1cLx_3cZ8OXCOxOyH83fuC0ew_xIAUsqy5wUay1FWOirTXYaeWPZ8aHOeuXVzjMkjeft7YNIug_TSbzI5_2OOpgAdWfusqsyiK0jfUXJrcQ?width=374&height=285&cropmode=none