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 ---------- 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 ] : https://mfkwma.dm.files.1drv.com/y4myHV-mOBu_GdGEwywKovQZGUVgXiSsdUwfe5VVnRRn8ZKj_PcObqnPzNDucG-uhXZ3A0A0UR7cftFwa3EXbM67QK4ESY4YHrF07m9dt5Wd4Z1cLx_3cZ8OXCOxOyH83fuC0ew_xIAUsqy5wUay1FWOirTXYaeWPZ8aHOeuXVzjMkjeft7YNIug_TSbzI5_2OOpgAdWfusqsyiK0jfUXJrcQ?width=374&height=285&cropmode=none