This project was completed for the data preparation techniques course. In this project different data preparation techniques were applied such as -

• Dataset Presentation
• Data Cleaning
• Data scaling pre-assessment
• Handling missing data and outliers
• Supervised Learning problem design and experimentation

The dataset we are working with is from an ongoing cardiovascular study on residents of the town of Framingham, Massachusetts. It is publicly available in Kaggle. The goal of this dataset is to predict whether the person has 10 year risk of heart diseases. This dataset is publicly available in Kaggle (https://www.kaggle.com/datasets/dileep070/heart-disease-prediction-using-logistic-regression)

There are 16 column in this dataset. They are:

• male: Whether the patient is male or female (Nominal: 1 means male and 0 means female). Men are more prone to heart diseases than women. So, the risk of gender varies depending on the gender.
• age: Age of the patient. It is a well known fact that the risk of heart diseases increases with age.
• Education: This column represents the level of education from 1 to 4.
• currentSmoker: Whether or not the patient is a current smoker (Nominal). Smoking plays an important role whether a person will be affected with heart disease or not.
• cigsPerDay: the number of cigarettes that the person smoked on average in one day
• BPMeds: whether or not the patient was on blood pressure medication (Nominal)
• prevalentStroke: whether or not the patient had previously had a stroke (Nominal)
• prevalentHyp: whether or not the patient was hypertensive (Nominal)
• diabetes: whether or not the patient had diabetes (Nominal). People with high diabetes are more tend to have heart attack as it effects the regular blood flow.
• totChol: total cholesterol level (Continuous). A normal human contains 200mg/dL level of cholestrol. If the level increases it may lead to a heart disease.
• SysBP: systolic blood pressure (Continuous). Blood pressure normally remains 120/80 or lower. Higher blood pressure will signify more stress on the heart.
• diaBP: diastolic blood pressure (Continuous)
• BMI: Body Mass Index (Continuous)
• heartRate: heart rate (Continuous) 60 to 100 beats per minute signifies regular. Generally a lower level signifies a better heart condition.
• Glucose: if the glucose level (Continuous) is too high it can damage one's heart which may result in a coronary heart disease.
• TenYearCHD: 10 year risk of coronary heart disease CHD (binary: “1”, means “Yes”, “0” means “No”)

• Mehadi Hassan
• Hridita Tabassum