Predicting the chances of occurrence of Cardio Vascular Disease (CVD) in people using classification techniques within fifty years of age

The changing lifestyle, food habits and other bad habits like smoking, drinking has lead people to heart attack at young age. This paper aims in predicting the likelihood of cardiac disease in people based on the attributes such as the age, sex, cp, trestbps, chol, fbs, restecg, thalac, exang, oldpeak, slope, ca, thal. The data of existing patients within fifty years of age has to be collected and trained. Classification algorithms like Naive Bayes algorithms is applied to develop a model. This model will form a basis for predicting the chances of occurrence of CVD. If a person's data are given the classifier will predict if he is liable to CVD or not. The output is a binary classification which will give 1 or 0; 1 being the chances to occur and 0 being the chances not to occur.