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Risk Prediction of Heart Disease
Classifications Model to predict risk of Heart Disease
Business Problem
Cardiovascular disease can happen to anyone, however there are some health risk factors that play a major role in getting a heart disease. Problem with heart disease, many people don’t realize it they have it until it is very late. By analyzing the contributing risk factors and early prevention can save millions of lives. The motivation of this project is to analyze and find the major risk factors of heart disease and use this information to predict the risk of heart disease for an individual so prevention methods can be appli.ed
Techniques
I used ggplot2 in R to perform exploratory data analysis on every variables, to find out which factors are most likely going to cause the heart disease.
I built two models, Logistic Regression and Random Forest. To do this analysis. I split the dataset into train set and test set. About 70% of the data is in train set. And this considering that the distribution of the target must be the same in both sets. Test set is used for model evaluations and suppose to mimic real world or unknown new data. I will also be performing 10 fold cross validation.
Future Applications
This model can be implemented by Hospitals, Clinic and Testing centres to identify risk factors in patients. Furthermore, the model can be used to cut costs of hospitalization for the patient, by giving Doctors opportunity to intervene aggressively to prevent complications.