In this project my objective is to predict whether the patient has heart disease or not based on various features like cp,trestbps,chol,fbs,restecg,thalach,exang,oldpeak,slope,ca,thal .I performed all the steps from Data gathering to testing new data on the model. I compared various machine learning algorithms on the basis of accuracy_score metric and find the best one . At the end , Random forest classifier had the best results.
Here are screenshots for the results and a grpah to compare the results of different models ; logistic regression , svm , KNN , decision trees , random forest classifier and gradient boosting
installations -Clone this repository and unzip it. -Begin a new virtual environment with Python 3 and activate it. -Install the required packages using pip install -r requirements.txt -run the file