Heart Disease Predictor
This project is built with the help of Streamlit . The algorithm used is Random Forest Classifier with the accuracy of 87%.The preprocessing techniques like scaling ,encoding,SMOTE is also performed .
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Heart Disease Predictor
This project is built with the help of Streamlit . The algorithm used is Random Forest Classifier with the accuracy of 87%.The preprocessing techniques like scaling ,encoding,SMOTE is also performed .
The problem Heart Disease Predictor solves
It helps in predicting the level of Heart Disease based on the description provided.
Challenges I ran into
The preprocessing and model building part was easy but , I faced difficulties in building the pipeline and deploying it to Streamlit.I tried various other models like XGBoost, Decision Tree Classifier, but Random Forest Classifier gave me the best result.Finding the relationship among the independent variables was also quite challenging for me.
Technologies used
Discussion