GitHub / mathlimam / HeartDiseaseRiskLR

This project contains a Python implementation of logistic regression to predict the risk of developing heart disease in the next 10 years, based on the Framingham dataset from Kaggle. The implementation achieved an accuracy of 87.27% on the test set. The code is available on GitHub under the repository name "HeartDiseaseRiskLR".

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mathlimam%2FHeartDiseaseRiskLR

Topics: ai, cardiovascular-disease, cardiovascular-diseases, data-analysis, data-science, data-visualization, framingham, framingham-heart-study, jupyter-notebook, kaggle, logistic-regression, machine-learning, python

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