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A machine learning project that compares five classification algorithms for predicting the presence of heart disease from clinical patient data.

  • Updated Aug 15, 2026
  • Jupyter Notebook
heartDiseasePrediction

This repo is the Machine Learning practice on NHANES dataset of Heart Disease prediction. The ML algorithms like LR, DT, RF, SVM, KNN, NB, MLP, AdaBoost, XGBoost, CatBoost, LightGBM, ExtraTree, etc. The results are good. I also explore the class-balancing (SMOTE) because the original dataset contains only 5% of patient and 95% of healthy record.

  • Updated Apr 13, 2024
  • Jupyter Notebook

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