GitHub - gcapellib/Projet_Jedha_Machine_Learning: Machine Learning project predicting heart disease risk from clinical data (UCI Heart Failure dataset, 918 patients). Compares Logistic Regression, Decision Tree, and Random Forest — best model achieves 88% accuracy and 90.2% recall with a 0.4 decision threshold to minimize missed diagnoses. · GitHub

Name		Name	Last commit message	Last commit date
DataSet_heart.xlsx		DataSet_heart.xlsx
Projet_Final.ipynb		Projet_Final.ipynb
README.md		README.md
cardiac_predictor2.html		cardiac_predictor2.html
main.py		main.py
model.pkl		model.pkl
requirements.txt		requirements.txt

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Machine Learning project predicting heart disease risk from clinical data (UCI Heart Failure dataset, 918 patients). Compares Logistic Regression, Decision Tree, and Random Forest — best model achieves 88% accuracy and 90.2% recall with a 0.4 decision threshold to minimize missed diagnoses.

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