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https://github.com/james-leste/heart_disease_prediction
Early detection and prediction of heart diseases are vital for timely intervention and prevention. In this study, we compare the performance of five machine learning algorithms, namely, K-Nearest Neighbors (KNN), Logistic Regression, Decision Tree, and Random Forest in predicting the presence or absence of heart disease.
https://github.com/james-leste/heart_disease_prediction
data-science jupyter-notebook machine-learning python
Last synced: 5 days ago
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Early detection and prediction of heart diseases are vital for timely intervention and prevention. In this study, we compare the performance of five machine learning algorithms, namely, K-Nearest Neighbors (KNN), Logistic Regression, Decision Tree, and Random Forest in predicting the presence or absence of heart disease.
- Host: GitHub
- URL: https://github.com/james-leste/heart_disease_prediction
- Owner: James-Leste
- Created: 2024-01-28T19:20:13.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-03-01T17:07:50.000Z (8 months ago)
- Last Synced: 2024-10-11T08:09:28.771Z (27 days ago)
- Topics: data-science, jupyter-notebook, machine-learning, python
- Language: Jupyter Notebook
- Homepage:
- Size: 3.78 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Machine Learning Project: Heart Disease Prediction
Early detection and prediction of heart diseases are vital for timely intervention and prevention. In this study, we compare the performance of five machine learning algorithms, namely, K-Nearest Neighbors (KNN), Logistic Regression, Decision Tree, and Random Forest in predicting the presence or absence of heart disease.