chayandatta/Heart_disease_prediction
Heart Disease prediction using 5 algorithms
Compares five classification algorithms (Logistic Regression, Random Forest, Naive Bayes, KNN, Decision Tree) on the UCI Heart Disease dataset, with hyperparameter tuning to optimize accuracy across models. Delivered as a Jupyter notebook enabling interactive exploration of model performance and feature importance visualization. Targets ML beginners seeking hands-on experience with supervised learning fundamentals and algorithm comparison workflows.
127 stars. No commits in the last 6 months.
Stars
127
Forks
44
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Nov 04, 2024
Commits (30d)
0
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