Developed a heart disease detection model using logistic regression on a dataset containing 303 entries. The dataset comprises various clinical attributes such as age, sex, cholesterol levels, and more. After splitting the data into training and test sets, the model achieved an accuracy of 85.1% on the training data and 81.97% on the test data. The model can effectively predict whether a person has a healthy heart or is at risk of heart disease based on their medical characteristics.
Python (VS Code, Microsoft Jupyter Extension)
Pandas (pip install pandas)
NumPy (pip install numpy)
scikit-learn (pip install -U scikit-learn)
Jupyter Notebook (pip install notebook) (jupyter notebook)