🔍 Explore the likelihood of heart disease with machine learning!
This Python project utilizes three powerful algorithms—Linear Regression, Logistic Regression, and Support Vector Machine—to predict the probability of heart disease in individuals. The user-friendly interface, built using Tkinter, provides an intuitive experience for data visualization and model evaluation. Analyze and understand the factors influencing heart health with ease!
🚀 Key Features:
- Predict heart disease using three machine learning models.
- Interactive Tkinter GUI for easy visualization.
- Utilizes popular Python libraries like scikit-learn, matplotlib, and seaborn.
- Evaluate model performance and make informed decisions.
👩💻 How to Use:
- Clone the repository.
- Install dependencies:
pip install -r requirements.txt. - Run
main.pyto train and evaluate models. - Explore the project folder for the executable file.
🤝 Contributing:
- Fork the repository, create a branch, and open a pull request.
- Share your insights and contribute to enhancing heart disease prediction.
🌐 Explore the Future of Heart Health!