https://github.com/mahtabranjbar/heart-risk-classifier
https://github.com/mahtabranjbar/heart-risk-classifier
decision-trees gradient-boosting knn random-forest svm
Last synced: 2 months ago
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- Host: GitHub
- URL: https://github.com/mahtabranjbar/heart-risk-classifier
- Owner: MahtabRanjbar
- License: apache-2.0
- Created: 2023-09-14T23:17:34.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-09-14T23:24:45.000Z (over 1 year ago)
- Last Synced: 2025-01-24T11:44:42.447Z (4 months ago)
- Topics: decision-trees, gradient-boosting, knn, random-forest, svm
- Language: Python
- Homepage:
- Size: 134 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Heart Attack Risk Classifier
This project is a heart attack risk classification system that uses machine learning algorithms to predict whether an individual is at low or high risk for a heart attack. It provides an interface where users can input their health information, and the system will classify their risk based on the trained models.
## Table of Contents
- [Dataset](#dataset)
- [Model](#model)
- [Installation](#installation)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)
# Dataset
The heart attack dataset used for training and prediction is loaded from the `heart.csv` file. This dataset contains various features related to heart health, such as age, sex, cholesterol levels, blood pressure, and more. The target variable, "output," indicates the risk level of a heart attack, where 1 represents high risk and 0 represents low risk.
# Model
The heart attack risk classification system utilizes several machine learning algorithms for prediction. The available models include:
- Logistic Regression
- K-Nearest Neighbors (KNN)
- Support Vector Machine (SVM)
- Decision Trees
- Random Forest
- Gradient Boosting
- XGBoost
Each model has its own set of parameters that can be adjusted for fine-tuning the classification performance.
# Installation
1. Clone the repository:
```bash
git clone https://github.com/MahtabRanjbar/heart-risk-classifier.git
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
3. Run the application:
```bash
streamlit run src/app.py
```
4. Access the application in your web browser at `http://localhost:8501`.
## Contributing
Contributions are always welcome! If you have any ideas or suggestions, please feel free to open an issue or a pull request.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more information
## Contact
If you have any questions or comments about this project, please feel free to contact me at [email protected]