{"id":20988323,"url":"https://github.com/venky-1710/stress-level-predection","last_synced_at":"2026-04-05T22:36:34.430Z","repository":{"id":246417444,"uuid":"817995892","full_name":"venky-1710/stress-level-predection","owner":"venky-1710","description":"Stress Level Prediction is a web app using machine learning to estimate user stress levels. It takes inputs like anxiety, sleep quality, and academic performance, then predicts stress using a Decision Tree Classifier. 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It uses a machine learning model to make predictions and provides a user-friendly interface for input and result display.\n\n## Features\n\n- User input form for various stress-related factors\n- Machine learning model (Decision Tree Classifier) for stress level prediction\n- Responsive web design with custom styling\n- Input validation to ensure data integrity\n- Error handling for invalid inputs\n\n## Technologies Used\n\n- Python\n- Flask\n- scikit-learn\n- pandas\n- numpy\n- HTML/CSS\n- JavaScript\n\n## Project Structure\n\n- `app.py`: Main Flask application file containing the server-side logic and machine learning model\n- `templates/`: Directory containing HTML templates\n  - `login.html`: Input form for user data\n  - `result.html`: Displays the predicted stress level\n  - `error.html`: Error page for invalid inputs\n- `static/`: Directory for static files\n  - `styles.css`: Custom CSS styles for the application\n- `StressLevelDataset.csv`: Dataset used for training the model (not included in the repository)\n\n## Setup and Running the Application\n\n1. Clone the repository:\n   ```sh\n   https://github.com/venky-1710/stress-level-predection.git\n   ```\n2. Install the required dependencies:\n   ```sh\n   pip install flask pandas numpy scikit-learn\n   ```\n3. Ensure you have the `StressLevelDataset.csv` file in the project root directory.\n\n4. Run the Flask application:\n   ```sh\n   python app.py\n   ```\n5. Open a web browser and navigate to `http://localhost:5000` to use the application.\n\n## How to Use\n\n1. Fill in the form with your stress-related factors. Each field has a specified range of values.\n2. Click the \"Submit\" button to get your predicted stress level.\n3. The result page will display your predicted stress level based on the input factors.\n\n## Future Improvements\n\n- Implement user authentication and data storage\n- Add more detailed explanations for each input factor\n- Incorporate additional machine learning models for comparison\n- Develop a feature to track stress levels over time\n\n## Contributing\n\nContributions to improve the project are welcome. Please feel free to fork the repository and submit pull requests.\n\n## License\n\nThis project is open source and available under the [MIT License](LICENSE).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvenky-1710%2Fstress-level-predection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvenky-1710%2Fstress-level-predection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvenky-1710%2Fstress-level-predection/lists"}