Student Dropout Prediction System

A Django-based web application for predicting student dropout likelihood based on academic performance metrics.

Prerequisites

• Python 3.11 or higher
• pip (Python package installer)

Setup Instructions

1. Clone the repository or download the files:

git clone <repository-url>
cd sponnasi

2. Create a virtual environment:

# Windows
python -m venv venv

# Linux/Mac
python3 -m venv venv

3. Activate the virtual environment:

# Windows
venv\Scripts\activate

# Linux/Mac
source venv/bin/activate

4. Install required packages:

pip install -r requirements.txt

5. Navigate to the Django project directory:

cd student_dropout

6. Run database migrations:

python manage.py migrate

7. Start the development server:

python manage.py runserver

8. Open your web browser and go to:

http://127.0.0.1:8000/

Usage

1. Enter the following student information:

   • JEE Main Score
   • Attendance Percentage
   • CGPA

2. Click "Predict" to see the dropout prediction result

Project Structure

student_dropout/
├── predictor/              # Main application
│   ├── templates/         # HTML templates
│   ├── django_predictor.py # Prediction logic
│   ├── urls.py           # URL configurations
│   └── views.py          # View functions
├── student_dropout/       # Project settings
└── manage.py             # Django management script

Troubleshooting

1. If you get a "No module named 'django'" error:

   • Make sure your virtual environment is activated
   • Run pip install django

2. If the server won't start:

   • Check if port 8000 is already in use
   • Try python manage.py runserver 8080 to use a different port

3. If you see database errors:

   • Delete db.sqlite3 file (if it exists)
   • Run migrations again: python manage.py migrate

Development

To modify the prediction thresholds, edit the thresholds dictionary in: predictor/django_predictor.py

License

This project is open-source and available under the MIT License.