v1.0.0

Releases

v1.0.0 - Initial Release

Date: 25-12-2024
Description:
The first stable version of the House Price Prediction application. This release includes the following features:

• Frontend:

  • React-based user interface.
  • Responsive design for desktop and mobile.
  • Input fields for house attributes: bedrooms, bathrooms, living area, condition, and nearby schools.
  • Real-time predictions displayed after submitting inputs.

• Backend:

  • Flask-based API to connect frontend with the trained machine learning model.
  • Integration with the Random Forest Regressor model and scaler for price prediction.
  • Endpoint to handle prediction requests efficiently.

• Machine Learning:

  • Trained Random Forest Regressor for accurate house price predictions.
  • StandardScaler used for feature scaling.
  • Model trained and tested on a cleaned dataset for robustness.

Setup Instructions:

1. Clone the repository.
2. Set up the backend:
   • Navigate to backend and install dependencies (pip install -r requirements.txt).
   • Run app.py to start the Flask API.
3. Set up the frontend:
   • Navigate to frontend and install dependencies (npm install).
   • Run npm run dev to launch the React app.
4. Access the application in your browser at http://localhost:5173.

Known Issues:

• Ensure the correct path to the model files (house_price_model.pkl and scaler.pkl).
• Model accuracy may vary depending on the provided input data distribution.