Exoplanet Classifier Web Application

This project was developed by Team XLR8 for the NASA Space Apps Challenge 2025.

Team Members

• devnull37(Faris Allafi)
• Farah Muhssin
• Mentor: Mr. Mohamed Salah

School: Yas American Academy (Aldar Schools Abu Dhabi)

This project is a web application designed to classify exoplanets using machine learning models. It's built with React, Vite, and TypeScript, and leverages Shadcn UI for a modern and responsive user interface.

Features

• Exoplanet Classification: Utilizes pre-trained machine learning models (LightGBM, Random Forest, XGBoost in ONNX format) to classify exoplanets.
• Interactive User Interface: Built with React and Shadcn UI for a seamless user experience.
• Responsive Design: Adapts to various screen sizes for optimal viewing on desktop and mobile devices.

Technologies Used

• Frontend:
  • React
  • Vite
  • TypeScript
  • Shadcn UI
  • Tailwind CSS
  • ONNX Runtime Web (for running ML models in the browser)
• Machine Learning:
  • LightGBM (via ONNX)
  • Random Forest (via ONNX)
  • XGBoost (via ONNX)

Project Structure

.
├── public/
│   ├── lgb_model.onnx        # LightGBM ONNX model
│   ├── rf_model.onnx         # Random Forest ONNX model
│   ├── xgboost_model.onnx    # XGBoost ONNX model
│   └── STAGE2/
│       ├── confirmed.csv     # Confirmed exoplanet data
│       └── false-positive.csv # False positive exoplanet data
├── src/
│   ├── components/           # React components
│   │   ├── AboutModel.tsx
│   │   ├── ClassifierForm.tsx
│   │   ├── DataVisualization.tsx
│   │   ├── Footer.tsx
│   │   ├── Hero.tsx
│   │   ├── ResultsDisplay.tsx
│   │   └── ui/               # Shadcn UI components
│   ├── hooks/                # Custom React hooks
│   ├── lib/                  # Utility functions
│   ├── pages/                # Page components
│   └── utils/
│       └── classifier.ts     # Logic for exoplanet classification
├── package.json              # Project dependencies and scripts
├── tsconfig.json             # TypeScript configuration
├── vite.config.ts            # Vite configuration
└── ...other config files

Training Code

The machine learning models used in this project were trained using the code available on Kaggle: https://www.kaggle.com/code/farisallafi/space-apps-challenge-team-xlr8

License

This project is licensed under the Apache License 2.0.

##Website

https://space-apps-challenge-xlr8.netlify.app/