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title: Energy ML Prediction System | |
emoji: ⚡ | |
colorFrom: blue | |
colorTo: green | |
sdk: gradio | |
sdk_version: 5.42.0 | |
app_file: app.py | |
pinned: false | |
license: mit | |
# Energy ML Prediction System | |
AI-powered energy consumption prediction and threshold exceedance detection. | |
## Models | |
- **Threshold Detection**: Random Forest classifier (AUC = 0.94) | |
- **Energy Prediction**: Random Forest & XGBoost regressors | |
- **Performance**: R² up to 0.72, MAE as low as 0.53 MWh | |
## Features | |
- Real-time predictions via simple JSON interface | |
- Multiple model comparison (RF vs XGBoost) | |
- Threshold exceedance probability (8.3 and 9.0 MWh) | |
- Secure access with authentication | |
## Usage | |
1. Select your model | |
2. Input JSON configuration | |
3. Get instant predictions | |
## Authentication | |
Login required for access. | |
- Username: admin | |
- Password: energy123 | |
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*Built with Gradio • Powered by scikit-learn & XGBoost* |