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| title: Fricitonangle prediction of solid waste | |
| emoji: π | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: streamlit | |
| sdk_version: "1.29.0" | |
| app_file: app.py | |
| pinned: false | |
| # Friction Angle Predictor | |
| This Streamlit app predicts the friction angle of waste materials based on their composition and characteristics. The app uses a deep learning model trained on waste composition data to make predictions and provides SHAP value explanations for model interpretability. | |
| ## Features | |
| - Interactive input for waste composition parameters | |
| - Real-time prediction of friction angle | |
| - SHAP waterfall plot for model interpretation | |
| - User-friendly interface | |
| ## Usage | |
| 1. Enter the waste composition values in the input fields | |
| 2. Click "Predict Friction Angle" to get the prediction | |
| 3. View the results and SHAP waterfall plot for explanation | |
| ## Model | |
| The model is a neural network trained on waste composition data. It uses the following features: | |
| - Waste composition percentages | |
| - Physical properties | |
| - Material characteristics | |
| ## Requirements | |
| See `requirements.txt` for all dependencies. |