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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. |