chaithanya2035/FWI_Prediction_ML_Regression_model

Ridge regression model that predicts the Fire Weather Index (FWI) from weather observations collected in two Algerian regions (Bejaia and Sidi-Bel Abbes). # FWI Prediction — Algerian Forest Fires Ridge regression model that predicts the **Fire Weather Index (FWI)** from weather observations collected in two Algerian regions (Bejaia and Sidi-Bel Abbes). ## Project structure ``` . ├── application.py # Flask app with /home and /predict endpoints ├── models/ │ ├── ridge.pkl # Trained Ridge model │ └── scaler.pkl # StandardScaler used during training ├── notebooks/ │ └── ML_production_Project1.ipynb # EDA & model training └── templates/ └── home.html # Web UI ``` ## Setup ```bash python3 -m venv .venv source .venv/bin/activate pip install -r requirements.txt ``` ## Run ```bash python application.py ``` Visit `127.0.0.1` for the web UI, or send a JSON POST to the same endpoint: ```bash curl -X POST 127.0.0.1 \ -H "Content-Type: application/json" \ -d '{"Temperature":29,"RH":57,"Ws":18,"Rain":0.0, "FFMC":65.7,"DMC":3.4,"ISI":1.3,"Classes":0,"region":0}' ``` ### Input features | Feature | Description | |---------|-------------| | Temperature | Temperature in °C | | RH | Relative humidity (%) | | Ws | Wind speed (km/h) | | Rain | Rainfall (mm) | | FFMC | Fine Fuel Moisture Code | | DMC | Duff Moisture Code | | ISI | Initial Spread Index | | Classes | 0 = Not fire, 1 = Fire | | Region | 0 = Bejaia, 1 = Sidi-Bel Abbes | ## API | Endpoint | Method | Description | |----------|--------|-------------| | `/predict` | GET | Web UI | | `/predict` | POST | Returns `{"fwi": }` |