Muskansingh2002/Algerian-Forest-Fire-Risk-Predictor

A Flask-based machine learning web application that predicts forest fire risk in Algerian regions using Ridge Regression. Built using the Algerian Forest Fire Dataset, the model takes in environmental parameters like temperature, humidity, wind speed, rainfall, and fire weather indexes to estimate fire likelihood. # 🔥 Algerian Forest Fire Risk Prediction Web App This is a Flask-based machine learning web application that predicts the risk of **forest fires in Algeria** using environmental data. It uses a trained **Ridge Regression** model and the **Algerian Forest Fires Dataset** collected between June and September 2012. --- ## 🌍 Dataset Description The dataset includes **244 observations** from two Algerian regions: - **Bejaia (Northeast Algeria)** – 122 samples - **Sidi Bel-Abbes (Northwest Algeria)** – 122 samples Each instance contains meteorological data and fire weather indexes, observed between **June to September 2012**. The data is labeled as either **Fire** or **Not Fire**. ### 📊 Attributes: | Feature | Description | |--------|-------------| | 1. Date | Observation Date (DD/MM/YYYY) | | 2. Temp | Temperature at noon (°C) — range: 22 to 42 | | 3. RH | Relative Humidity (%) — range: 21 to 90 | | 4. Ws | Wind Speed (km/h) — range: 6 to 29 | | 5. Rain | Daily Rainfall (mm) — range: 0 to 16.8 | | 6. FFMC | Fine Fuel Moisture Code — range: 28.6 to 92.5 | | 7. DMC | Duff Moisture Code — range: 1.1 to 65.9 | | 8. DC | Drought Code — range: 7 to 220.4 *(Not used in model)* | | 9. ISI | Initial Spread Index — range: 0 to 18.5 | | 10. BUI | Buildup Index — range: 1.1 to 68 *(Not used in model)* | | 11. FWI | Fire Weather Index — range: 0 to 31.1 *(May be used as target)* | | 12. Classes | **Output Label**: Fire / Not Fire | --- ## 🤖 Project Overview This project demonstrates the deployment of a **machine learning model** via a **Flask web interface**. The user can input weather and fire index values, and the model will predict the likelihood or severity of a forest fire based on training from the Algerian dataset. --- ## 🧠 Machine Learning Model - **Model**: Ridge Regression - **Scaler**: StandardScaler - **Target**:- **Classes** — Binary classification with two possible valu …