CodeByAarish/Algeria-Forest-Fire-Prediction

# 🔥 Forest Fire Prediction using Polynomial Regression Welcome to the **Forest Fire Prediction System** — a smart machine learning project designed to help assess and prevent the risk of forest fires using real-time weather and environmental data. --- ## 🌟 About the Project Forest fires can spread rapidly and devastate ecosystems. Early prediction of fire-prone conditions is **crucial**. This project uses **Polynomial Regression** to predict the **FWI (Fire Weather Index)** — a numerical indicator that represents the potential for forest fires based on several environmental features. --- ## 📊 Features Used Below are the key input variables used for prediction: | 🔢 Feature | 📘 Description | |--------------------|----------------| | 🌡️ `Temperature` | Air temperature in Celsius (°C) | | 💧 `RH` | Relative Humidity in percentage (%) | | 🌬️ `Ws` | Wind speed in km/h | | ☔ `Rain` | Rainfall in mm | | 🔥 `FFMC` | Fine Fuel Moisture Code (dryness of leaves/grass) | | 🌲 `DMC` | Duff Moisture Code (moisture of loosely compacted organic material) | | 🌳 `DC` | Drought Code (moisture of deep compact organic matter) | | 🌀 `ISI` | Initial Spread Index (expected fire spread rate) | | 📈 `BUI` | Build-Up Index (total amount of fuel available for burning) | | 🗺️ `Region` | Area code (1 = Bejaia, 2 = Sidi-Bel Abbes) | | 🚨 `Classes` | Binary flag: 1 = Fire occurred, 0 = No fire | ---