shrutiranipoddar/Algerian_forest_fire_prediction

# 🔥 Algerian Forest Fire - Temperature Prediction using Ridge Regression This project uses **Ridge Regression**, a regularized linear regression technique, to predict the **temperature** in Algerian forest regions. Accurate temperature prediction is important for anticipating wildfire risks and enabling early fire management. --- ## 📊 Problem Statement Forest fires are a major environmental hazard in Algeria, especially during summer. Understanding how weather variables influence temperature can help prevent catastrophic events. This project builds a **regression model** to predict **temperature** using multiple environmental and meteorological features from two Algerian regions: Bejaia and Sidi-Bel Abbes. --- ## 🧠 ML Approach ### ✅ Model Used - **Ridge Regression** (Linear regression with L2 regularization) ### ⚙️ Preprocessing - **StandardScaler** from `sklearn.preprocessing` was used to normalize features. ### 📈 Evaluation Metrics - Mean Absolute Error (MAE) - Mean Squared Error (MSE) - R² Score ---