Deepdavara03/Algerian_forest_ml

# 🌲 Algerian Forest Fire Prediction (ML Project) This project predicts the **burned area of forest fires** in Algeria using **Machine Learning (Ridge Regression)** based on meteorological and fire weather index (FWI) features. The model is deployed using **Flask** with a simple web interface. --- ## 📌 Project Overview Forest fires cause severe environmental and economic damage. This project uses historical weather and fire index data from **Algerian forests** to predict the **area burned (in hectares)**. --- ## 🧠 Machine Learning Concepts Used - Linear Regression - Ridge Regression (L2 Regularization) - Feature Scaling (StandardScaler) - Model Serialization (Pickle) - Flask Web Application --- ## 📊 Dataset Information **Dataset:** Algerian Forest Fires Dataset **Features:** - Temperature - RH (Relative Humidity) - Ws (Wind Speed) - Rain - FFMC - DMC - DC - ISI - Classes - Region **Target:** Area burned (in hectares) --- ## 🏗️ Project Structure ML_Algerian_forest/ │ ├── application.py ├── requirements.txt ├── README.md │ ├── model/ │ ├── ridreg.pkl │ └── scaler.pkl │ ├── templates/ │ ├── home.html │ └── index.html --- ## 🚀 How to Run the Project ```bash git clone github.com cd ML_Algerian_forest pip install -r requirements.txt python application.py ``` Open browser: 127.0.0.1 --- ## 📦 Libraries Used - Python - NumPy - Pandas - Scikit-learn - Flask --- ## 🔮 Future Improvements - Better UI (Bootstrap) - Deployment on cloud - Advanced ML models ---