PrathamCodeWorld/FWI_PREDICTION

Using Algerian Forest Fires dataset we are trying to predict FWI (Fire Weather Index) using Linear,Ridge,Lasso and ElasticNet Regression # Algerian Forest Fire Weather Index (FWI) Prediction ## Overview This project predicts the **Fire Weather Index (FWI)** using meteorological and environmental parameters from the Algerian Forest Fire dataset. The application is built using **Python**, **Flask**, and **Scikit-learn**, with a trained **Ridge Regression** model. also we have pickle file for **linear Regression** **Lasso Regression** and **Elastic Regression** --- ## Features - Predict Fire Weather Index (FWI) - User-friendly web interface - Data preprocessing using StandardScaler - Ridge Regression model - Real-time prediction through Flask --- ## Dataset Dataset: Algerian Forest Fires Dataset Features used for prediction: - Temperature - RH (Relative Humidity) - Ws (Wind Speed) - Rain - FFMC - DMC - DC - ISI - Classes - Region Target Variable: - FWI (Fire Weather Index) --- ## Technologies Used - Python - Flask - NumPy - Pandas - Scikit-learn - HTML --- ## Project Structure ``` Algerial_Forest_FWI_Prediction/ │ ├── application.py ├── requirements.txt ├── README.md ├── ml_models/ │ ├── ridge.pkl │ ├── scaler.pkl │ ├── Linearmodel.pkl │ ├── Lassomodel.pkl │ └── ElasticNetmodel.pkl │ ├── templates/ │ └── fwi_page.html │ ├── MODEL_TRAINING/ ├── algebian_feature_selection_model_training.ipynb ├── algerain_forest_clean_dataset.ipynb └── EDA_ON_algerain_foreset_dataset.ipynb ``` --- ## Installation Clone the repository ```bash git clone github.com ``` Move to the project directory ```bash cd FWI_PREDICTION ``` Create a virtual environment ```bash python -m venv venv ``` Activate the virtual environment ### macOS/Linux ```bash source venv/bin/activate ``` ### Windows ```bash venv\Scripts\activate ``` Install dependencies ```bash pip install -r requirements.txt ``` --- ## Run the Application ```bash python application.py ``` Open your browser and visit ``` 127.0.0.1 ``` --- ## Machine Learning Workflo …