iamvrvasanth/Algerian-Forest-Fire-Prediction

End-to-end Machine Learning project for predicting the Fire Weather Index (FWI) using weather parameters, featuring a responsive Flask web application. # Algerian Forest Fire Prediction using Machine Learning An end-to-end Machine Learning project that predicts the **Fire Weather Index (FWI)** using meteorological observations from the Algerian Forest Fires dataset. The project demonstrates the complete ML workflow including data preprocessing, exploratory data analysis, feature engineering, model training, evaluation, and deployment through a Flask web application. --- ## Project Overview The Fire Weather Index (FWI) is an indicator used to estimate wildfire risk based on weather conditions. This project uses historical weather observations to train a machine learning regression model capable of predicting the FWI for new environmental conditions. The application allows users to enter weather parameters through a web interface and instantly receive the predicted Fire Weather Index. --- ## Features - End-to-end Machine Learning workflow - Data Cleaning and Preprocessing - Exploratory Data Analysis (EDA) - Feature Engineering - Feature Scaling using StandardScaler - Multiple Regression Model Training - Model Performance Evaluation - Best Model Selection - Model Serialization using Pickle - Interactive Flask Web Application - Modern Responsive User Interface - Input Validation using dataset value ranges --- ## Dataset **Dataset:** Algerian Forest Fires Dataset The dataset contains meteorological observations collected from two regions in Algeria. - Bejaia Region - Sidi Bel-Abbes Region ### Input Features | Feature | Description | |----------|-------------| | Temperature | Air Temperature (°C) | | RH | Relative Humidity (%) | | Ws | Wind Speed (km/h) | | Rain | Rainfall (mm) | | FFMC | Fine Fuel Moisture Code | | DMC | Duff Moisture Code | | ISI | Initial Spread Index | | Classes | Fire / Not Fire | | Region | Region Identifier | ### Target Variable - Fire Weather Index (FWI) --- # Machine Learning Workflow ### 1. Data Collection - Load the Algerian Forest Fires dataset ### 2. Data Preprocessing …