veeravallisarathkumar/Algerian_forest_fires_Projects

# Algerian Forest Fire Dataset Analysis This repository contains an analysis of the **Algerian Forest Fire Dataset**, along with tools and code to preprocess, analyze, and model the data. The dataset focuses on forest fire incidents in Algeria and includes meteorological, environmental, and fire-related parameters. --- ## Table of Contents - **Introduction** - **Dataset Description** - **Features** - **Features of the Project** - **Prerequisites** - **Installation & Setup** - **File Structure** - **How to Use** - **Customization** - **License** --- ## Introduction - The **Algerian Forest Fire Dataset** provides data for two distinct regions in Algeria: the **Bejaia Region** and the **Sidi Bel-abbes Region**. - This project explores the data to gain insights into the factors affecting forest fires. - It applies machine learning models to predict fire occurrence and severity based on environmental and meteorological variables. - The goal is to develop predictive models that can assist in fire prevention and management strategies. --- ## Dataset Description - The dataset contains records from **June 1st to September 30th, 2012**. - It includes the following: - **Meteorological data** (e.g., temperature, relative humidity, wind speed). - **Fire Weather Index (FWI) parameters**. - **Region-specific information**. - **Fire occurrence indicators** (classes: `Fire` or `No Fire`). --- ## Features - **Region**: The region of Algeria (Bejaia or Sidi Bel-abbes). - **Date**: Day, month, and year of the observation. - **Temperature (°C)**: Average temperature of the day. - **RH (%)**: Relative humidity percentage. - **Ws (km/h)**: Wind speed. - **Rain (mm)**: Rainfall in millimeters. - **FWI System Parameters**: Includes FFMC, DMC, DC, ISI, BUI, and FWI values. - **Classes**: Binary class indicating the presence of a fire (`Fire` or `No Fire`). --- ## Features of the Project - **Data Cleaning**: Handles missing or corrupted data. - **Exploratory Data Analysis (ED …