honeyvig/Algerian-Forest-Fires-ML

# Algerian_forest_fires_dataset Algerian Forest Fires Dataset Analysis This project focuses on analyzing the Algerian Forest Fires dataset, which includes meteorological and fire-related data from two regions in Algeria (Setif and Bejaia). The main goal is to understand the patterns behind forest fires and help predict fire risk using machine learning models. 📁 Dataset Source: UCI Machine Learning Repository Regions: Bejaia and Sidi-Bel Abbes Features: Includes weather data like temperature, relative humidity (RH), wind speed, rain, and fire indexes such as FFMC, DMC, DC, ISI, BUI, and FWI. Target: Classes (fire or not fire) 🔍 What This Notebook Does Loads and cleans the dataset Explores the data with visualizations Checks correlation between features Applies feature scaling Trains and tests regression models Evaluates model performance (MAE, MSE, R²) 📊 Libraries Used pandas numpy matplotlib seaborn scikit-learn 📌 Goal To build a simple and effective machine learning pipeline that helps predict the Fire Weather Index (FWI) based on weather conditions.