aliy112005/Forest-Fire-Prediction

This project focuses on Algeria, one of many countries affected by this phenomenon. It uses Python-based machine learning and data science libraries to build a model capable of predicting forest fires based on meteorological data. # Predicting Forest Fires in Algeria ## 1.0 Introduction Forest fires are a significant environmental concern, causing both ecological and economical damage, burning large land areas, and displacing communities. While forest ecosystems could once recover from naturally occurring fires, climate change—with its longer droughts and rising temperatures—has hindered this recovery process. Therefore, preventing wildfires or detecting them early to limit their damage is an increasingly important goal. This project focuses on Algeria, one of many countries affected by this phenomenon. It uses Python-based machine learning and data science libraries to build a model capable of predicting forest fires based on meteorological data. ## 2.0 Problem Definition Given meteorological and locational data from two regions in Algeria, can we build a machine learning model to predict whether a forest fire will occur ("fire") or not ("not fire")? ## 3.0 Dataset The data for this project is a modified version of the Algerian Forest Fires Dataset, originally from the UCI Machine Learning Repository. * **Original Source:** UCI ML Repository * **Dataset File:** `ForestFire.csv` The dataset includes 243 instances covering forest fires across two regions of Algeria. It contains 11 attributes and 1 target attribute. ### Features (Data Dictionary) | Attribute | Description | | :--- | :--- | | **Day** | Day of the month | | **Month** | Month of the year ('june' to 'september') | | **Temp** | Temperature at noon (max) in Celsius (22 to 42) | | **RH** | Relative Humidity in % (21 to 90) | | **Ws** | Wind speed in km/h (6 to 29) | | **Rain** | Total rain for the day in mm (0 to 16.8) | | **FFMC** | Fine Fuel Moisture Code: Moisture of surface litter (key to ignition) | | **DMC** | Duff Moisture Code: Moisture of shallow organic layers | | **DC** | Drought Code: Moisture of deep organic layers | | **ISI** | Initial Spread Index: Score correlating with fire velocity spread | | **BUI** | Bui …