richa-m/algerian-forest-fire-prediction

Machine learning project for predicting the Fire Weather Index (FWI) using Algerian forest fire and meteorological data. # 🔥 Algerian Forest Fire Prediction A Machine Learning project for predicting the **Fire Weather Index (FWI)** using meteorological and fire-weather data from the Algerian Forest Fires dataset. ## 📌 Project Overview Forest fires are influenced by various weather and environmental conditions such as temperature, humidity, wind speed, rainfall, and moisture levels. In this project, different Machine Learning regression models are trained to predict the **Fire Weather Index (FWI)**. The project covers the complete workflow: ```text Raw Dataset ↓ Data Cleaning ↓ Exploratory Data Analysis ↓ Feature Selection ↓ Feature Scaling ↓ Train-Test Split ↓ Model Training ↓ Model Evaluation ``` ## 🎯 Objective The main objective of this project is to predict **FWI (Fire Weather Index)** using meteorological and fire-related features. This is a: **Supervised Learning → Regression Problem** because FWI is a continuous numerical value. --- ## 📊 Dataset The project uses the **Algerian Forest Fires Dataset**, which contains weather and fire-related observations from two regions of Algeria. ### Features | Feature | Description | | ----------- | ----------------------- | | Temperature | Temperature | | RH | Relative Humidity | | Ws | Wind Speed | | Rain | Rainfall | | FFMC | Fine Fuel Moisture Code | | DMC | Duff Moisture Code | | DC | Drought Code | | ISI | Initial Spread Index | | BUI | Buildup Index | | FWI | Fire Weather Index | | Classes | Fire / Not Fire | | Region | Region identifier | --- ## 📁 Project Structure ```text algerian-forest-fire-prediction/ │ ├── data/ │ ├── Algerian_forest_fires_dataset_UPDATE.csv │ └── Algerian_forest_fires_cleaned_dataset.csv │ ├── notebooks/ │ ├── data_cleaning_and_eda.ipynb │ └── model_training.ipynb │ ├── README.md └── requirements.t …