SamsonAdeolu/Predicting-Forest-Fire-Occurrence-and-Severity-in-Algeria

To analyze and predict the occurrence and severity of forest fires in Algeria using meteorological and environmental data from the Algerian Forest Fires dataset # Predicting-Forest-Fire-Occurrence-and-Severity-in-Algeria To analyze and predict the occurrence and severity of forest fires in Algeria using meteorological and environmental data from the Algerian Forest Fires dataset Project Title: Predicting Forest Fire Occurrence and Severity in Algeria Objective: To analyze and predict the occurrence and severity of forest fires in Algeria using meteorological and environmental data from the Algerian Forest Fires dataset. Dataset Overview: Name: Algerian Forest Fires Processed Dataset Source: UCI Machine Learning Additional Information The dataset includes 244 instances that regroup data from two regions of Algeria, namely the Bejaia region, located in the northeast of Algeria, and the Sidi Bel-Abbes region, located in the northwest of Algeria. 122 instances for each region. The period from June 2012 to September 2012. The dataset includes 11 attributes and 1 output attribute (class). The 244 instances have been classified into “fires” (138 classes) and “not fire”(106 classes) classes Attributes: - Date, Temperature, RH (Relative Humidity), Ws (Wind Speed), Rain, FFMC, DMC, DC, and ISI (fire weather indices) - Classes: fire, not fire Project Scope: Students will perform: - Exploratory Data Analysis (EDA) - Data Preprocessing - Feature Engineering - Supervised Machine Learning (Classification) - Model Evaluation & Selection - Visualization & Interpretation - Model Deployment (optional but ideal) 🛠️ Tools & Libraries: - Python (Jupyter/Colab) - Pandas, NumPy, Matplotlib, Seaborn - Scikit-learn - Streamlit or Flask (for deployment) - Git & GitHub (for version control) Project Workflow: 🔹 1. Problem Statement Forest fires in Algeria cause serious environmental damage. Predicting their occurrence can help in proactive disaster management. 🔹 2. Data Collection Students should: - Download the dataset from the UCI Repository - Store it as a CSV file (Algerian_forest_fires.csv) 🔹 3. Exploratory Data Analysis (EDA) Tasks: - Inspect co …