SenaGemici/Algerian-Forest-Fires-ML

This project analyzes the Algerian Forest Fires dataset from Kaggle. The goal is to predict the Fire Weather Index (FWI) using multiple regression models and to compare their performance. The dataset was obtained from Kaggle:Algerian Forest Fires Datas… 1. Data Cleaning: missing values, column name cleanup 2. One Hot Encoding for categorical features 3. Exploratory Data Analysis (EDA) 4. Correlation analysis to reduce multicollinearity 5. Model building and comparison: - Linear Regression - Lasso - LassoCV - Ridge - RidgeCV - ElasticNet - ElasticNetCV - The target variable for prediction is the Fire Weather Index (FWI). After comparing all models, Linear Regression gave the best performance in predicting FWI.