Analysis on Survival Probability in Road Accidents using Data Mining Techniques

Road traffic accidents are a significant cause of injury and death, making it crucial to predictsurvival chances for individuals involved. This study uses data mining techniques to predict the likelihoodof survival following road accidents based on various factors such as Crash Type, Speed Limit, Road. User,Gender, Survive. The analysis involves applying Data mining models like Decision tree, LightGBM (LightGradient Boosting Machine) and XGBoost(Extreme Gradient Boosting) to a dataset containing informationfrom past accidents. By cleaning and preparing the data, including Data Cleaning and encoding variables,the models are trained to classify whether a person will survive or not in an accident. The results show thatcertain factors, such as accident severity and vehicle type, are crucial for predicting survival. The studyhighlights the potential of data mining to enhance road safety measures and emergency response systems byproviding insights into the factors that influence survival outcomes in road accidents.