Feature Significance in Traffic Accident Prediction Using Random Forest Algorithm

Author(s)	Reena S
Country	India
Abstract	Traffic accidents are a significant global issue, impacting public safety, infrastructure, and the economy. Predicting these accidents can help in effective decision-making and mitigation strategies. This project explores the use of Random Forest, a robust machine learning algorithm, for predicting traffic accidents. By analysing various factors such as road conditions, weather, traffic density, and time of day, the study aims to identify key features that contribute most to traffic accidents. Feature importance, derived from the Random Forest model, highlights the variables that have the greatest influence on accident occurrence. The results provide valuable insights into accident prevention strategies and guide policymakers in making data-driven decisions for enhancing road safety.
Field	Computer Applications
Published In	Volume 4, Issue 2, March-April 2022
Published On	2022-03-08

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International Journal For Multidisciplinary Research