Road-Traffic-Accident-Analysis

This repository contains an in-depth analysis of traffic accident datasets from Toronto and Rawalpindi, utilizing Machine Learning and Association Rule Mining to identify factors contributing to severe injuries. The study develops predictive solutions, compares accident factors across regions, and proposes a framework for enhancing road safety in urban environments. Key methods include PyCaret for model training/testing and various advanced ML/DL techniques本仓库包含针对多伦多（Toronto）与拉瓦尔品第（Rawalpindi）两市交通事故数据集的深度分析，借助机器学习（Machine Learning）与关联规则挖掘（Association Rule Mining）技术，识别引发重伤的事故影响因素。本研究开发了交通事故预测解决方案，对比了不同区域的事故影响因素，并提出了一套用于提升城市道路交通安全水平的框架。核心研究方法包括使用PyCaret开展模型训练与测试，以及多种先进的机器学习/深度学习（ML/DL）技术。