pranavasu/Road-Traffic-Severity-Classification

This project aims to classify the severity of road accidents into three categories based on real-world data collected from Addis Ababa Sub-city, Ethiopia police departments for the years 2017-2020. # Road-Traffic-Severity-Classification ## Overview This project aims to classify the severity of road accidents into three categories based on real-world data collected from Addis Ababa Sub-city, Ethiopia police departments for the years 2017-2020. The dataset contains 32 features and 12,316 instances of accidents. The primary goal is to predict accident severity using various machine learning classification algorithms. ## Dataset Source - Link to the dataset ## Project Description ### Data Collection The dataset was obtained from manual records of road traffic accidents and has undergone preprocessing to exclude sensitive information. It comprises records from the years 2017 to 2020. ### Problem Statement The target feature for this project is `Accident_severity`, a multi-class variable with three categories. The objective is to classify accident severity based on the other 31 features. F1-score has been choosen as the evaluation metric.