IRJET - Predicting Accident Severity using Machine Learning

This document discusses predicting accident severity using machine learning. It begins with background on the large human and economic toll of road accidents worldwide. It then discusses using machine learning techniques like association rule mining to discover patterns between accident types and injury types in a dataset. Specifically, it uses an unsupervised learning approach with the Eclat algorithm to build a model and identify these patterns from accident records of a particular area. This can help traffic authorities and medical professionals better analyze accidents and injuries.