Abstract: Accidents are among the crucial problems the world is facing nowadays as they cause many demises, bruises, and mortalities as well as consistent loss of the economy. Exact frameworks to say the extremity in the accident is a crucial work to vehicular systems. This analysis work initiates representation in choosing many important parameters and to put up a framework for grouping the extremity of injuries. These frameworks are prepared by many machine ML techniques. Supervised learning techniques and unsupervised ML techniques are executed on set traffic accident values. The important point is to find the correlation among various types of the accidents with the type of the bruises. The survey of this study points out that unsupervised learning techniques could be a favorable aid to know the extremity and severity caused in an accident injury.
Keywords: Machine Learning, Traffic Accident, Unsupervised Learning, Eclat Algorithm, Injuries.
| DOI: 10.17148/IJARCCE.2020.9639