Today, MDST participated in the student poster competition at the “Meeting the Challenges of Safe Transportation in an Aging Society Symposium”. The poster highlights the key findings from the Fatal Accident Reporting System (FARS) competition we held earlier this year. The Michigan Institute for Data Science (MIDAS) provided MDST members access to a dataset of fatal crashes in the US, with a labeled variable indicating whether alcohol was involved in the incident, and models were judged based on how well they could predict the value of this true/false variable.
The poster describes the winning model for the competition, an ensemble of a neural network and boosted decision tree, and identifies crash time, location, and the number of passengers involved, as the most predictive variables.
We want to thank MIDAS for funding the competition, Chengyu Dai and Guangsha Shi for representing MDST at the ATLAS Symposium, and the many members of MDST who participated in the FARS Challenge.
You can download the poster from the link below.
- “Inferring Alcohol Involvement in Fatal Car Accidents with Ensembled Classifiers”,Guangsha Shi, Arya Farahi, Chengyu Dai, Cyrus Anderson, Jiachen Huang, Wenbo Shen, Kristjan Greenwald, and Johnathan Stroud.