This repo contains the models my team and I trained for the car evaluation, car accident and fungi classification datasets of the week-long Datathon hosted by the University of Toronto Scarborough's Data Science and Statistics Society. The datasets are linked below.
We used ensemble models, decision trees, boosting methods and neural networks (+ experimented with a denoising autoencoder neural net for the fungi image set).
Shoutout to Lucas, Mingyuan and Tony.
Fungi image set: arXiv:2109.07322 / https://doi.org/10.48550/arXiv.2109.07322
Car evaluation dataset: https://doi.org/10.24432/C5JP48.
Car accident dataset: https://doi.org/10.48550/arXiv.1906.05409
Citations (in same order as above):
Fungi: arXiv:2109.07322
Car Eval: Bohanec, M. (1988). Car Evaluation [Dataset]. UCI Machine Learning Repository.
Car Accidents:
- Moosavi, Sobhan, Mohammad Hossein Samavatian, Srinivasan Parthasarathy, and Rajiv Ramnath. “A Countrywide Traffic Accident Dataset.”, 2019.
- Moosavi, Sobhan, Mohammad Hossein Samavatian, Srinivasan Parthasarathy, Radu Teodorescu, and Rajiv Ramnath. "Accident Risk Prediction based on Heterogeneous Sparse Data: New Dataset and Insights." In proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM, 2019.