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Title: Road Accident Predictions as a Classification Problem
Authors: Agrawal, Madhulika
Gonçalves, Teresa
Quaresma, Paulo
Issue Date: 2021
Citation: Madhulika Agrawal, Teresa Gonçalves, and Paulo Quaresma. Road Accident Predictions as a Classification Problem. In Proceedings of the 27th Portuguese Conference on Pattern Recognition, RECPAD 2021, 2021.
Abstract: This paper aims at evaluating the performance of various classification methods for road accident prediction. The data is collected under MO- PREVIS [3] project which aims at improving road safety in Portugal. The data is highly imbalanced as there are fewer accident instances than the non-accident ones and due to this imbalance, it is observed that the tra- ditional classification algorithms do not perform well. Using sampling techniques (undersampling and oversampling) improved the results but not significantly. Some methods resulted in increased recall but that de- creased precision as the algorithm returned more false positives to make up for data imbalance.
Type: article
Appears in Collections:INF - Artigos em Livros de Actas/Proceedings

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