ReMAHA–CatBoost: Addressing Imbalanced Data in Traffic Accident Prediction Tasks

ReMAHA–CatBoost: Addressing Imbalanced Data in Traffic Accident Prediction Tasks

Using historical information from traffic accidents to predict accidents has always been an area of active exploration by researchers in the field of transportation. However, predicting only the occurrence of traffic accidents is insufficient for providing comprehensive information to relevant autho...

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Bibliographic Details
Main Authors:	Guolian Li, Yadong Wu, Yulong Bai, Weihan Zhang
Format:	Article
Language:	English
Published:	MDPI AG 2023-12-01
Series:	Applied Sciences
Subjects:	relief–F imbalanced data CatBoost traffic accident class imbalance
Online Access:	https://www.mdpi.com/2076-3417/13/24/13123

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