Ordinal Random Tree with Rank-Oriented Feature Selection (ORT-ROFS): A Novel Approach for the Prediction of Road Traffic Accident Severity

Road traffic accident severity prediction is crucial for implementing effective safety measures and proactive traffic management strategies. Existing methods often treat this as a nominal classification problem and use traditional feature selection techniques. However, ordinal classification methods...

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Bibliografiska uppgifter

Huvudupphov:	Bita Ghasemkhani, Kadriye Filiz Balbal, Kokten Ulas Birant, Derya Birant
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2025-01-01
Serie:	Mathematics
Ämnen:	machine learning traffic accident severity prediction ordinal classification feature selection random tree road traffic accident
Länkar:	https://www.mdpi.com/2227-7390/13/2/310
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