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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主要な著者:	Bita Ghasemkhani, Kadriye Filiz Balbal, Kokten Ulas Birant, Derya Birant
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2025-01-01
シリーズ:	Mathematics
主題:	machine learning traffic accident severity prediction ordinal classification feature selection random tree road traffic accident
オンライン･アクセス:	https://www.mdpi.com/2227-7390/13/2/310
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