Classification of Imbalanced Travel Mode Choice to Work Data Using Adjustable SVM Model

Classification of Imbalanced Travel Mode Choice to Work Data Using Adjustable SVM Model

The investigation of travel mode choice is an essential task in transport planning and policymaking for predicting travel demands. Typically, mode choice datasets are imbalanced and learning from such datasets is challenging. This study deals with imbalanced mode choice data by developing an algorit...

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Bibliographic Details
Main Authors:	Yufeng Qian, Mahdi Aghaabbasi, Mujahid Ali, Muwaffaq Alqurashi, Bashir Salah, Rosilawati Zainol, Mehdi Moeinaddini, Enas E. Hussein
Format:	Article
Language:	English
Published:	MDPI AG 2021-12-01
Series:	Applied Sciences
Subjects:	imbalanced data travel mode choice data hybrid support vector machine-based model
Online Access:	https://www.mdpi.com/2076-3417/11/24/11916

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