Classification of imbalanced travel mode choice to work data using adjustable SVM model

• Main Authors: Qian, Yufeng, Aghaabbasi, Mahdi, Ali, Mujahid, Alqurashi, Muwaffaq, Salah, Bashir, Zainol, Rosilawati, Moeinaddini, Mehdi, Hussein, Enas E.
• Format: Article
• Published: MDPI 2021
• Subjects: QC Physics; QD Chemistry; TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.um.edu.my/33878/

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...