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...
| Main Authors: | Qian, Y., Aghaabbasi, M., Ali, M., Alqurashi, M., Salah, B., Zainol, R., Moeinaddini, M., Hussein, E.E. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.29606 / |
| Published: |
MDPI
2021
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121446235&doi=10.3390%2fapp112411916&partnerID=40&md5=e3dcd54289547b7d81ece73df251bc85 http://eprints.utp.edu.my/29606/ |
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