Analysis of Travel Mode Choice in Seoul Using an Interpretable Machine Learning Approach
Understanding choice behavior regarding travel mode is essential in forecasting travel demand. Machine learning (ML) approaches have been proposed to model mode choice behavior, and their usefulness for predicting performance has been reported. However, due to the black-box nature of ML, it is diffi...
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| Format: | Article |
| Language: | English |
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Hindawi-Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/6685004 |