Predicting transport mode choice preferences in a university district with decision tree-based models
Modeling and prediction of mode choice are essential to support more sustainable and safer transportation decisions. There is plenty of literature in this decade showing that machine learning (ML) models have been effective predicting techniques, although not easily interpretable. When these techniq...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-12-01
|
Series: | City and Environment Interactions |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S259025202300020X |