Unveiling the influence of behavioural, built environment and socio-economic features on the spatial and temporal variability of bus use using explainable machine learning

Documents similaires

• Uncovering key predictors of high-growth firms via explainable machine learning
  par: Huang, Yiwei, et autres
  Publié: (2024)
• Countrywide natural experiment reveals impact of built environment on physical activity
  par: Althoff, Tim, et autres
  Publié: (2024)
• Are machine learning technologies ready to be used for humanitarian work and development?
  par: Sekara, Vedran, et autres
  Publié: (2023)
• The geography of inequalities in access to healthcare across England: the role of bus travel time variability
  par: Chen, Zihao, et autres
  Publié: (2025)
• An explainable machine learning approach for energy forecasting at the household level
  par: Béraud, Pauline, et autres
  Publié: (2024)