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Relationships between Transportation Expenditures and Built Environment in the United States: Insights from Interpretable Machine-Learning Approach
16 references·0 citing·48 second hop
Relationships between Transportation Expenditures and Built Environment in the United States: Insights from Interpretable Machine-Learning Approach (2024)Relationships between Transportation Expe…Understanding cycling distance according to the prediction of the XGBoost and the interpretation of SHAP: A non-linear and interaction effect analysis (2022)Understanding cycling distanc…Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach (2021)Non-linear associations betwe…Choice modelling in the age of machine learning - Discussion paper (2021)Choice modelling in the age o…Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models (2020)Prediction and behavioral ana…Bike-sharing or taxi? Modeling the choices of travel mode in Chicago using machine learning (2019)Bike-sharing or taxi? Modelin…Synergistic effects of the built environment and commuting programs on commute mode choice (2018)Synergistic effects of the bu…Machine Learning Travel Mode Choices: Comparing the Performance of an Extreme Gradient Boosting Model with a Multinomial Logit Model (2018)Machine Learning Travel Mode …Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo (2018)Applying gradient boosting de…Application of eXtreme gradient boosting trees in the construction of credit risk assessment models for financial institutions (2018)Application of eXtreme gradie…A comparative study of machine learning classifiers for modeling travel mode choice (2017)A comparative study of machin…Intelligent Agent Transparency in Human–Agent Teaming for Multi-UxV Management (2016)Intelligent Agent Transparenc…A meta-analysis of the impact of rail projects on land and property values (2013)A meta-analysis of the impact…Travel and the Built Environment (2010)Travel and the Built Environm…Cities, regions and the decline of transport costs (2003)Cities, regions and the decli…Identifying the Impacts of Rail Transit Stations on Residential Property Values (2001)Identifying the Impacts of Ra…Travel demand and the 3Ds: Density, diversity, and design (1997)Travel demand and the 3Ds: De…Impacts of Mixed Use and Density on Utilization of Three Modes of Travel: Single-Occupant Vehicle, Transit, and Walking (1994)A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area (1997)Environmental correlates of walking and cycling: Findings from the transportation, urban design, and planning literatures (2003)AN ECOLOGICAL APPROACH TO CREATING ACTIVE LIVING COMMUNITIES (2005)Multiple Factor Analysis (2007)Analysis of Panel Data (2003)A meta-analysis of estimates of urban agglomeration economies (2008)Commuter rail accessibility and house values: The case of the Montreal South Shore, Canada, 1992–2009 (2013)A spatial Difference-in-Differences estimator to evaluate the effect of change in public mass transit systems on house prices (2014)Accessibility to transit, by transit, and property prices: Spatially varying relationships (2020)Cities and Housing. 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References

  • 2010Travel and the Built Environment5,396 cited
  • 1997Travel demand and the 3Ds: Density, diversity, and design4,588 cited
  • 2001Identifying the Impacts of Rail Transit Stations on Residential Property Values861 cited
  • 2003Cities, regions and the decline of transport costs642 cited
  • 2018Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo446 cited
  • 2017A comparative study of machine learning classifiers for modeling travel mode choice423 cited
  • 2020Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models406 cited
  • 2016Intelligent Agent Transparency in Human–Agent Teaming for Multi-UxV Management403 cited
  • 2018Application of eXtreme gradient boosting trees in the construction of credit risk assessment models for financial institutions320 cited
  • 2013A meta-analysis of the impact of rail projects on land and property values282 cited
  • 2021Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach250 cited
  • 2018Machine Learning Travel Mode Choices: Comparing the Performance of an Extreme Gradient Boosting Model with a Multinomial Logit Model214 cited
  • 2018Synergistic effects of the built environment and commuting programs on commute mode choice199 cited

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2022
Understanding cycling distance according to the prediction of the XGBoost and the interpretation of SHAP: A non-linear and interaction effect analysis
150 cited
  • 2021Choice modelling in the age of machine learning - Discussion paper140 cited
  • 2019Bike-sharing or taxi? Modeling the choices of travel mode in Chicago using machine learning93 cited
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