Web: http://arxiv.org/abs/2206.11056

June 23, 2022, 1:10 a.m. | Kailai Wang (University of Houston), Xize Wang (National University of Singapore)

cs.LG updates on arXiv.org arxiv.org

Whether the Millennials are less auto-centric than the previous generations
has been widely discussed in the literature. Most existing studies use
regression models and assume that all factors are linear-additive in
contributing to the young adults' driving behaviors. This study relaxes this
assumption by applying a non-parametric statistical learning method, namely the
gradient boosting decision trees (GBDT). Using U.S. nationwide travel surveys
for 2001 and 2017, this study examines the non-linear dose-response effects of
lifecycle, socio-demographic and residential factors on …

america arxiv boosting decision gen gradient lg millennials trees

More from arxiv.org / cs.LG updates on arXiv.org

Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

Data Science Intern

@ NannyML | Remote

Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY