Development and application of TeEMs (Telecommuting Expectation Models): Predicting post-pandemic Telecommuting Choice and Frequency using Machine learning models
The Choice model had balanced dataset and AdaBoost model obtained the highest values for every criterion except precision, followed by Gradient Boost model. Age, Commute distance and Time were most important attributes.
Authors
- Melanie Sattler (ORCID: https://orcid.org/0000-0002-3760-2780)
- Arasambattu K. Mohanakrishnan (ORCID: https://orcid.org/0000-0002-3758-4578)
- Victoria Chen (ORCID: https://orcid.org/0009-0001-5527-7168)
Institutions
- The University of Texas at Arlington (US)
Publication Details
- Published
- 2025-04-29
- DOI
- https://doi.org/10.18260/1-2--55041
- Primary Topic
- Human Mobility and Location-Based Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation