Improving the accuracy of freight mode choice models: A case study using
the 2017 CFS PUF data set and ensemble learning techniques

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Improving the accuracy of freight mode choice models: A case study using the 2017 CFS PUF data set and ensemble learning techniques

1 February 2024

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Papers citing "Improving the accuracy of freight mode choice models: A case study using the 2017 CFS PUF data set and ensemble learning techniques"

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Title
Modeling Freight Mode Choice Using Machine Learning Classifiers: A Comparative Study Using the Commodity Flow Survey (CFS) Data M. Uddin Sabreena Anowar Naveen Eluru 28 11 0 01 Feb 2024
Kaggle forecasting competitions: An overlooked learning opportunity Casper Solheim Bojer Jens Peder Meldgaard AI4TS 74 207 0 16 Sep 2020
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,090 0 22 May 2017
Using Big Data to Enhance the Bosch Production Line Performance: A Kaggle Challenge Ankita Mangal Nishant Kumar 44 55 0 29 Dec 2016
Model-Agnostic Interpretability of Machine Learning Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 88 839 0 16 Jun 2016