ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2402.00654
  4. Cited By
Improving the accuracy of freight mode choice models: A case study using
  the 2017 CFS PUF data set and ensemble learning techniques
v1v2 (latest)

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
Diyi Liu
Hyeonsup Lim
M. Uddin
Yuandong Liu
Lee D. Han
Ho-Ling Hwang
Shih-Miao Chin
ArXiv (abs)PDFHTML

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

5 / 5 papers shown
Title
Modeling Freight Mode Choice Using Machine Learning Classifiers: A
  Comparative Study Using the Commodity Flow Survey (CFS) Data
Modeling Freight Mode Choice Using Machine Learning Classifiers: A Comparative Study Using the Commodity Flow Survey (CFS) Data
M. Uddin
Sabreena Anowar
Naveen Eluru
26
11
0
01 Feb 2024
Kaggle forecasting competitions: An overlooked learning opportunity
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
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
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
Model-Agnostic Interpretability of Machine Learning
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
88
839
0
16 Jun 2016
1