Ensemble-based method for Task 2: Predicting traffic Jam

Author

Jingrui HE
Qing HE
Grzegorz SWIRSZCZ
Yiannis KAMARIANAKIS
Rick LAWRENCE
Wei SHEN
Laura WYNTER

Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

12-2010

Abstract

In this paper, we describe our solution for ICDM 2010 Contest Task 2 (Jams), where the task is to predict future where the next traffic jams will occur in morning rush hour, given data gathered during the initial phase of this peak period. Our solution, which is based on an ensemble approach, finished Second in the final evaluation.

Keywords

Cross validation, Ensemble, Nearest-neighbor

Discipline

Numerical Analysis and Scientific Computing | Transportation

Research Areas

Intelligent Systems and Optimization

Areas of Excellence

Digital transformation

Publication

Proceedings of the 2010 IEEE International Conference on Data Mining Workshops, Sydney, Australia, December 13

First Page

1363

Last Page

1365

ISBN

9780769542577

Identifier

10.1109/ICDMW.2010.54

Publisher

IEEE Computer Society

City or Country

Los Alamitos, CA

Citation

HE, Jingrui; HE, Qing; SWIRSZCZ, Grzegorz; KAMARIANAKIS, Yiannis; LAWRENCE, Rick; SHEN, Wei; and WYNTER, Laura. Ensemble-based method for Task 2: Predicting traffic Jam. (2010). Proceedings of the 2010 IEEE International Conference on Data Mining Workshops, Sydney, Australia, December 13. 1363-1365.
Available at: https://ink.library.smu.edu.sg/sis_research/10336

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

https://doi.org/10.1109/ICDMW.2010.54