Ensemble-based method for Task 2: Predicting traffic Jam

Jingrui He, Qing He, Grzegorz Swirszcz, Yiannis Kamarianakis, Rick Lawrence, Wei Shen, Laura Wynter

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationProceedings - 10th IEEE International Conference on Data Mining Workshops, ICDMW 2010
Pages1363-1365
Number of pages3
DOIs
StatePublished - Dec 1 2010
Externally publishedYes
Event10th IEEE International Conference on Data Mining Workshops, ICDMW 2010 - Sydney, NSW, Australia
Duration: Dec 14 2010Dec 17 2010

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Conference

Conference10th IEEE International Conference on Data Mining Workshops, ICDMW 2010
CountryAustralia
CitySydney, NSW
Period12/14/1012/17/10

Keywords

  • Cross validation
  • Ensemble
  • Nearest-neighbor

ASJC Scopus subject areas

  • Engineering(all)

Cite this

He, J., He, Q., Swirszcz, G., Kamarianakis, Y., Lawrence, R., Shen, W., & Wynter, L. (2010). Ensemble-based method for Task 2: Predicting traffic Jam. In Proceedings - 10th IEEE International Conference on Data Mining Workshops, ICDMW 2010 (pp. 1363-1365). [5693453] (Proceedings - IEEE International Conference on Data Mining, ICDM). https://doi.org/10.1109/ICDMW.2010.54