Prediction of bike rental using model reuse strategy

Arun Bala Subramaniyan, Rong Pan

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

Abstract

This paper describes the methodology used for ECMLPKDD 2015 Discovery Challenge on Model Reuse with Bike Rental Station Data (MoReBikeS). The challenge was to predict the number of bikes in the new stations three hours in advance. Initially, the data for the first 25 new stations (station 201 to 225) was provided and various prediction methods were utilized on these test stations and the results were updated every week. Then the full test data for the remaining 50 stations (station 226 to 275) was given and the prediction was made using the best method obtained from the small test challenge. Several methods like Ordinary Least Squares, Poisson Regression, and Zero Inflated Poisson Regression were tried. But reusing the linear models learnt from the old stations (station 1 to 200) with lowest mean absolute error proved to be the simple and effective solution.

Original languageEnglish (US)
Title of host publicationCEUR Workshop Proceedings
PublisherCEUR-WS
Volume1526
StatePublished - 2015
EventECML/PKDD 2015 Discovery Challenges, ECML-PKDD-DCs 2015 - Porto, Portugal
Duration: Sep 7 2015Sep 11 2015

Other

OtherECML/PKDD 2015 Discovery Challenges, ECML-PKDD-DCs 2015
CountryPortugal
CityPorto
Period9/7/159/11/15

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Subramaniyan, A. B., & Pan, R. (2015). Prediction of bike rental using model reuse strategy. In CEUR Workshop Proceedings (Vol. 1526). CEUR-WS.