JSW 2012 Vol.7(11): 2450-2459 ISSN: 1796-217X
doi: 10.4304/jsw.7.11.2450-2459
doi: 10.4304/jsw.7.11.2450-2459
A Reuse-based Environment to Build Ensembles for Time Series Forecasting
Claudio V. Ribeiro1, Ronaldo R. Goldschmidt2, and Ricardo Choren3
1EMGEPRON/Engineering Department, Rio de Janeiro/RJ, Brazil
2UFRRJ/Technology and Languages Department, Nova Iguaçu/RJ, Brazil
3IME/Computer Engineering Department, Rio de Janeiro/RJ, Brazil
Abstract—Several works show that ensembles improve the performance of time series forecasting solutions. However, developing an ensemble is not an easy task. Usually, the analyst has to develop each ensemble as a separate project, designing, implementing and configuring the individual and the ensemble methods for each experiment. This paper proposes a change to this common view. It argues that it is possible and necessary to also look from a reuse perspective. Combining ideas from reuse and time series forecasting requirements, this paper proposes an environment to enable reusability for ensemble development. The environment intends to provide a flexible tool for the analyst to include, configure and execute individual methods and to build and execute ensemble experiments.
Index Terms—ensembles, time series forecasting, reuse, environment
2UFRRJ/Technology and Languages Department, Nova Iguaçu/RJ, Brazil
3IME/Computer Engineering Department, Rio de Janeiro/RJ, Brazil
Abstract—Several works show that ensembles improve the performance of time series forecasting solutions. However, developing an ensemble is not an easy task. Usually, the analyst has to develop each ensemble as a separate project, designing, implementing and configuring the individual and the ensemble methods for each experiment. This paper proposes a change to this common view. It argues that it is possible and necessary to also look from a reuse perspective. Combining ideas from reuse and time series forecasting requirements, this paper proposes an environment to enable reusability for ensemble development. The environment intends to provide a flexible tool for the analyst to include, configure and execute individual methods and to build and execute ensemble experiments.
Index Terms—ensembles, time series forecasting, reuse, environment
Cite: Claudio V. Ribeiro, Ronaldo R. Goldschmidt, and Ricardo Choren<, "A Reuse-based Environment to Build Ensembles for Time Series Forecasting," Journal of Software vol. 7, no. 11, pp. 2450-2459, 2012.
General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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