Aggregation Algorithm vs. Average For Time Series Prediction

Waqas Jamil, Yury Kalnishkan, Hamid Bouchachia

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

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Learning with expert advice as a scheme of on-line learning has been very successfully applied to various learning problems due to its strong theoretical basis. In this paper, for the purpose of times series prediction, we investigate the application of Aggregation Algorithm, which a generalisation of the famous weighted majority algorithm. The results of the experiments done, show that the Aggregation Algorithm performs very well in comparison to average.
Original languageEnglish
Title of host publicationProceedings of the ECML PKDD 2016 Workshop on Large-scale Learning from Data Streams in Evolving Environments, STREAMEVOLV-2016
Number of pages14
Publication statusPublished - 23 Sept 2016


  • Aggregation Algorithm; time-series; auto-regressive-moving-average; auto-regressive-integrated-moving-average; Fourier transform; on-line learning

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