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Aggregation Algorithm Vs. Average for Time Series Prediction.

Jamil, W., Kalnishkan, Y. and Bouchachia, A., 2016. Aggregation Algorithm Vs. Average for Time Series Prediction. In: ECML/PKDD 2016 Workshop on Large-scale Learning from Data Streams in Evolving Environments (STREAMEVOLV-2016), 19-23 September 2016, Riva del Garda, Italy.

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STREAMEVOLV-2016_paper_8.pdf - Accepted Version
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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 se- ries 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.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Aggregation Algorithm; time-series; auto-regressive-moving- average; auto-regressive-integrated-moving-average; Fourier transform; on-line learning.
Group:Faculty of Science & Technology
ID Code:24798
Deposited By: Symplectic RT2
Deposited On:03 Oct 2016 10:22
Last Modified:14 Mar 2022 13:59


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