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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Official URL: http://www.ecmlpkdd2016.org/
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|
|Deposited By:||Unnamed user with email symplectic@symplectic|
|Deposited On:||03 Oct 2016 10:22|
|Last Modified:||03 Oct 2016 10:28|
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