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ToolsJamil, 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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Official URL: http://www.ecmlpkdd2016.org/
Abstract
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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